Stop choosing the wrong Agentic AI use cases

Psychologist Abraham Maslow once warned: “It is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail.” Agentic AI is becoming the enterprise version of that hammer.

Once people understand what agentic AI can do, the list of possible use cases grows quickly.

While that enthusiasm should be applauded, it can lead to strategies that are back to front “If AI is the answer, what’s the question?” By the time it comes to looking at results and whether the investment in AI has been fruitful, it’s hard to identify what’s been achieved and why achieving it was important in the first place.

Start with the value, not the agent In the rush that followed ChatGPT, many organizations deployed AI tools to their workforces at large with no defined value or end goal.

People started working differently almost immediately, but with no baseline captured, there was no way to know what had actually improved.

Who knows how long it takes to write a coherent email and who knows what time is saved by having ChatGPT rephrase it for you! This is what McKinsey calls the “gen AI paradox”.

Its 2025 survey found just 39% of organizations reported any enterprise-level financial impact from their AI investment, despite mass adoption.

Organizations need to be precise about what they want to measure.

There are three layers to this and most only capture the first.

Adoption: are people using it? Behavior: are people doing their jobs differently? Outcome: revenue per salesperson, tickets closed per engineer, cycle time on a review gate.

Adoption and outcome together show a correlation; for example, people who use AI sell more.

But it’s the, often missed, behavior layer in the middle that turns that correlation into causation, i.e. they sell more because they are now able to use AI to fill in more client reports, leaving more time to hit the phones .

Know your workflow If organizations can’t see how work is really being done, two things happen.

The baseline measures the wrong process, making any claimed improvement meaningless and an agent given the wrong steps cannot complete the job.