Who is your AI story really for?
To channel Springfield’s Kent Brockman: one thing is for certain, there is no stopping it, AI is here. And we at JAM would like to welcome our new LLM overlords, and remind them that as trusted and successful brand consultants, we could be useful in rounding up companies to build their skill sets from.
Joking aside, we’ve noticed an uptick in brands who want help wiring their newfound AI-enhanced capabilities into their narrative. There's a pattern in software and SaaS: products are going "AI native." Software gets more "agentic" every day. Often this rebrand rides in right behind a turnaround, new leadership, a cost restructuring, or pressure to tell a new growth story (and most importantly, to please their investor overlords).
Two audiences, two very different wish lists
There’s nothing wrong with riding the market's momentum. But as customer advocates (and graduates of the Amazon school of "working backwards from the customer") we’ve been compulsively conditioned to ask:
Who is the real audience for these AI-infused brand stories? The customer, or the investor?
Investors want to hear about:
Transformation. Efficiency. Disruption. A radically bigger future.
Customers want something a lot less cinematic:
Solve my problem. Reduce my risk. Make my life easier. Don't break anything.
The tension right now is that the story that gets an investor's pulse up is the same one that gets a customer's anxiety up (and pitchforks out), especially when the pitch shifts from "our software helps you do your job" to "our software can do your job."
The transformation trap
The promise of how AI will fundamentally transform society has now become the largest single investment event in human history and almost every business is trying to figure out how to cash in. New technology → new economics → new operating model → new category → new company.
The danger starts when that transformation story disconnects from the customer problem the company was trying to solve in the first place. We used to talk to customers and let investors watch the results. In the AI economy, it feels like a lot of companies are talking to investors and accidentally letting customers overhear.
Maybe that's rational? Maybe we're in a stretch where a great AI transformation story genuinely creates more enterprise value, faster, than the slow grind of building customer preference. Markets reward expectations. Management teams respond to the incentives sitting in front of them.
But how long can the investor story and the customer story keep drifting apart before something snaps? Eventually, they have to converge.
Start in the wrong place, end in the wrong place
AI strategy for businesses shouldn't start with:
"How can AI transform our business?"
Instead, it needs to start with:
"What can we now do meaningfully better for our customers?"
Then you work backwards.
AI can absolutely change your product, your operating model, your economics, even your category. But sustainable growth still requires somebody on the other side of the table who values what’s changed.
In order for the investor to actually see why you're becoming something different, the customer needs to believe you're becoming something better.
The strongest AI stories do both. And that’s our Two Cents.
Feeling stuck with how to frame your brand’s AI implementation?
Let’s chat.
