Digital Trends: 05.27.26

Why marketing leaders should treat AI enablement as change management problem

I've spent most of my career working with marketing teams as part of digital transformation initiatives in consulting and training roles. One thing I've learned is that the hardest part of these initiatives is never the technology, but managing the change around it. I see this same dynamic unfolding as marketing teams try to transform with AI, but it's even more complicated.

If you're a marketing leader trying to navigate AI enablement, try taking a more deliberate change management approach. Focusing on the fundamentals below can help you drive more effective use of AI with your team. They build on ADKAR, the change management framework developed by Prosci, adapted for the realities of AI enablement.

1. Awareness: Do people understand why changing their AI use is needed now?

Everyone is aware of AI today. You can't avoid it. Every business article and CMO interview focuses on investing more in AI. But when it comes to teams understanding the "why" driving adoption, it is unclear at best. It often feels like the reason is that everyone else is doing it, so we must too.

Marketing leaders can move past the hype by grounding any AI discussion in the context of what the marketing team needs and wants to achieve. Frame AI as a powerful new tool that can help the team. Be specific, and think in terms of "AI is now here, so finally we can..."

2. Alignment: Is leadership aligned on a direction for how to use AI?

In the early days of social media, marketing leaders needed to be part of cross-departmental teams setting up governance and guidelines for engaging in this new medium. This same horizontal collaboration is required to establish guidelines for AI that balance benefits and risks.

Marketing leaders need to advocate for AI priorities, use cases, and guardrails that will benefit their team. Establishing these guidelines becomes the foundation for what change looks like, as they describe how AI is to be used (and not used).

3. Desire: Are people motivated to change how they use AI?

This is the big one. Studies consistently rank marketing among the functions most exposed to AI, leading to credible concerns about job loss and the elimination of work that people find meaningful. How can someone be expected to support something that appears to be working against them?

Marketing leaders need to meet this head on. After all, these are concerns you may have yourself. Here it can be helpful to establish ways for people to have agency in how AI will be used. When it comes to exploring efficiency gains, have people find ways to automate busy work they do not enjoy. Better still, focus on innovation: things that couldn't have been done before. You need a compelling and credible answer to "what's in it for me?"

4. Knowledge: Do people understand how to change their use of AI?

Most marketing teams have received a mix of foundational AI training and access to online tutorials for using AI tools, with a few impressive AI demos mixed in. The challenge is that most marketing teams have not invested beyond this general training, when research shows that role-specific, hands-on training is what actually builds capability.

Marketing leaders need to sponsor the development and delivery of training that is heavily customized to their team: the tools they use, the guidelines that have been defined, and the tasks they perform. Part of this training needs to focus on ways they can find AI opportunities in their own workflows, so they are capable and confident enough to experiment independently.

5. Ability: Are people able to put changes in AI use into practice?

Even if people are motivated and trained up on AI use, marketing teams are so stretched that finding the time and space to experiment feels impossible. In these cases, teams revert to existing ways of working and basic AI use. Some marketers feel like they are not doing their jobs when they take time out to try something new or experiment with AI.

Marketing leaders need to remove these blockers and cultivate a culture where AI experimentation is expected and supported. A big part of this is coaching teams to be open to changing workflows to incorporate AI and the advantages it might present, to rethink how work gets done. Teams need permission to challenge ways of working, plus coaching support to do it effectively.

6. Reinforcement: How will people sustain these new ways of working with AI?

A big part of reinforcement is measurement: are people putting training into action? It can be tempting to measure AI usage through logins, prompts, or tokens consumed per person. Focusing on driving these usage metrics can give the impression of progress, but not necessarily improvement.

Marketing leaders need to remember that the goal should not be getting more people to use AI, but to improve outcomes using AI. Focus on measuring outcomes the marketing team is responsible for, such as brand health, lead generation, and attributed revenue. Work with teams to cultivate ways to share lessons from AI use, to support each other, and build capability collectively.

7. Evolution: How will we change our use of AI as AI evolves?

Most change management approaches assume a stable future state that everyone is working towards. AI doesn't work that way. The pace of innovation is so rapid that marketing teams cannot treat AI enablement as a change management project with an end date.

Marketing leaders need to have governance in place, along with other leaders within their organization, to regularly review performance, ideas from the team, and technical advances. Teams need to keep understanding new ways to scale and how guidelines may need to adjust. In many ways marketers are well suited for this ongoing work, responsive to constant changes in the market and media landscape.

If you are a marketing leader struggling with driving AI enablement, understand that while the technology is new, the processes around change management are well defined. Don't get distracted by the technology. Approach it in a more grounded way through the lens of change management. None of us knows exactly what the future holds, but this approach can provide you with useful tools to navigate it.

Digital Trends: 05.15.26

Hi all, hope my Canadian readers enjoyed a sunny long weekend.

This time of year is sort of funny. Maybe it’s a Toronto thing. Since the end of February, I’ve had about a dozen people I’ve been emailing with who all sign off the same way: let’s wait for patio season and have a proper catch-up. Well friends, that time has come. Looking forward to some patio drinks. And if you’d like to connect on a patio soon, reach out.

In the spirit of learning about AI together, I’ve got another short video for you. My goal is to keep making these badly enough that you can tell there’s no AI avatar involved. This one’s about a small aha moment: I realized just how many different things I can start building web apps for using vibe-coding. Here’s a quick demo of something little I made in the video below.

As I mention in the video, here are a few folks that share helpful resources on vibe-coding: Futurepedia, Jeff Su, Nate Herk.

AI & Search Marketing

It’s pretty amazing how quickly people have adopted AI for researching products and services. Our familiarity with Google, plus the fact that AI chat looks so similar from a UX perspective, has likely fuelled this. New research shows 44% of online buyers now start their journey in an LLM or split between AI tools and traditional search, and that number skews higher among younger cohorts. That AI-generated traffic is also doing more once it lands: in March 2026, it converted 42% better than other sources, a sharp reversal from March 2025 when it converted 38% worse. Is AI-generated traffic more valuable?

Marketers are responding. Many are leaning into AEO, making sure their sites are LLM-readable, and developing AI-native content. Mondelez has shared how they are making this a priority. For those who want to make sure they show up in AI search, OpenAI just launched a self-serve ad platform. Free users of ChatGPT have started seeing display ads on relevant queries this past week (below is one that served to me on a search for hotels in Toronto). A lot of the lead-up framed this as a hit to unbiased AI results, but seeing it in the wild, it feels close to the search experience we are used to. Not too disruptive. Will be interesting to see how it well it performs.

AI & Work

Microsoft released a new report on how AI is reshaping work that’s worth a skim. What stood out to me was the role of culture and managers in driving adoption. When managers actively modelled AI use, employees reported a 17-point lift in AI value. When managers created psychological safety around experimentation, that jumped to 20-points. A good reminder that it’s not just about individual training.

The workforce impact continues to play out in different ways. Some tech leaders are using AI to be almost omnipresent: Mark Zuckerberg is reportedly building a digital avatar of himself for employees to access. This article looks at the downstream effects when a manager seems to trust AI more than their team – a new blind spot for many leaders.

The workforce itself is shifting too. Employers can be skeptical of how reliant AI-native new hires are, but those who help an organization figure out practical AI use can be really valuable. I think about this a lot: if you’re a young person trying to break into a company, being able to explain and navigate AI within teams in a smart, clear, and inclusive way will make you super-valuable to an employer.

And what will the office even sound like as more of us use voice-to-text? Alone in a closed office it works great. But what happens when everyone stops typing and starts talking? If you’re keen to trial voice-to-text, I recommend giving Wispr Flow a try.

Cool Beans

• Break Mode: I know it’s a bit of agency award-bait, but I love this concept from Ogilvy: a special edition KitKat packaging that puts your phone into a smartphone jail so you can truly have a break.

• Spotify at 20: The app turned 20 and dropped a recap of your full listening history, including your very first stream (I will go to my grave before I disclose mine). It’s also rolling out “confirmed real artist“ tags to fight AI slop, including ‘podslop’ (39% of podcasts from the past nine days are likely AI-generated).

• Flying Drink Tray: This new concept imagines ‘what if your drink could fly itself across the room to you?’ Or maybe fly itself to my sunny corner of a patio?

Digital Trends: 05.01.26

A lot of my time these days goes into helping teams upskill on AI: finding practical applications, exploring new ways to work. One thing that keeps coming up in these engagements is that while people know most of the AI terms, they have a hard time fitting them together into a mental model.

I recently walked a team through a slide to give them a shared starting point. I’m sharing it below in case you or your team are wrestling with the same thing.

Here is the slide to download. If you think your team could benefit from AI training, feel free to reach out (hello@kickframe.com) and I can share what Kickframe’s customized in-house training looks like.

AI & Critical Thinking

Another thing that comes up pretty much every time I run an AI training session: someone will sheepishly admit, “I feel like AI is making me dumber.” There’s usually a laugh, and a few nods.

There’s a growing body of research that backs this feeling. AI can lift task performance while quietly reducing the parts of work that make it engaging: ownership, meaning, the sense that the output is yours. The more people lean on AI for a task, the less critical thinking they tend to do, and confidence in the work can rise faster than the quality does. Some early neuroscience work even suggests reduced mental engagement when LLMs do the heavy lifting.

At the same time, most of us know what AI does well: synthesis, analysis, research, drafting, and more. So while the benefits are real, the conversation in the room turns to how we can use AI without offloading our thinking in ways that hurt our work, our teams, and our own engagement and capacity for messy cognitive work.

