Remember how AI was going to disrupt and transform our businesses? Well, according to many of my perambulations – and more than one piece of research – a lot of that hype has since fizzled. Why? Because, from where I sit, there’s more focus being placed on installing AI than installing AI of practical value.
- Findings from the U.S. Census Bureau’s Business Trends and Outlook Survey (BTOS) show an overall decline in AI adoption. According to tech.co, “the data points to businesses with over 250 employees adopting AI significantly less than just a few months ago, with businesses with between 100 and 249 employees and between 50 and 99 employees both seeing a more modest decline.”
- Reinforcing the point, AI Implementation Research from Project NANDA out of MIT (see The GenAI Divide: State of AI In Business 2025), reports that “AI adoption is high, but disruption is low.” Specifically, it says, 95% of organizations are getting no return at all on their AI investments. “Just 5% of integrated AI pilots are extracting millions in value, while the vast majority remain stuck with no measurable P&L impact. This divide does not seem to be driven by model quality or regulation, but seems to be determined by approach.”
- And the most common story I hear is “we invested in AI. We tested tools. We ran pilots. But we’re still not seeing results.”
Most often, this state of affairs arises because the executive marching orders were issued in terms of the need to “do AI” rather than figuring out where – or even whether – AI can make an everyday difference. And therein lies the rub.
Avoiding Your AI Stall
Like as not, the issues that are slowing AI’s roll have little to do with the technology, which is certainly imperfect but can be made to return enormous value. How? By focusing from the start on my favorite and most fundamental question:
What business problem are you trying to solve?
If you can’t answer this clearly and concisely, then your initiative almost certainly will stall – because if you can’t define your desired result, then you can’t know if you’re making meaningful progress, your senior managers will wonder “what’s the point?” and they’ll then pare your program.
Happily, your AI journey doesn’t have to stall forever, or even at all. The key – as ought to be the case with any and every technology effort – is to spend dedicated time and attention on even this short list of critical tasks:
- Identify use cases that may actually move the needle
- Prioritize them according to their potential business/operational benefit
- Articulate a clear and measurable value expectation
In so doing, take pains to be and remain as pragmatic as possible. Though the excitement curve is flattening, so much frenzy still surrounds AI as a disruptive and transformative influence that it doesn’t take much for it to become divorced from reality. It’s your job to make sure this doesn’t happen.
If you agree that the power of AI depends on its ability to return practical value, let’s connect and work together to achieve the results you need.