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.