Here are a few practices I share in my training sessions. Some are grounded in this early research, and all are things I’m working on incorporating into how I work:

1. Start With Your Own Thinking First: Before opening a chat window, sketch your own view of the problem, hypothesis, or approach, even roughly. Studies on “decide first, then consult” patterns suggest this helps protect you from anchoring to whatever the AI says, and keeps ownership over the result.

2. Use AI To Challenge, Not To Answer: Instead of asking for output you’ll polish, try asking it to argue against your position, surface weak assumptions, or represent the perspective you’re missing. This is still critical thinking work, and often more of it than you’d do on your own.

3. Separate Speed Tasks From Thinking Tasks: Not every step of a project deserves the same cognitive investment. Being intentional up front about which parts you’ll move through quickly, and which parts you want to sit in the ambiguity of yourself, helps you avoid drifting into AI use across the whole project.

4. Recognize That Critical Thinking With AI Looks (And Feels) Different: A 2025 study of knowledge workers found critical thinking doesn’t disappear with AI use, it shifts: toward verifying claims, integrating output with your audience, and investing real effort in the prompt itself. Separate research found ownership of AI-assisted writing rose with prompt effort. The work has shifted shape, not disappeared.

5. Check In Honestly: Are these outputs actually strong, or do they just look strong? Could I explain this if someone challenged me? Is my independent critique getting weaker? It’s easy to drift into offloading more than you mean to, and over time that can quietly erode both the muscle of critical thinking and the enjoyment of doing it. A question worth asking yourself from time to time: what am I gaining from AI, and what might I be losing?

Fresh Research

• 2026 Global Digital Report (We Are Social): The mother of all digital media reports just published a mid-year edition. If you’re looking for a stat on digital media use, good chance it’s somewhere in these 605 slides.

• Gen Z AI Adoption (Gallup): New survey on shifting Gen Z sentiment toward AI. Adoption is flat but the mood is sliding: excitement is down 14 points to 22%, hopefulness down 9 points to 18%, and anger up 9 points to 31% over the past year.

• 2026 AI & Digital Trends (Adobe): A survey of both marketers and customers that highlights the gap between the two. For example, 49% of organizations believe customers will eventually want AI agents to be their primary way of interacting with brands, while only 19% of customers agree.

Cool Beans

• AI-Powered Devices: Samsung launched Project Luna, a smart speaker that swivels to face you when you talk. A new humanoid robot (not the Terminator 2 model) also broke a world record for sprinting, and an artist built robot dogs with the heads of Elon Musk and Mark Zuckerberg, because why not.

• NotebookLM Graphic Novels: I’m a regular NotebookLM user and love the Studio features, particularly Mind Map. Now creators are using the tool to generate graphic novels – helping writers and educators make materials more engaging.

• AI Jesus & BuddhaBot: For $1.99 a minute you can hop on a video call with an AI avatar of Jesus. Or try BuddhaBot, trained solely on early Buddhist scriptures. And of course, there’s a BuddhaBot Plus.

Digital Trends: 04.22.26

Hello, me again. Thanks to everyone who reached out about the last video. I’ll be sharing more short videos like it, each covering a practical way to use AI in marketing work.

My goal with these is to help the teams I train (and you, if you’re reading this) feel more curious and confident experimenting with AI. To go on the offensive with it, rather than feeling like it’s coming for your job. That defensive reflex makes sense, especially when AI touches work you’ve built your career around. But let’s flip it around. You’re the expert in your work, which makes you the right person to shape where AI shows up in it. These videos are intended to encourage you to experiment and find the places where AI can amplify what you already bring to your role and your career.

This week’s video is on customer personas, which is work I’ve done throughout my career and some of my favourite to do. Lately I’ve been experimenting with how AI can help me do it even better, and here’s some of what I’ve learned.

Download Customer Persona Prompt (.MD file)

AI & Advertising

ChatGPT has become a research companion for many consumers alongside traditional search, and ads on the platform are getting closer. OpenAI is projecting $100 billion in ad revenue and recently launched its ad manager. ChatGPT also announced a more integrated opportunity: a beta app with Starbucks that lets users get a drink recommendation from a prompt or photo, then finish checkout in the Starbucks app.

Amazon’s Rufus chatbot (its “virtual product expert”) is also now letting advertisers pay for sponsored product recommendations. That one feels natural for Amazon, we’re already used to sponsored results there. ChatGPT is the more interesting case, though I suspect free-tier users will adjust quickly, similar to how we got used to Google’s sponsored results. It may even nudge more people toward a paid, presumably ad-free tier (like Netflix). I don’t think the consumer backlash will be as bad as some are predicting.

Fresh AI Research

Where Enterprises are Actually Adopting AI (a16z): AI is delivering the most value in work that’s text-based, repetitive, verifiable, and lightly regulated. That’s why coding, support, and search dominate enterprise use cases today, with coding an order of magnitude bigger than anything else.

Global AI Study (PWC): 75% of AI’s economic gains are being captured by just 20% of companies, and the leaders are pulling ahead by using AI for growth, not just productivity. They’re twice as likely to redesign workflows around AI than to simply bolt tools onto existing ones.

Anthropic Economic Index (Anthropic): Experience with AI compounds. Users who have been on Claude for 6+ months have a 10% higher success rate in their conversations, evidence of “learning-by-doing” and a sign that AI fluency is a skill that builds with use.

Cool Beans

Cassette Futurism: An aesthetic built around the tactile, physical tech of the 80s. It’s tied to a trend called “friction-maxxing“ (so many maxxings these days, btw), which is catching on with young consumers, not just nostalgic old dudes like me. Related: the rise of cyberdecks, handmade computers assembled from mismatched parts.

Aadam Jacobs Collection: A Chicago music fan has recorded more than 10,000 concerts over the decades using a cassette recorder stuffed in his pocket, including early sets from Nirvana and R.E.M. He has posted all of them. If you’re looking to kill some productivity today, go browse and listen here.

Robots & Chores: The ultimate sci-fi promise everyone’s still chasing - a robot that does your chores. Companies are working on this, and like every other AI tool, it needs mountains of training data, so people are being paid to record themselves doing laundry and dishes so the robots can learn. This frightening humanoid is apparently shipping soon, straight into my nightmares. I’ll take this robot dog that does chores instead, thanks.

Digital Trends: 014.15.26

Hi all, just a quick note about something new I’m trying out here in the newsletter. If you’ve been following along, most of my focus has been on how marketers can use AI to help their work and their careers. My goal has always been to share things I find useful, so I hope you do too.

With that in mind, I’m going to start sharing more practical, hands-on examples of AI in action for everyday marketing tasks. Things I’m learning about, trying, or seeing with my clients and in my training work with teams. I’m going to try these as videos. And as you will soon see, I have the on-camera charisma of a newsletter writer. But, I’ll keep them short. Down the road, I’d love to feature some of you and your tips. This first one focuses on the basics: online research.

Download Research Prompt Builder (.MD file)

AI Adoption & Leadership Gap

The latest AI research confirms a familiar pattern: broad adoption, limited impact. A study of Canadian marketers found 81% are using AI, but only 22% use it extensively and just 21% say it meaningfully affects their day-to-day work. A new Microsoft study shows that AI adopters report saving 40 to 60 minutes a day, yet 40% also received “workslop” in the past month (AI-generated content that looks great, but isn’t accurate or useful).

The research also points to a gap between leadership intentions and on-the-ground reality when it comes to training and support. Role-specific AI training is rare, and structured change management support is largely absent. The numbers illustrate this disconnect clearly: 88% of executives say their employees have adequate AI tools, yet only 21% of workers agree. In the past 30 days, 54% of workers bypassed their company’s AI tools entirely and completed the work manually (some “quietly rebelling”). And when executives were asked to identify the top skills needed for AI success, only 6% named change leadership. Yikes.

The companies achieving better results approach AI adoption through this change management lens. Wharton’s AWARE framework is a useful starting point for leaders thinking about what their teams actually need: Acknowledge the psychological impact on your team, Watch for unhealthy coping behaviours, Align support systems, Redesign roles for human-AI complementarity, and Empower staff through transparency and participation.

Fresh Research

2026 Digital Trends (Deloitte): Deloitte’s annual survey on digital media consumption is back, with a useful data point for media planners: social drives discovery, but conversion happens elsewhere. Important reminder for teams measuring attribution.

2026 AI Index Report (Stanford): Annual AI landscape report. Notable (and distressing) employment finding: entry-level jobs in AI-exposed fields like software development and customer support are declining, while mid-career and senior roles are holding steady or increasing.

Cool Beans

AI-Free Logo: Like “Canadian-Made” labels at the supermarket, companies are racing to create a definitive certification and logo for AI-free media. The “organic” label for digital media.

Spotify Prompted Playlists: Spotify launched prompt-based playlist creation and is now publishing its own prompts to try. Favourite so far: “My Unheard Saved Tracks,” which surfaces Liked Songs you have only played once (AKA songs I accidentally clicked ‘like’ on).

Binge Movie Tracking App: New Letterboxd competitor Binge integrates with Apple devices to warn you when a jump scare is coming. Clearly inspired by the Peebreak app I designed last week.

Digital Trends: 04.01.26

Hi all,

I hope you are well. Wait, do I? Is the actual meaning of this opening email line “Do not write back and give the other person a bulletin on your health”? The Economist has a painfully funny guide to email opening lines, all of which I am guilty of using. But seriously, I hope you are well.

