The #1 AI Trap Leaders Will Fall Into. And How to Avoid It

People have got AI wrong. They are obsessed with agents and automations that shave minutes off repetitive tasks. Nice to have, sure. Your inbox cleared, a customer support ticket drafted without effort, finances monitored for dips in key metrics, and marketing campaigns spun up in days instead of weeks. But that is the ceiling of our thinking at the moment.

Here is the thing: these baseline use cases do matter. They are the low-hanging fruit every business should execute on. They free up time and energy for people to focus on higher-value work such as being creative, reimagining business models, unlocking new revenue streams, or re-engineering how the company operates. They are the stepping stones.

The trap is stopping there. Too many leaders treat ticking these boxes as “we have done AI”, or this is where our journey ends. That mindset locks in an artificial ceiling. The real advantage comes from making the leap of imagination, not just automating what we already do but asking how AI lets us do things we could not even conceive of before. That is where the innovative applications lie, and that is where the next competitive edge will be built.

Every major technological transformation started as a sideshow before it rewrote industries. At first, companies focused on surface-level applications. The winners were those who saw past the obvious and reimagined their models. The laggards were those who stopped at the ceiling.

Internet:

Cloud:

Mobile + Social:

Each wave wasn’t about digitising the old way of doing things. It was about unlocking an entirely new way of reaching customers, serving them, and running businesses. AI is no different.

The pace of change has caught everyone off guard. Rewriting your mental model of the world never happens overnight. Whilst not universal, but the more experience you have, the harder it is to let go of old ways of operating, with years of muscle memory make thinking rigid. The good thing is we're seeing plenty of experienced operators making the leap and adapting fast. On the other hand, we've got people earlier in their careers who are able to spot applications more easily because they are not weighed down by baggage.

The real block is the human learning curve with AI. Dharmesh Shah’s graph below shows it clearly.

AI capability is compounding at an exponential rate, while our ability to learn and adapt is inching forward in a straight line. The gap between the two is where competitive advantage, and competitive collapse, now sits.

That gap explains why most executives anchor their thinking to baseline use cases like email writing, campaign automation, predictive inventory purchasing, or optimising customer support. They are climbing the shallow slope of the learning curve while AI capability has already sprinted far ahead. The ceiling exists because we mistake the bottom half of the curve for the whole story.

Even those living and breathing AI get caught there. We tinker with micro-use cases while missing the fact that the upper curve is already unlocking new operating models, new industries, and entirely new ways to organise work in the same way the internet, cloud, mobile & social rewrote the playbook.

Closing the gap requires skating to where the puck is going, which means leaders must place bets even without perfect information, because waiting for certainty only guarantees you stay on the lower slope. The leap of imagination is the bridge between executing on the stepping stones you can see today, and looking for the next breakthrough as business models change in-front of us.

Understandably it is incredibly difficult to see where the future will end up. We do not know if the first major changes will appear in how customers behave, or in how competition manifests. But history suggests this is often where the impact shows up first.

With AI agents, customers will not search, click, and compare the way they do now. Their agents will book trips, choose insurance, or negotiate contracts, sometimes before the human even realises the need exists. Engagement shifts from visible decision-making to delegated, invisible action.

That is why treating AI as a faster email writer or marketing copilot is a ceiling. The customer experience itself is about to be rewritten. Search engines, comparison sites, and even traditional brand marketing start to matter less when agents transact directly. Loyalty and consideration are built not through campaigns, but through whether your business integrates seamlessly into an ecosystem of agents that act on the customer’s behalf.

This mirrors every previous wave.

AI is next. The difference is that customers may not even be consciously in the loop when decisions are made. That demands businesses break through the mental ceiling, because the winners will be those who design for a world where agents, not humans, are the primary decision-makers.

If customers are the first to change, businesses will not be far behind. This rewiring happens on two fronts:

What once required a full team can now be handled by one person and an agent. Workflows that used to take days or weeks collapse into seconds. Copywriting that took an agency a week becomes a prompt. Customer support that once needed hundreds of reps is handled by autonomous agents with greater accuracy and scale, managed by a handful of humans. Software that once required years to build and was sold to a mass market can now be prototyped in days and tailored to a single individual.

This is where AI orchestration comes in. Most companies are still thinking about AI as a set of departmental tools: marketing runs campaigns, finance monitors risk, service handles tickets. That is another example of a mental ceiling we place on AI.

The next step is to treat AI as a horizontal layer across the business. Insights in one department should not stop at a report for a manager. They should trigger action in another department, and then trigger an outcome in the next, without a human needing to hand it over.

This is not about creating more actions for humans, it is about delivering outcomes without adding work. A good place to start is to ask:

That exercise forces you to lift above the incremental and confront how AI could redefine your model entirely. The companies willing to ask that question will see opportunities others miss.

At the end of the day, people do not want more tools or more tasks to do. They want outcomes.

For decades, technology has promised outcomes but delivered enablement. SaaS gave us tools, but we still had to operate them. Agencies talked about outcomes, then dropped a slide deck in your inbox. Even consumers were pushed more work: “log into your portal”, “download our app”, “track it yourself".

AI opens the door to something different. The outcome itself is delivered, and the human only steps in where judgment, creativity, or empathy is needed. The trip is booked, the campaign is launched, the financial risk is flagged and acted on.

Some call this Service-as-Software. And yes, the name sounds like someone flipped SaaS on its head after one too many coffees. But the idea matters: instead of buying a tool to help you act, you buy the result itself.

This is not about removing people. It is about removing the unnecessary work that technology has quietly shoved onto us for years, so people can focus on what only they can do: strategy, creativity, relationships, or just more time to breathe. Enablement is the stepping stone, and true delivery is the destination.

This is the point where the pattern breaks. The internet rewired distribution, cloud rewired scale, mobile and social rewired access and interaction. AI is different because it rewires the very act of thinking and doing. For the first time, intelligence itself is abundant.

That changes the game as we're no longer bound by human attention, bandwidth, or expertise. AI can read, write, reason, see, and act. It does not just support decisions, it can make them. It does not just provide information, it can deliver outcomes.

Unlike the earlier shifts, this one sits on top of all the infrastructure already in place. The internet gave us connectivity. Cloud gave us capacity. Mobile gave us access. AI combines them all and accelerates them. And this time, it is not limited to Silicon Valley as a first mover: the pace is global, uneven, and relentless.

So here is the inflection point. Every leader has to decide: do you stop at enablement, building tools and ticking boxes, or do you push for outcomes, delivering results without dragging people through more work?

One path keeps you at the ceiling. The other path opens the next era of business.