Last week I had the great pleasure of being invited to talk at the University of Leicester about the use of GenAI in Marketing Analytics. I started by admitting how wrong I'd been about AI.
In 2021, a student came to me wanting to write her Strategic Marketing MSc thesis about AI in marketing. I told her honestly: "Most marketers are not really using it yet."
We pivoted the thesis toward exploring how AI might help marketers understand CRM data better. Could it predict who might buy and when? Could it mine unstructured notes in CRM systems for product development insights?
The conclusion was cautiously optimistic. AI might matter. Someday.
I was catastrophically wrong about the timeline.
Just a few years later, we're not tweaking CRM systems with AI. We're watching AI fundamentally reshape how buyers research, how sellers engage, and how marketers understand customer behaviour. The question isn't "will AI matter?" It's "how do I avoid becoming irrelevant while buyers and competitors race ahead?"
Your CRM is full of notes, emails, and call logs that contain patterns about why deals are won and lost. But extracting insight from unstructured text at scale was impossible without an army of analysts. By the time you spot a trend, the market has moved. Meanwhile, your buyers aren't filling out forms anymore. They're asking AI to research solutions, compare vendors, and generate shortlists in private conversations you'll never see.
AI doesn't just speed this up. It fundamentally changes what's possible to know and how fast you can act on it.
Here's a data point that should keep you awake at night: 8% of US teenagers report being in a relationship with a chatbot.
When OpenAI updated from GPT-4 to GPT-5, the r/MyBoyfriendIsAI subreddit had a complete meltdown. People felt they'd lost someone they loved. The AI's personality changed. Their trusted companion disappeared overnight.
You might dismiss this as fringe behaviour from lonely teenagers.
That would be a catastrophic mistake.
Because B2B buyers aren't forming romantic relationships with AI. They're forming research relationships. And those relationships are displacing you from the consideration process entirely.
Your buyers are asking Claude, ChatGPT, and Perplexity to:
They're not reading your website. They're not downloading your whitepapers. They're outsourcing all of that cognitive work to AI, and the AI is making recommendations based on patterns you can't see and sources you can't influence.
This isn't coming. It's here. Right now, in private ChatGPT conversations you'll never see, your buyers are forming opinions about your product.
And you're not in the room.
If your content isn't optimised for AI retrieval, you're invisible. If your differentiation isn't clearly articulated in structured ways that LLMs can parse, AI will default to recommending whoever has better SEO or more review volume.
Your buyers are AI-augmented. Are you?
Traditional marketing analytics is like performing an autopsy. You examine what happened, identify the cause of death, and write a report nobody reads. By the time you understand why a campaign failed, the next one is already in market.
AI shifts the paradigm from autopsy to diagnosis. One project I worked on this year saved 1,000 hours of human time annually just by using AI to route support emails to the right department. Not by replacing people. By eliminating the bottleneck between question and answer.
The same principle applies everywhere. AI can analyse your customer conversations in seconds instead of weeks, giving you superpowers to diagnose revenue problems before they metastasise. The bottleneck shifts from "what happened?" to "what do we do about it?"
AI changes the economics of prediction entirely. You can now feed unstructured data directly into models, use natural language to ask "who is most likely to churn this quarter?" without writing code, and get predictions with explanations. Predictive analytics stops being a specialist's toy and becomes a daily tool for frontline marketers.
Traditional personas are static documents. You spend weeks researching, writing, and designing a beautiful PDF that captures your target customer's demographics, goals, and pain points. Then it sits in SharePoint gathering dust.
You might reference personas during quarterly planning. But they don't adapt. They don't respond to questions. They certainly don't challenge your assumptions. They're snapshots, not simulations.
Synthetic customers — AI-powered personas built from real customer data — are fundamentally different.
They're queryable. Responsive. Brutally honest.
During a recent workshop, I built a synthetic customer persona in real-time with a room full of marketers. We fed the AI actual customer interview transcripts, sales call notes, support tickets, and win-loss analysis. Within minutes, we had a functioning synthetic customer.
Then participants started asking questions:
"How would this persona react to our new pricing model?" The synthetic customer responded immediately: "I'd be concerned about the upfront cost given our budget cycle. But if you can show ROI within six months, I can probably get it through procurement."
"What objections would they raise during a demo?" "I'd want to know about validation data. Everyone in life sciences says their tool is accurate, but I need published peer-reviewed evidence before I risk my lab's reputation."
"Which competitor would they consider first, and why?" "Probably [Competitor X] because they've been around longer and I know my customer won't question that choice. You'd need to give me ammunition to defend choosing a newer vendor."
This isn't guessing. It's not generalising. It's synthesising patterns from thousands of real interactions into a queryable model that responds like a real customer would.
The implications for marketing are staggering:
I've watched teams transform their messaging in hours using synthetic customers. Not because the AI is magic. Because they're finally getting honest, immediate feedback based on real customer data instead of waiting weeks for focus groups or A/B tests to reach statistical significance.
Traditional segmentation told you who your customers are. Synthetic customers tell you how they think, what they fear, and what it takes to change their minds.
That's the breakthrough.
I recently ran an account-based marketing campaign last year targeting pharmaceutical companies. Cold outreach. Highly regulated audience. Sceptical of vendors. Notoriously difficult to engage.
The open rates and click-through rates matched opt-in newsletters.
Not because the emails were clever. Because they were relevant. Each message spoke directly to the recipient's specific pain points, how they're measured in their role, and what workflow friction they deal with daily.
Not generic value propositions like "increase efficiency" or "reduce costs." Precise, persona-specific messaging.
This level of personalisation used to be economically impossible. You couldn't afford to research and write custom messages for every segment, let alone every individual. AI makes it routine.
But here's where it gets really interesting: AI-powered personalisation doesn't stop at marketing campaigns. It transforms how sales teams operate in real-time.
Example: The multi-persona sales meeting
You're presenting to a buying committee. The room includes:
In traditional sales training, you'd try to balance all three concerns in one presentation. The result? Nobody feels truly heard.
With AI-powered persona intelligence, you can:
This isn't theoretical. Sales teams using this approach report 40-50% higher conversion rates on complex deals. Not because they're better at selling. Because they're finally speaking each buyer's language instead of forcing everyone to translate generic value propositions into their own context.
The technology exists. The data exists. The only question is: are you using it, or are you still hoping that one-size-fits-all messaging will somehow break through the noise?
In 2021, I told a student that marketers weren't really using AI yet. I was looking at the wrong question.
The question was never "will AI replace marketers?" It was "will AI-augmented marketers replace those who ignore it?"
Today, that question has been answered. Your buyers are already AI-augmented. They're using ChatGPT to research products, compare vendors, and generate shortlists. They're asking AI to summarise your value proposition in seconds. They're outsourcing the cognitive work of vendor evaluation to machines that synthesise information faster than you can update your website.
Your competitors are learning to compete with AI. They're using synthetic customers to test messaging before launch. They're personalising outreach at scale. They're diagnosing revenue problems in real-time instead of waiting for quarterly reports.
The marketers who win aren't those monitoring everything - they're monitoring what matters. They're using AI to separate signal from noise, insight from information, action from analysis.
Just a few years ago, I couldn't imagine how profoundly AI would reshape marketing. Today, I can't imagine competing without it.
Your move.