Disclosing AI Use

“Did you use AI for this?” It’s such a loaded question, but in 2026 it really shouldn’t be. Most of us recognize the value of AI, but we tend to downplay how much we use it in our day-to-day work (unless we’re bragging about it on LinkedIn). As a consultant and corporate trainer, I use AI regularly, and I’ve been making an effort to be more upfront about it with my clients, even when they don’t ask (and most don’t). Why? I want to show them how I’m using it to benefit our project. I want them to have a clear answer ready if their boss ever asks. And I want to demonstrate that I’m aware of the risks and actively managing them. And as someone who trains marketing teams on AI, I want to lead by example when it comes to transparency.

So, I’ve started including an AI use disclosure section in my statements of work. It’s a simple 1-pager tailored to the type of work Kickframe provides, but the core topics (i.e., disclosure, data protection, accuracy, and tools) can be adapted for most industries.

If you’re interested, download a copy here and make it your own.

AI & Marketing

Speaking of AI use and disclosure, brands like Le Creuset and Aerie are committing to not using AI in their advertising. This ‘made-by-humans’ stance is receiving positive reactions on social. I’m curious how long this positioning lasts for marketers, since 70% of consumers can’t tell if advertising is AI-generated. It may be more a signal to the industry than to consumers.

The feelings around this make sense. Anthropic recently published a report that ranked market research analysts and marketing specialists 5th out of 800 occupations most exposed to AI displacement (Anthropic also just published a guide to use Claude to create brand assets). Mark Ritson shared this thoughts on this in a recent piece, arguing that much of what marketers do overlaps with what AI is already good at. His advice for marketers is spot on: invest in training to learn marketing fundamentals and build fluency with AI tools so you can direct them, not be replaced by them.

Fresh Research

• Effects of Relying on AI at Work: A new study finds that passively copying AI output undermines your self-efficacy, ownership, and sense of meaning at work. But drafting your own work first and then using AI to refine it preserves your connection to it.

• Navigating the Jagged Technological Frontier: (Ethan Mollick): A new paper explores the useful concept of viewing AI as a “jagged frontier,” showing that knowledge workers perform better when they use AI for parts of a workflow it handles well (within the frontier), but can perform worse when they apply it to tasks outside that frontier.

• What 81,00 People Want from AI (Anthropic): Nuanced findings from virtual interviews with Claude users, highlighting key points of tension with AI (Learning vs. Cognitive Atrophy, Emotional Support vs. Emotional Dependence, Economic Empowerment vs. Economic Displacement).

• The Top 100 Gen AI Consumer Apps (Andreesen Horowitz): 6th edition of this report, shows the growth of agents and creative tools beyond image generation. Plus, a useful directory of the top 100 apps to try out.

Cool Beans

• The Guinndex: An AI engineer created an AI agent that called every pub in Ireland (over 6,000) to track the cost of a Guinness. Who want to join me for a €5.52 pint at The Squealing Pig?

• Restart Your Life: The ultimate ‘Choose Your Own Adventure’ Book - change a few variables about yourself and see how differently your life might turn out with this AI-powered simulation. Yikes.

• Stitch: A new service from Google that uses AI to help you “vibe design” high-fidelity UIs for digital products. Unlike tools like Replit that focus on coding a working product, you can use natural language to create UI designs and design systems. Here’s the design for a new app I created after watching the looong (but excellent) Project Hail Mary this weekend:

Digital Trends: 03.15.26

Thanks to those who joined the AI + Strategic Planning for Marketers workshop last week. It was great to hear how people are incorporating AI into their work - particularly the upstream, thinky stuff. Research shows that most marketers are using AI for content creation and analytics - not for ideation or briefing. And for those who are using AI for upstream work, it is mostly as a Google replacement.

One way to find new opportunities is to break down larger areas of work into individual tasks, then look at how each task can be supported by AI. And if it can, the more interesting question becomes: how do we reorganize the work to get to better results? As we discussed during the session, AI adoption is more of a change management challenge than a technical one.

Something I’ve found useful for levelling up AI in planning work is meta-prompting, essentially using prompts to create better prompts. Rather than typing “research this” or “summarize that,” I’m trying to be more intentional about the instructions I give AI to get stronger, more structured outputs. I’ve created a couple of meta-prompts to help. Download the markdown files and give them a try:

• Research Prompt Builder: Helps sharpen research focus and define clearer questions before diving in. Use this before conducting secondary research.

• Summary Prompt Builder: Helps summarize findings into more useful formats and flag what may have been missed or underweighted. Use this when synthesizing findings from different sources.

If you’re interested in attending the next event, just reach out (hello@kickframe.com) and I’ll add you to the invite list.

AI & Commerce

New research confirms what many of us are likely experiencing - consumers are increasingly using AI to research purchase decisions. The challenge for marketers is that 93% of those AI search sessions end without a click through to a brand website. This zero-click trend is increasing as Google AI Overviews now appear in 25% of searches, up from 57% in Q4 2025. This is driving more brands to invest in Answer Engine Optimization (AEO), focusing on being present in sources AI models frequently cite (YouTube, Reddit) and creating content that gets referenced most (guides and product comparisons.) Klaviyo published an interesting playbook for marketers that maps out four personas, each defined by how much they trust AI and how often they use it.

There does appear to be a ceiling, though. Consumers currently use AI primarily upstream in their shopping journey, for research and comparisons. Purchase and post-purchase, not so much. This may explain why OpenAI is pulling back on efforts to allow customers to make purchases directly inside ChatGPT. It feels a lot like Meta’s 15-year-plus attempt to bring commerce into Facebook and Instagram. Unless OpenAI becomes more of an OS like Apple, I can’t see in-chat transactions gaining traction for the same reasons. Don’t ditch that brand website yet, folks.

AI & Work

A couple of new AI-related terms came across my feed this week, both work-related.

The first is “The Fuckening.” It refers to the prediction that AI will lead to massive job loss among knowledge workers. It feels relevant given the recent layoffs at Block, which cut 4,000 workers and saw its stock price increase. The fear is that others will follow suit, even if not warranted (“AI-Washing” – another term). A KPMG survey of CEOs tells a different story: 55% expect to increase hiring this year as a result of AI, and only 9% intend to reduce their workforce. Strange fucken times.

The other term is “Brain Fry,” which refers to mental fatigue from excessive use or oversight of AI tools beyond one’s cognitive capacity. Now this one I relate to. Research shows that people found their overall productivity at work increased when using up to using 3 tools, after which it started to dip. Many described a feeling of “fog” from juggling different tools. Interestingly, this condition cited most in marketing roles, the number one job function experiencing “Brain Fry”.

Cool Beans

• Google Maps: Very cool AI enhancements are coming to Google Maps powered by Gemini, including Ask Maps. Users can ask very specific questions like “is there a public tennis court with lights on that I can play at tonight?” Immersive driving also looks very cool.

• The Human Flatus Atlas: “A first-of-its-kind nationwide study using Smart Underwear technology to finally quantify the dynamic range of intestinal gas production and explore what these patterns reveal about gut health and the microbiome”. In other words, a new device to measure how often people fart.

• WalkmanLand: Careful with this one if you are Gen X, you will go down a rabbit hole. It’s a catalogue archiving Walkmans, including my precious WM-AF54 Sports model.

Digital Trends: 03.01.26

From Templates to Prompts

Speaking of practical uses, I wanted to share a recent experiment. A few years ago, I put together The Kickframe Toolbox, a collection of marketing planning templates with guidance on choosing and using them. It’s still live, and you can download everything in editable formats.

I was wondering if these frameworks could also work as prompts. A prompt could walk you through the same steps as a template, asking questions, clarifying your thinking, and producing a completed draft. I built one and it worked pretty well. Then I took it further and created a meta-prompt (a prompt that generates other prompts) and applied it across a handful of other frameworks.

What impressed me here was that I could use Claude Code to automate the whole process. I gave it the meta-prompt with instructions, along with the Toolbox frameworks, and it produced a full set of prompt files. From there I had Claude Code build a simple web page with all of the prompts accessible. The whole thing took a few hours, not counting the automation, which ran on its own.

Don’t go firing your strategic planners! These prompts are pretty clunky, and there’s no substitute for strong, clear thinking. But it did make me think that tools like these could be helpful for capturing and organizing early thoughts into a first draft.

The AI Adoption Gap

A recent study by Section uncovered a major challenge in organizational AI adoption: executives tend to think their AI rollouts are going well, but employees do not. Most workers currently use AI for only basic tasks, if they use it at all.

This disconnect shows up clearly in marketing teams, where 89% of marketers feel pressure from leadership to adopt AI, yet 37% say they lack a clear AI strategy to follow. Meanwhile, agencies are cutting staff partly due to expected AI efficiencies, and companies like Accenture are tying promotions to regular AI use. Leaders need to get real about AI planning, change management, and team training.

AI + Marketing Reports

A bunch of new reports have come out on AI in marketing. Here are links to a few, along with what I found to be the most interesting takeaway from each.

• State of Marketing 2026 (Hubspot): Nearly half of marketers (49%) agree that web traffic from search has decreased because of AI answers. But 58% note that AI referral traffic has much higher intent than traditional search.

• Market Research Trends 2026 (Rival): Only 27% of research professionals are excited about the use of AI to create synthetic respondents.

• Generative AI & The Marketer (Typeform): 50% of marketers say they’ve published AI-generated work without disclosing and would do so again.

• State of Marketing (Salesforce): Marketer’s top priority: implementing or operationalizing AI. Marketer’s top challenge: implementing or operationalizing AI.

Cool Beans

• LoveFrom,: Jony Ive’s design firm is reportedly working on a smart speaker with OpenAI and recently designed the interior of a Ferrari (no CD player FYI).

• D’oh FM: Thousands of songs on peer-to-peer network Soulseek have had their vocals stripped out and replaced by Homer Simpson.

• Eternal Playlist Urn: Speaking of music, if you were hoping to buy an urn for a loved one that holds their ashes and plays their favourite tunes, sorry, they’re sold out.

Digital Trends: 02.15.26

Two years ago, I came across research on how people were actually using AI at work. One finding stuck with me: the people getting the most value from AI pause at the start of each task and ask, “How could AI help here?” I’ve been trying to build that habit into my own strategic planning work, and I’ve learned a few practical tips. I’m also curious what others other learning.

So, I’m hosting a new 1-hour virtual meet-up: AI + Strategic Planning for Marketers on March 10th. I’ll share a few use cases, lessons, and prompts - and leave some time for others to share what’s working for them.

If you’d like to join, sign up here. It’s free, and even better if you come with a tip to share.

AI + Work

AI taking our jobs is a popular narrative, but is it true? I’m sure that a site like RentAHuman.ai – where people can sell their labour to AI agents – reinforces this belief. But the data is messier. A new study shows that in fields where there is higher AI exposure, like financial services and software, headcount is actually increasing as are wages. Perhaps some of these companies seeing the value from AI and are looking at new hires as amplifiers?

And how are people feeling about AI use? Again, it’s messy. A new report suggests that AI doesn’t reduce work, “it intensifies it”. AI-empowered employees are moving faster, covering a wider range of tasks, and extending work into more hours of the day. Another study describes a “belief anxiety” paradox: people can see AI’s business value in work while still feeling insecure about what it means for their own role. Is AI really working for employees if it makes them feel less in control of their own jobs?

AI + Search

Another popular topic, at least with marketers, is how AI is impacting the customer journey. Airbnb made headlines last week by saying that traffic from AI chatbots converts better than Google. So as more people are using AI chatbots for research, marketers are scrambling to product AI-optimized content and investing in services to track their visibility in AI results.

However, SparkToro released an interesting study showing that brand and product recommendations from AI chatbots are highly inconsistent. When asking for recommendations, it reports there is less than a 1 in 100 chance of getting the same list twice in ChatGPT or Google AI, and roughly 1 in 1,000 odds of getting the same list in the same order.

Useful Stuff

• How to Write a Coaching/Learning Prompt (Seth Godin): Helpful framework, with examples, for prompting an AI chatbot to act like a thoughtful coach and help you learn and work through important life decisions.

• Guide Building Brands (Something Different): Synthesizes research on how brands and businesses grow. Useful reference and a guide for exploring the underlying evidence in more depth.

• AI Taxonomy (Narain Jashanmal): AI means different things to different people, so someone put together a helpful guide to help you talk about AI subjects more specifically and clearly.

Fresh Research

• State of AI (Deloitte): A new report on AI adoption reinforces that scaling AI is mainly a change management challenge, with 84% of companies saying they have not redesigned jobs or workflows around AI capabilities.

• AI Predictions (Advertising Week): Quick round-up of how AI is showing up for marketers, and how it’s affecting both creative and media. Notable point on AI reshaping the client agency relationship – aligns with how agency Monks is moving from billable hours to a subscription model (I’m old enough to remember when they were called ‘retainers’).

• B2B CX in an AI World (Adobe): A good read for B2B marketers. It highlights a key challenge with using GenAI for content creation: you can produce assets faster, with a 22% drop in cost per asset, but oversight costs for quality checks have risen by 40%.

Cool Beans

• 2X2 Gallery (Alex Morris): The only thing I love more than a Venn Diagram is a good, old-fashioned 2X2. Here’s a bunch of them.

• Posts from the Dead: In what feels like a ghost-movie plot, Meta has a patent for training an AI model on a deceased user’s post, keeping post-mortem accounts active by uploading new content in their voice after they die.

• Xikipedia: Instead of doomscrolling videos, why not try scrolling a feed of posts from Wikipedia tailored to your interests.

• Vertical Pizza Box: I’m 100% sure that the people in this reaction video work for the agency that pitched this marketing stunt idea, but who cares.

Digital Trends: 02.01.26

Thanks to everyone who joined our AI + Marketing Show & Tell live session. We had a bunch of folks show up and share practical examples of how they are using AI in their own roles, workflows, and teams. Ideas ranged from turning Google Notebook into a behavioural scientist, to building personas for sales prospects, to using AI to help navigate internal politics. I learned a lot.

During the session, I also shared a few observations from my experience training and working with marketing teams on AI. Some tips I’ve found helpful for breaking down barriers, so people can start adopting AI more intentionally and with greater success:

I’ll be hosting a few more of these training and sharing sessions over the coming months, so keep an eye on the newsletter or reach out and I’ll make sure you’re included.

Smarter Personal AI Adoption

During the AI + Marketing Share & Tell, the people that seemed to be getting the most value from AI often did a few things consistently. They personify it so it has a clear role in the work (my skeptical assistant, my editor, my researcher). They also build small prompting habits that improve outputs (e.g., “before you start, ask me three questions that will help you complete this.”). Here are a few other tips from that came across my feeds this week:

Kamil Blanc: Shares a “Human API” concept. Use a reusable block of context about you, your role, your audience, and your preferences so the chatbot has better direction for most professional requests.

Jack Clark: Using agents to “multiply yourself.” He shares examples of multi-agent workflows that can scan papers and summarize with minimal supervision, like a set of autonomous colleagues.

Ethan Mollick: Be intentional about what you delegate to AI. Before you hand something off, do a quick trade-off check. How long would it take you to do it yourself? How long will it take AI plus your time to guide it, review it, and fix it?

AI Reshaping Advertising

Over the next year, it’ll be interesting to watch how AI reshapes paid media. Shoppers are already using AI chatbots alongside traditional search, and brands are starting to think about GEO alongside SEO for organic visibility. The open question is what “paid” becomes inside these AI experiences.

BCG frames the landscape in three buckets: Search embedded AI, Assistant native AI, and Retail and commerce AI. We’re also getting more hints about how ads could work in ChatGPT. The pitch is that ads won’t influence organic answers, but organic answers may influence which ads are eligible. That’s pretty fuzzy, and it risks blurring the line between an “answer” and an “ad,” which Seth Godin flags as a serious trust problem.

On the creative side, the Super Bowl will be a useful test. Some brands are openly sharing how they’re using AI in production. Others are emphasizing that their ads are “human-made” by showing the behind the scenes process. For now, that’s likely a hedge against data showing consumers (and creative professionals) often dislike creative that feels obviously AI generated. My bet is this “AI shaming” phase won’t last long, and budgets will move quickly once these AI media platforms scale. But I’m skeptical we’ll see meaningful commerce happen directly inside AI chatbots anytime soon (despite OpenAI relationship with Shopify) assistants anytime soon as ads, answers, and inventory start to blend.

Fresh Research & Reports

• Journalism, Media & Technology Trends (Reuters): Publishers are leaning into video and original reporting as social referrals keep dropping: down 43% from Facebook and 46% from X over three years. More decline is expected as AI chatbots take over discovery. Google AI Overviews show up at the top of about 10% of US searches.

• AI & CEO Leadership (BCG): CEOs fall into Followers, Pragmatists, and Trailblazers. Trailblazers are the most AI-forward, with most spending 8+ hours a week building AI expertise, and they’re more confident and excited than peers.

• State of AI in the Enterprise (Deloitte): Many companies are stuck in the “proof of concept trap,” prioritizing safe pilots over scaling. A key issue is change management: 84% haven’t redesigned jobs around AI capabilities.

• The State of AI in Marketing 2026 (Jasper): The biggest blocker to scaling AI in marketing is legal, compliance, and brand review. 27% cite legal/compliance as the top reason they’re not scaling AI, over 3x higher than 2025. What’s the point of producing more content quicker if approvals can’t keep up?

Cool Beans

• Apple AI Pin? Rumour has it that Apple is working on an AI pin with dual cameras, microphones, and a speaker. OpenAI is also rumoured to be launching AI-powered earbuds later this year.

• Weird Tech Patents: Love this index of images pulled from real tech patents. Looks like someone beat me to launching my Inflatable Dog Immobilizer App idea.

• Just Scream: Speaking of being late to the party, this site looks like it is from 2021: a place where people upload audio of themselves screaming. You can browse and listen to 27,000 plus entries, with categories ranging from Hope to Circle of Life.

BTW, it’s always nice when someone likes or subscribe to my newsletter. I just received this notification – you are in good company.

Digital Trends: 01.18.26

AI Advertising

AI is changing how people research and discover products. New research shows that 41% of consumers use AI assistants to research products, 33% to look for reviews, and 31% to search for deals.

Until now, the playbook for marketers has been focused on organic visibility - make sure your content is easy for chatbots to cite, and build for AI powered searches that are more open-ended and task-based than traditional web search. That’s starting to shift, as platforms are rolling out paid media inside these AI-powered experiences.

Walmart is already baking ads into its shopping agent, letting advertisers pay to have products recommended by their bot. Amazon is testing sponsored prompts that appear within relevant searches, nudging shoppers toward a brand or deeper brand information. Google is introducing offers in AI Mode, like exclusive discounts, and a Business Agent that lets shoppers chat with a retailer directly from search results. And OpenAI is the one everyone is watching: it is expected to introduce advertising too, likely as sponsored placements in a sidebar - which feels very Google-like.

I’m sure brands will want in. The bigger question is how it will be received by consumers. I don’t expect much backlash for Google or Amazon – but ChatGPT? If ads appear for paid users, I’m very skeptical.

Fresh Research & Ideas

The AI Gap Widens (IAB): The study shows advertisers are far more positive about AI-generated ads than the younger consumers who see them. How long until AI feels normal enough that people stop trying to spot it (or shame marketers for using it)?

Winning Consumer Attention (McKinsey): Great insight here for media planners: it’s not just about how much time people are spending with media, but the quality of attention. Research shows that high-focus, high-intent experiences like live sports and concerts drive more value than other media.

Copilot Usage Report (Microsoft): Most interesting finding for me was how much mobile and desktop use varies: desktop is more work related, while mobile is used for advice and support - especially (and consistently) around health topics.

Use AI to Ask Better Questions (Neil Perkin): Some smart tips for using AI as a thought partner to reframe problems. For example, asking AI chat how an expert from a completely different field might tackle a problem from your domain.

Speaking about prompts, one tool that I’ve been monkeying around with to improve my more comprehensive prompts is Open AI Platform. I can start with a basic prompt and have it rewritten and optimized (payment required). Worth a try if only to understand how to better structure your prompts.

Cool Beans

ChatHub: Ever wondered how different chatbots respond to the same prompt? Choose four, run the same prompt, and compare their responses side by side in a single browser window.

FitDrop: Super fun interactive site made by Iain Tait where you can explore fashion from 1980 to 2025. All images are created by Nano Banana. Turns out I’ve progressed very little beyond 1992.

CreepyLink: A URL shortener that makes your links look as suspicious as possible. Click on this link, if you dare…https://verify.ic6do.com/Af1Iro_urgent_security_alert.php

AI Baby Panda Robot: Yes, you read that right. Read more about this aberration and other bizarre tech products from this year’s CES.

Digital Trends: 01.08.26

Happy 2026! I hope you had a fantastic break and that your year is off to a great start.

This year, I’ll be focusing even more on the practical application of AI in marketing—both in my work with teams, and in what I share through this newsletter. In my training sessions, I’ve found that people are tired of the AI hype and are much more interested in the tangible ways AI can help in their day-to-day work. Some of the best moments in training sessions come when people share their own discoveries—simple hacks, prompts, or clever ways they’ve made AI part of their workflows.

To build on that, I’m hosting an AI + Marketing Show & Tell on January 22 at 12:00pm EST. It’ll be part training session, part roundtable. I’ll share a few lessons from the past year, and if enough people join and volunteer, we’ll do a quick round of sharing practical AI uses—big or small—that make marketing work even 1% easier or more enjoyable.

If you’re interested in joining, sign up here and I’ll send you the details.

AI Use in Marketing

Research on marketers’ use of AI continues to show consistent findings: everyone recognizes its importance, but the majority remain in a quasi-experimentation phase. More recent research reveals some useful nuance around adoption patterns and tips for success. Key trends and lessons emerging about how marketing departments are using AGI include:

• AI is considered less likely to disrupt marketing workflows that require human judgment (briefing and ideation) compared with workflows that are more production or automation focused (personalization and adaptation).

• 86% of CMOs believe that creative agencies are not yet using AI at scale, and 60% of those CMOs believe agencies need to provide staff with AI training and upskilling.

• CMOs reporting more positive AI impact tend to create 9 - 12 month roadmaps that address tools, governance, talent, measurement, and training. Among these CMOs, 75% are investing in GenAI upskilling across all levels.

• Senior marketing and CX executives see the biggest areas of AI impact over the past year as increased productivity and greater content and idea output. Additionally, 47% report revenue growth as a result of marketing more effectively.

• Marketing teams underestimate the time and costs associated with incorporating AI into their work. While developing assets more quickly is a benefit, that does nothing for the time required for reviewing assets and approvals from clients: “The real cost isn’t generating assets, it’s generating your assets…a single prompt can give you 200 like, pretty good options. But someone has to sift through and judge and refine. That decision work used to be invisible; now it is the job.”

• Beyond using AI for efficiency in producing assets, marketers and creative agencies are also applying generative AI to develop creative concepts that would otherwise be too costly to produce at an acceptable standard—for example, Jeep’s recent campaign featuring AI-generated wild animals speaking in the ad.

• Looking at the role AI plays in the customer journey, surprisingly (to me), younger consumers are fairly positive (48%) toward agentic AI—specifically, a brand using a virtual shopping assistant that browses sales and adds items to their cart based on styles and past purchases.

• Shopping-related GenAI use grew by 35% between February 2025 and November 2025. It is used for a wide range of purchases, but activity focuses on higher-consideration decisions, including travel planning and detailed technical comparisons such as laptops.

Fresh Research & Decks

• AI X Commerce in 2025 (Juozas Kaziukėnas): A super-useful and up-to-date primer on the impact of AI on commerce. Great perspective on how the customer journey and retail media is changing.

• Digital Twins as Funhouse Mirrors: An academic study finds that much vaunted AI-generated digital twins used for research are not reliable substitutes for real human responses. Edward Cotton shares a useful marketer’s perspective on LinkedIn, with a lively debate in the comments (many coming from companies selling AI-generated digital twins).
  Teens, Social Media, and AI Chatbots in 2025 (Pew): Nearly two-thirds of U.S. teens use AI chatbots like ChatGPT, with about one-third using them daily. About one in five teens say they are online “almost constantly.” 3 of those teens live in my house.

• Year in Search 2025 (Google Search): Always a fun time capsule of the top searches by country. In Canada, where the Blue Jays had an amazing World Series run (I still don’t want to talk about Game 7), trending searches included: What time is the Jays game today? How many innings in baseball? And (a question asked repeatedly in my house): Why do baseball players spit?

Cool Beans

• Promptist: If you’re looking to level-up your prompting, this tool is worth trying. It shows how a rough prompt can be expanded and improved with more detail and structure. It can also give you ideas for breaking tasks into more focused, smaller prompts.

• Lego Smart Bricks: Lego announced new tech-enabled bricks that create sounds, lights, and other effects, blending digital and physical play. Some play experts are freaking out.

• AI Desktop Companion: Interested in having a holographic AI companion in a jar that chats with you all day, every day? Reserve yours here.

Digital Trends: 12.15.25

One of the last things on my to-do-list before signing off for a rum and eggnog is to press send on this newsletter. As my festive gift to you, I’ve sifted through the mountain of trend decks that have flooded my inbox and feeds over the past few weeks to bring you my annual 12 Trend Decks of Christmas.

This marks the third edition of this holiday gift. In past years, Santa made an appearance reading my newsletter.

In 2023 using DALL-E:

In 2024 using Sora:

And this year, using Veo-3 / Google - a quick reminder of how fast GenAI is evolving.

Thank you to everyone who has read, shared, or reached out this year. I truly appreciate your support and wish you a wonderful holiday.

Now, onto the decks…

1. Let Them Eat Lore (OK COOL):

A creative, fun report that goes deep on trends impacting social media and Internet culture. Lots of current examples and tips for brands. Great for marketers and creators looking to increase reach and engagement in social media and community spaces. Highlight: The growing influence of comments in social media – “the culture is in the comments, and the hot take is currency.”

2. 1,000 Tiny Pieces (Hopeful Monsters):

Explores how culture has fragmented through changes in our media ecosystem, and how brands must rethink how to engage through participation in fandoms and distributing new types of content. Great for marketers and media planners rethinking how to be more culturally relevant in their categories. Highlight: Brands must earn permission to be present within micro-communities (bottom-right).

3. 2026 Global Consumer Predictions (Mintel):

Explores three global consumer trends shaping marketing today: resistance to algorithmic influence, a redefinition of youth, and a retreat into self-contained personal bubbles. Great input for big picture brand planning, with lots of nuggets from across the globe. Highlight: 74% of Canadian consumers agree that deepfake AI videos and pictures make it hard to tell what is real.

4. Trending 2026 (Foresight Factory):

Explores trends revolving around the concept of Cognitive Crossroads – how consumers are navigating the tension between what it means to be human and the growing use of technology. Great for those interested in exploring the impact of bigger picture societal trends and consumer behaviour. Highlight: Most people (US / GB) agree that our use of AI will have a future intellectual cost.

5. 2026 Trend Report (Trendhunter):

Explores emerging trends across consumer categories, spotlighting AI’s growing impact and showcasing standout products, services, and campaigns. Great for sparking ideas or fueling an innovation-focused brainstorm. Highlight: Too many to pick just one - skim through and you’ll leave with a new start-up idea.

6. Connecting the Dots (GWI):

Explores 5 trends that will impact marketers in 2026 based on GWI research spanning AI, Gen Alpha, and the World Cup. Great for marketers scanning for signals for their 2026 plans and want to avoid blind spots. Highlight: Social media isn’t really social anymore…

7. Generative Realities (Dentsu):

Explores 5 trends that marketers and agencies can consider to inform creative work for 2026, focusing on connections between culture, technology, and vibes. Great for marketers and creative teams looking for some fresh consumer and cultural insights. Highlight: ‘Analog Futures’ – younger generations embracing more simplistic (and hedonistic) activities and times as a resistance to algorithmic sameness.

8. CX Trends Report (Acxiom):

A survey that explores the impact of AI in the lives of consumers, and the implications to designing modern, effective customer experiences. Great for marketing and UX leaders in high-touch industries like banking, healthcare, telecom, and travel. Highlight: People are far more open to AI offering proactive support or alerting them to a potential security issue, than to the technology making payments on their behalf or acting as a personal assistant in all areas of their life.

9. 2026 Tech Trends (SURF):

Explores 10 emerging digital technology trends and their potential impact, risks, and value for organizations. Very detailed, data-backed material. Great for leaders figuring out digital pilots or digital roadmap investment decisions. Highlight: The report uses The Value Compass to consider how digital transformation initiatives relate to public values.

10. 2026 Digital Advertising Trends (Smartly):

Explores digital advertising trends based on a survey of marketers who are actively planning and managing campaigns. Great for digital marketers and media teams to take stock of what their peers are thinking and doing heading into 2026. Highlight: About half of marketers are using AI for visual asset generation for digital advertising campaigns, with adoption growing.

11. 2026 Marketing Trends (Meltwater):

Explores 15 marketing and communication trends including the rise of AI Search Optimization and LLM reputation management. Great for marketers and agencies considering what adjustments to make from their 2025 media plans. Highlight: To optimize for AI Search, marketers should publish authoritative content, human-attributed explainers, FAQs, and a brand source-of-truth hub with consistent facts easy for LLMs to ingest.

12. 2026 Trend Report (Pinterest):

Outlines 21 trends based on Pinterest behaviour across categories like food and drink, fashion, beauty, and interior design. Fun to see how this behaviour is synthesized into broader themes. Great for marketers and content creators considering new ways to be on trend. Highlight: Pen pals are back!

Bonus: I fed all of the decks into Google NotebookLM and created an Infographic that synthesizes them. Filing this under “kind of cool, kind of useless” - for now.

Digital Trends: 12.01.25

Last night I spent an hour on ChatGPT figuring how to upgrade the Wi-Fi in my house. I started with a vague idea of my options and ended up buying five products to install. The experience differed from a traditional online search because I could:

• Access general guidance and answers framed around the problem I was trying to solve, with technical details dumbed down (a few levels) so I could understand them.

• Review detailed comparison of products across brands and retailers, identified and scored based on my specific needs.

• Confirm my product choices sourced from reviews, and the compatibility of the products based on product manuals.

It was clunky in spots. I had to remind ChatGPT of context to evaluate options based on my current setup. When it came to the final steps of purchasing, some of the retailer links were broken or out of stock.

But overall, the experience felt informative, personalized and - with the evergreen caveat that AI hallucinates – pretty trustworthy. I’ll report back on whether it works.

Regardless, shopping is changing with AI. But how?

The IAB released a great study on the role AI is playing in the shopping journey. Its findings generally align with my experience. AI is being used most effectively mid-funnel, where decision-making complexity is highest. However, for many, AI isn’t removing steps from the process—it’s adding them, as people validate AI-generated recommendations elsewhere.

McKinsey released a similar study, highlighting the different ways that customers use AI-powered search for different stages of the journey.

How can AI help complete this last step? ChatGPT recently introduced Shopping Research, a tool designed to help people find and compare products—presumably with ads coming soon. Further down the funnel, major platforms are rolling out agentic solutions that can complete purchases. Google, for example, has launched a service that can call stores or check out on retailer websites automatically when a price drops.

However, retailers are not pleased. Amazon has filed a lawsuit against Perplexity for using its AI agents to search products and complete purchases on its site. They’re concerned about losing control of the shopping interface, where much of their advertising revenue comes from. Bain has released a new report outlining the different paths retailers can take in response, including building their own AI agents.

AI & ADVERTISING

How is AI impacting search advertising? McKinsey estimates that 20-50% of customer traffic from traditional search is at risk of shifting to AI-driven search. That’s a wide range – c’mon, seriously, McKinsey - but the takeaway is clear: the shift is significant. Advertisers should focus on understanding where AI chatbots source their information to ensure strong representation in AI search results. Currently, only 16% of brands systematically track AI search performance. A recent SEMrush study found clear differences among platforms: ChatGPT most often cites Reddit and Wikipedia, while Google’s AI Mode favors Google-owned domains. The landscape is evolving quickly. Here’s a useful backgrounder from Ofcom on GenAI search, outlining the main types.

AI RESEARCH & REPORTS

• 2025 Edelman Trust Barometer: A useful snapshot of people’s current attitude toward AI. In general, trust is the biggest barrier to adoption (more than access, motivation, ability). At the workplace, enthusiasm for AI grows if workers receive training or feel sure that AI will be used for productivity, not job elimination.

• Parent & Teen AI Use (NORC): Survey indicates that unlike the early days of social media, AI adoption isn’t dramatically skewed toward younger generations. In fact, both groups use it in similar ways.

• Canadian Business & AI Use (KPMG): Survey of executives found that 93% of organizations are using AI in some way, up from 61% last year but only 2% are seeing positive ROI. Most are still in pilot phase.

• AI Eats The World (Benedict Evans): Always a must-read from Benedict Evans, which his bi-annual big picture tech perspective – this time placing AI in a historical context to try to understand what comes next.

• The Impact of Visual Generative AI on Advertising Effectiveness: If you’re looking for proof that humans create more effective advertising than GenAI, maybe give this one a pass.

COOL BEANS

• Corners of the Internet Database: Curated list of links to sites that are keeping the web weird. Like The Fish Doorbell - a livestream showing fish swimming through Utrecht, where viewers can watch a lock operator open a gate to let them pass.

• Consulting Slop: Provide a company name, business problem, and consultancy brand and have a presentation deck created for you instantly. I’ve seen worse.

Digital Trends: 11.15.25

How is AI impacting commerce? New studies show the impact of AI chatbots in driving motivated shoppers to retail websites, specifically:

• More traffic: 15% of total referral traffic for Walmart in September was from ChatGPT

• More engagement: GenAI traffic spends 32% more time on retailer websites than non-AI visitors

• More growth: >50% of consumers anticipate using AI assistants for shopping by the end of 2025

But why stop at driving traffic to retailers when you can have customers checkout on your own platform? OpenAI is following the playbook of Meta and others – allowing users to buy directly through ChatGPT while taking a cut from merchants and collecting valuable data. “Buy It in ChatGPT,” lets people check out instantly from merchants like Etsy and Spotify. Walmart’s also on board.

This raises some big questions. Will retailers that spent years and millions building their own online stores lose direct access with their customers and first-party data? And will they now need to rethink their setup to treat AI agents as their new “customers”? It’s easy to envision a sort-of ChatGPT.shop app or mode launching soon.

AI & ADVERTISING

So, what should advertisers do about it? Many of the same principles as traditional SEO still apply, but with a few wrinkles:

• Since most product research happens at the lower end of the funnel, ensure product information is detailed, accurate, and structured for AI retrieval in response to lower-funnel questions.

• Recognize that search engines still dominate online discovery time, and Google will soon default people into AI mode for more complex queries – including those that are shopping-related.

• Track your “share of model.” Some brands are well-known to people but under-represented in AI-generated answers, and vice-versa.

The more interesting question is how to use AI overall as a marketer: as a tool for efficiency or for growth. PwC argues for both - using cost savings to invest in effectiveness and upstream innovation. For example, Lavazza built AI-driven personas from 5,000 customer interviews, making insights more interactive and accessible for teams. Don’t limit your AI exploration to doing more of the same with less.

FREE TOOLS & RESOURCES FOR STRATEGISTS

A few smart, generous strategists have opened their Google Drives (and hearts!) and are sharing great resources to help fellow strategists:

• Creative Strategy Starters (Rat-thew Kilgour, not sure if that’s his real name but I love it): Great thought-starters for facilitating a creative brainstorm.

• The Strategist’s Playbook (Jasmine Bina and JL Rawlence): Collection of popular strategy frameworks put into a cultural context.

• Sweathead Strategy Resources (Mark Pollard): Mark is a prolific strategy writer and has opened up his archive – loads of templates, examples, and inspiration to explore.

And if you’re looking for more strategy boxes, circles, and arrows check out the KickframeToolbox.com with over 50 modern marketing frameworks, all free to download and edit.

FRESH AI RESEARCH

• The State of AI (McKinsey): Paints a picture of corporate AI as widespread, but not deep. The business units that report the greatest revenue gains are marketing and sales.

• 2025 AI Adoption Report (Wharton): The business tasks that have seen the highest jumps over the last year are Presentation and Report Creation and Idea Generation and Brainstorming.How People Around the World View AI (Pew): 45% of Canadians say they feel more concerned than excited about AI, while only 9% feel more excited than concerned — a level of concern that exceeds the global median.

• Digital 2026 Canada (We are Social): Great compilation of Canada-specific digital statistics, including ChatGPT jumping from the 12th to the 6th most visited website in Canada.

COOL BEANS

• Neo The Home Robot: A new AI-powered robot maid is now available for pre-order, shipping in 2026 for $20,000.

• Helix The Flying Car: A new flying car is now available is now available for pre-order, shipping in 2026 for $200,000.

Digital Trends: 10.15.25

Last week I spoke at CRM Edge, a live event bringing together marketers exploring AI. Speaking at conferences differs from designing and delivering corporate training because I don’t need to meet specific client learning objectives. Instead, I can just sort of riff along with PowerPoint accompaniment. This presentation focused on something I’ve been riffing a lot about lately - the parallels between how businesses are approaching AI today and how they approached the web (or “digital”) 25 years ago.

I shared a few lessons I’ve learned over my career that apply to AI today. I thought I’d share them here, too.

Lesson 1: Expertise over an Expert

Teams that adopted digital effectively had leaders who invested in learning about it and were genuinely interested. They didn’t just delegate to an expert. Bringing in an expert can help, but make sure that person is responsible for coordination and upskilling across departments. Think horizontally. Like the Internet, AI is a general-purpose technology. Build expertise across the organization and avoid thinking the AI box is checked just by setting up an AI lab or centre of excellence.

Lesson 2: Strategic Alignment over Add-Ons

The most effective digital strategies supported the business’s main goals. AI initiatives should be treated the same way - not as a separate track but as an enabler of what the business wants to achieve. If new customer acquisition is a key goal, focus AI there. Avoid vanity projects or flashy press releases. Progress may not look exciting. And if you’re an agency pitching, don’t tack on an AI idea at the end of your deck to show that you “get it.”

Lesson 3: Clear Framing & Guidelines

What do we mean when we talk about “digital”, or in this case “AI”? What does “good” or “more” look like? What exactly do we want teams to do or explore Marketing teams understandably feel FOMO about AI, but we need to be fair to team members and be clear about what AI adoption involves. Guidelines are important to ensure exploration balances potential benefits and risks. Remember that the goal isn’t AI adoption - it’s achieving better outcomes with AI.

Lesson 4: Capabilities over Technology

I’ve lost count of how many times I’ve heard the analogy of a martech tool as an expensive car sitting unused in the garage. That’s what happens when we focus on acquiring technology without the data, people, and processes needed to use it effectively. With AI, ensure teams understand its core capabilities so they can explore how it connects in relevant, additive ways to their work goals. Don’t look for opportunities only through the lens of a tech feature set.

Lesson 5: Augment & Automate

One thing we all experienced with the rise of digital was drowning in data. Want another word cloud? How about a dashboard that links to another dashboard? With AI, let’s focus on what actually helps us make better decisions. That means not just using ChatGPT like a search box but as a tool to help us think. Look at ways to automate research through agentic scans - sending updates in the frequency and format that are most useful to us.

Lesson 6: Ongoing AI Exploration

How do you finish a project when technology keeps changing and customer behavoiur keeps evolving? One lesson we learned from digital is that transformation is never complete. The term “transformation” was helpful to describe the effort required to invest in digital, but with AI we need to think in terms of continuous evolution - pilot, measure, scale. This mindset is even more important for AI, which is more accessible to teams and where capabilities are advancing faster.

It’s interesting to look back on these lessons, many of which seem obvious now. Having led digital strategy, managed digital research analysts, built digital transformation roadmaps (and yes, been a “digital expert” in a digital lab building digital ideas!) what’s happening with AI almost feels nostalgic. It reminds me of the early part of my career exploring the web, which I look back on fondly. I’m excited for this next wave of innovation and hopeful that we can benefit from some of these lessons learned.

Digital Trends: 10.01.25

It’s hard to believe that I’ve been writing this newsletter in some form for over 10 years. It’s been a helpful way for me to keep up with changes in digital marketing, stay connected to my network, and provide me with an outlet for thinking and writing. Over the last 2 years, my focus has shifted more and more toward AI, which has captured my curiosity like the early days of the web (and my career). So, I’m going to keep focusing on it. Which brings me back to this newsletter. I’ll be adding some very short videos that explore practical ways which people use AI in marketing and business. I’ll talk with practitioners and builders to highlight useful prompts, tools, and real use cases. Think of it as an AI + Marketing Show & Tell.

If you or someone you know has something worth sharing, please get in touch. I’d love to shine a light (and learn from) folks who are finding creative ways to build and use AI in their work.

So How is AI Being Used?

Many studies show that AI is now widely adopted. Now, the companies behind the models are sharing more data on how people are actually using their tools. OpenAI released a report that breaks use into three patterns: Asking (49%), Doing (40%) and Expressing (11%). This is similar to Google’s “I want to know, go, do, buy” micro-moments framework for search, which is helpful to explore customer intent. Anthropic released a report on Claude that groups use into Automation and Augmentation. Automation recently passed Augmentation, with 49% of use compared to 47%.

A new Pew survey on American attitudes toward AI revealed some, well, surprising views. 11% of Americans support AI advising people about their faith in God. If you’re in that 11% and want to take things a step further, check out ChatwithGod (or ChatwithGod Pro for $8/month.)

AI & the Workplace

Working on an AI project inside a large consultancy must feel complicated. On one hand, revenue from AI client work is becoming a major growth driver. On the other, consultancies like Accenture are using AI to automate tasks and layoff consultants. It’s a bit like a cashier teaching a customer how to use self-checkout.

Consultants are also among those eager to build their AI skills. Udemy reports that AI courses are booming on their platform, with agentic AI emerging as the most popular topic. A recent BCG report found that only 36% of professionals across industries are satisfied with the quality of AI training their companies provide.

This lack of strong training is contributing to another problem at work: workslop. These are AI-generated documents and presentations that look polished but contain little real substance. 40% of people say they’ve received workslop in the past month. This problem may grow as tools like Claude can now not only help with files but create them from scratch. Tip: ask ChatGPT to critique your work, not create / rewrite it.

AI & Marketing

Marketing teams have been early adopters of AI, and recent reports show no signs of slowing. A CMO survey found that 89% agree “Gen AI will make a massive difference in producing content quickly and cheaply,” and 90% agree “Gen AI will make it much easier to in-house marketing tasks.” A WPP survey of experts showed broad consensus that AI will produce most creative content, including music, TV, movies, and art (71% view this as likely). It’s hard to imagine a future where most ad production work is not done by Gen AI and overseen by a subject matter expert (aka a human). Tasks like resizing, reformatting, swapping images, changing copy and CTAs, and regionalizing content are important but repetitive. Brand managers want them done fast, and in my experience, designers aren’t exactly in a huge rush to take on this work.

AI as Media

Marketers are also interested in AI as media. An IAB survey found that 81% of media planners are interested in buying or selling ad space on consumer-facing AI platforms like ChatGPT. This makes sense: 60% of people use AI for product discovery, and 48% use it for travel and restaurant reservations. What brands wouldn’t want to be there?

They may not have to wait long. OpenAI is reportedly launching its own ad platform and features that let users make purchases directly without leaving the service. It is also creating new media spaces through ChatGPT Pulse. I’m interested in how how ad formats will evolve in this new context. Could brands sponsor follow-up prompts? Could they appear in a ChatGPT-curated shopping lists based on past prompts? Sponsor an agent to complete a related task?

Cool Beans

• Meta Ray Band Display: A cool demo that showcases a bunch of use cases that combine hand gestures with AR glasses. Like a design challenge where the only constraint was that you can’t use your phone.

• Gemini + Google Products: Google is turning Gemini into an AI layer that sits on top of all its products and screens. Gemini is being added to Chrome, letting you ask about what’s on your current tab. It’s also coming to Google TV to help you decide what to watch.

• New Baldness Cure? A new treatment reportedly made 100% of male mice regrow their fur. I didn’t know bald mice were a thing, but human trials are next. Stay tuned…

Digital Trends: 09.15.25

How can AI help me with this? I’m training myself to ask this question before starting any task. It seems simple and obvious, but old ways of working are hard to shake. In strategic planning, there are plenty of moments to pause and consider how AI might help. Neil Perkin has a great resource that maps AI’s role across different stages of the planning process with some smart thought-starters. The IAB has also published a very cool AI in Advertising Use Case Map that explores how AI can support research, planning, production, and measurement.

I love stumbling across creative ways to use AI in my work. To explore your own AI use cases or track pilots, check out the free, customizable templates in the Kickframe Toolbox. And if you’ve come up with any clever new use cases you need to let me know and I’ll share them in my next newsletter.

AI & Consulting Work

My interest in exploring new AI use cases comes in part from running my own small consulting and training business. These tools can make it feel like having extra people on my team, giving me capabilities (and time!) I wouldn’t normally have. For large consulting firms, I’m it is very different. What happens when thousands of junior staff are doing work that AI can now support? Hiring for junior consulting roles in Canada has dropped 40% since 2022, the year ChatGPT launched. At the same time, new “AI-first” consultancies are emerging, with junior teams focused on designing and refining AI-driven workflows.

More broadly, the impact of AI on hiring young people isn’t evenly distributed. Roles where AI automates work (like coding) are shrinking, while roles where AI augments work are holding steady. For those starting careers in strategy or marketing (I know a few of you who subscribe!), I think it will become increasingly important to take ownership of the value that you provide and be responsible for finding new ways for AI to increase it. And if you can help others – especially older, senior-level leaders - understand and apply AI within teams, you’re gold.

Shadow AI

One reason that you’ll stand out is that AI adoption in most companies is a mess. A recent study found that workers at over 90% of companies use personal chatbot accounts for daily tasks - usually without IT approval – while only 40% of companies have official subscriptions. As employees get comfortable with personal AI tools, they’re more frustrated with clunky IT-approved tools. But many keep using them on the down-low, with 1 in 3 calling it their “secret advantage.” This is creating a division between those adopting AI and not – a “two-tier economy”. For those of you who lead marketing teams (I know a few of you who subscribe!), I think it’s important to create a clearly supported safe space to experiment with AI, and focus on celebrating responsible, creative use cases and recognizing those leading the way.

Fresh Reports:

• Culture & Trends Report (YouTube): A marketer’s guide to the media habits and interests of 14–24-year-olds, with a bunch of references I’m not even going to try to pretend that I know.

• Social Media Trends / Marketer’s Guide (OK COOL): A fun, smart guide to what’s trending in social culture right now, with plenty of great examples and commentary.

• AI & Search (Semrush): Study shows that ChatGPT is not cannibalizing search, it is expanding search by providing Google searchers with a new mode of information seeking.

• How Customers us AI Search (Bain): New data shows that more people are using ChatGPT for shopping, and clickthroughs within ChatGPT answers are growing significantly (from 2.2% to 5.7% CTR).

Cool Beans

• New Audio Overviews (NotebookLM): Google keeps rolling out different ways to summarize and analyze your Notebook LM material. Now with new podcast-style formats.

• Claude for Chrome: Anthropic is testing a new browser extension that can work inside Chrome, and interact with what is within the browser. View the demo to view this browsing / agent panel.

• Airpod Pro 3 – Live Translation: Amazing demo of the real-time translation feature from Apple. Finally vindicated for dropping French in grade 11.

Digital Trends: 09.01.25

I was having a beer with a friend who said he was getting dumber. He blamed it on his frequent use of AI (not frequent use of alcohol). I have had the same feeling at times with my own use of AI, particularly when using it to help me write. Since writing is thinking, am I delegating the thinking because it can be difficult?

New research suggests this concern is real. A recent Microsoft study found that as people grow more confident in using AI, their critical thinking declines. Teens are noticing it too. One 14-year-old sketch artist put it perfectly: “I wouldn’t feel satisfied if I just typed and it made art for me. The process of thinking it through—feeling like, ‘my hand hurts but I’m close to finishing’—that’s what makes it meaningful. You can’t enjoy that if AI just does it for you.” So what can we do?

• Use AI at the beginning or end of a project, not in the “messy middle” where reasoning and decision-making matter most.

• When you use AI, ask it for contrasting perspectives or prompts that critique and/or reflect on its own responses.

• Practice debating with others. There are huge cognitive benefits come from it, and you can even use AI as your debating partner.

Actually, my friend and I debate over beer all the time. Maybe I’m ok.

AI & Brand Discovery

How can my brand show up more in ChatGPT responses? That’s the big question many marketers are asking. Agencies and consultancies have predictably launched new practice areas to serve this growing interest, sometimes called Generative Engine Optimization (GEO) or Answer Engine Optimization (AEO). But for now, the practices here look a whole lot like SEO: publish useful, structured, and authoritative content over time. The main difference may be creating more content to answer the exploratory questions people bring to chatbots.

What about Google? In Canada, Google is rolling out AI mode - the feature that many publishers fear is killing site traffic. They’re also experimenting with ad formats in this new interface. You can try it here. Many say AI will kill Google, but this article argues the opposite: if high-intent shoppers still use Google, advertisers will still value it as the “last touch” at the bottom of the funnel.

Amazon is also feeling the impact. For years, it’s been the starting point for many shopping searches. To protect that position, Amazon is blocking bots from scraping its product data for AI tools, while launching its own assistant - Rufus (see other retailer bots here). Meanwhile, manufacturers are taking the opposite approach - making sure their metadata is clean and structured so AI tools can easily find and recommend their products.

AI & Ad Agencies

I feel for ad agency owners. Advertising is tough business in the best of times, and AI is making it tougher. In-house teams are ramping up creative production (Kimberly-Clark now produces hundreds of AI-powered ads daily). Brands are also taking more control of media spend (direct US advertiser investment has jumped from 9.8% in 2019 to 30.3% in 2024). The size of the ad industry pie is shrinking.

So, what can agencies do to respond?

• Rethink time-based business models and focus on value (as defined by the client), with AI-driven efficiencies increasingly expected.

• Evolve the agency talent mix by investing in AI-focused roles like data scientists and AI Ops folks.

• Focus on what AI isn’t good at (yet) - deep consumer psychology and cultural insight. Stay upstream.

• Be transparent with clients about AI tools, policies, and guidelines to build trust and alignment.

• Go beyond efficiency to explore new ways of creating value – and potentially grow the pie.

Cool Beans

• Vibe Coding Example: Stephen Beck has a great write-up on how he ‘vibe-coded’ a cool website listing places to visit across the Hudson Valley.

• 21 Ways to Use AI at Work: The NYT shares how 21 people from very different jobs use AI at work – from selecting wines for restaurant menus to translating legalese.

• Talk to Statues: The Palace of Versailles collaborated with OpenAI to create an app where visitors can “speak” with 20 statues in the gardens.

• Gemini Storybook: A fun one for kids: describe any story you’d like, and get a personalized, illustrated storybook.

Digital Trends: 08.15.25

Ben Evans noted in a recent presentation that marketing is one of the areas most impacted by AI so far. That’s because content development is subjective (more than one “answer” is acceptable), and errors are easy to spot. Adoption is high - recent studies show that 89.5% of marketers are using AI in some part of their processes, primarily to generate copy and images. In addition, 86% of marketers report saving time - on average, 4.74 hours per week.

So what does this actually look like within marketing teams? In startups, a new HubSpot study found that 69% have a dedicated AI lead or team. It reminds me of the early “Head of Digital” role - someone tasked with evangelizing and identifying opportunities before the rest of the company (hopefully) catches up. Unilever has reportedly set up a GenAI “assembly line” for creative production (a term I’m sure creative professionals find deeply inspiring). It’s leading to the production of more creative assets, at faster speeds, with stronger results - and putting more pressure on creative agencies.

Marketing leaders, including at Unilever, are careful to position GenAI as a tool to “help free up time for people to focus on the more human elements of the creative process.” Ok. But leaders need to be clearer about their true intentions, even if it makes people uncomfortable. Yes, we want to create more. Yes, we want to spend less. Yes, we want to reduce turnaround times. Yes, we want better results. And yes, we will use GenAI to help us do that - in ways that will impact roles and processes. Let’s get real.

AI & SEARCH

Are Google AI Overviews reducing traffic to publisher websites? Publishers certainly think so and have been voicing their complaints to Google. The head of Search at Google recently responded, saying that traffic is stable and that the quality of search traffic is actually increasing. She also shared an interesting insight: more traffic is going to “forums, videos, podcasts, and posts where they can hear authentic voices and first-hand perspectives.” Rather than just optimizing for keywords, perhaps publishers need to focus more on creating this kind of content.

It’s a bit of a tightrope for Google to walk. Features like AI Overviews are valuable to users who now expect ChatGPT-like answers and experiences. However, Google can’t alienate advertisers by encouraging users to rely solely on zero-click searches. Google’s new Web Guide feels like a middle ground—using AI to categorize website links rather than just summarize them. We’ll see if Google can continue to straddle this space between AI-generated responses and traditional website links—this approach feels a bit like a turducken.

In the meantime, more brands are working to increase their visibility within AI recommendation engines, in addition to general web search. HBR recently released a useful framework for measuring and optimizing your presence in LLMs. It’s interesting to see how platforms like ChatGPT are moving into the space Google has dominated for the past 20 years. OpenAI is reportedly developing a checkout feature that allows users to complete transactions within ChatGPT. I’m skeptical (see Meta’s attempts over the past 15 years), but there may be potential—especially if it integrates well with ChatGPT’s new agent that can complete tasks on your behalf. Could a ChatGPT agent hang out in a Ticketmaster waiting room and automatically buy the best concert tickets for me?

FRESH RESEARCH

• AI Pulse Survey (EY): Despite the hype around agentic AI, only 14% of companies have implemented it. The top barriers are cybersecurity (35%) and data privacy (34%).

• GenAI Data Exposure (Harmonic): A study on GenAI usage shows significant risks: 22% of uploaded files and 4% of prompts contained sensitive data. Files posed the greatest threat, driving the most severe PII exposure incidents.

• Deloitte Global Gen Z & Millennial Survey 2025 (Deloitte): GenAI fears are shifting young people toward skilled trades—66% of Gen Z and 68% of millennials plan to pursue GenAI-resistant careers, up from 59% and 52% last year.

• The Substack AI Report: Substack writers place high value on AI - on average, they’d pay $140/month to keep access. But the community is divided: users expect significant benefits to their work and careers over the next five years, while non-users believe it will be harmful. It feels like the early internet - you have to use it to understand the potential.

COOL BEANS

• Robot Keytar Player: Ok, music made by AI isn’t cool. But a poorly disguised robot playing keytar on stage at a Chinese Music Festival is.

• ChatGPT for Schoolwork: OpenAI has launched Study Mode to help students build critical thinking skills, rather than just get answers. Hopefully it’s used as intended. I’ve seen my own kids use ChatGPT in productive ways—like generating study guides or quizzes based on their material (though I suspect there are other uses they’re less inclined to tell their dad about).

• AI-Powered App Builders: I’ve been tinkering with Replit and Lovable lately. As a non-coder, it’s wild how quickly you can prototype mobile apps using plain-language prompts. It’s helpful in my world to be able to quickly visualize an idea (even in a very basic way), instead of just describing it. Below is my latest: an app that helps me to find outdoor pickup basketball courts within walking distance of a bar for post-game beers. Might need to add a filter for nearby emergency rooms too.