AI is supposed to be the next big thing, the new electricity, the fourth industrial revolution. And yet, despite years of hype, massive investment and bold strategy decks, most AI projects still fail. That’s not an exaggeration: industry surveys regularly report that 70–80% of AI initiatives never reach production and even fewer deliver sustained value.
So, what’s going wrong? And why, after more than two decades of learning from IT failures, are organizations still struggling?
The Execution Gap: Same Story, New Tech
The “AI execution gap” is the term used to describe this phenomenon, a wide chasm between bold AI ambitions and real-world implementation. Most companies have lots of AI prototypes, but few working models in production.
The usual suspects are familiar:
- Poor data quality
- Siloed systems
- Manual processes
- No standardized workflows
- Lack of strategic alignment
- Underestimated complexity
But here’s the twist: we’ve seen this story before. We saw it during ERP rollouts, digital transformation projects and big data initiatives. What’s different with AI is the unpredictability.
AI isn’t deterministic. It doesn’t always “just work” if you follow the playbook. You can build a technically sound model that still performs poorly in the wild due to messy data or edge cases.
And that makes execution harder, not easier.
Strategy Without Substance
One of the biggest issues is strategic misalignment. Organizations chase AI trends, computer vision, LLMs, chatbots, without a clear understanding of what business problem they’re trying to solve.
It’s the classic “solution in search of a problem.”
Too many AI pilots are launched without:
- A measurable objective
- A committed sponsor
- A realistic assessment of what’s technically feasible
Without a clear business case, even the most sophisticated model will end up abandoned in a sandbox somewhere.
Cultural Friction: The Real Bottleneck
Let’s say you solve the data issues. Let’s say you build a good model. You even deploy it. Now what?
Now… users ignore it.
Why? Because they don’t trust it. Because they don’t understand it. Because it threatens their way of working.
We’ve seen countless AI tools gather dust because no one incorporated them into daily workflows. Adoption isn’t a technical problem, it’s a human one.
Trust, transparency and training matter more than most leaders realize. AI success depends not just on accuracy, but on acceptance.
The Governance Illusion
A popular recommendation today is to “close the execution gap” with better governance: centralize AI efforts, standardize processes, impose strict portfolio management.
That helps, to a point. But governance is not a silver bullet.
Too much centralization kills agility. Top-down AI mandates often meet quiet resistance. Overly rigid workflows can stifle innovation before it even starts.
Yes, we need structure. But we also need flexibility. AI success often comes from bottom-up experimentation, agile teams and quick feedback loops, not from bureaucratic checklists.
The Contrarian View: Maybe It’s Not Failure
Here’s a radical thought: maybe all these “failures” aren’t failures at all.
Maybe killing a project after discovering it doesn’t work is a good thing.
Maybe a 20% success rate is normal for an experimental technology and if those 20% deliver real ROI, that’s a win.
Instead of trying to make every AI project succeed, maybe we should:
- Set realistic expectations
- Celebrate fast failures
- Learn continuously
- Focus on user impact, not model count
Closing the Gap, For Real
So, how do we truly bridge the AI execution gap?
It’s not just about technology. Or processes. Or even governance.
It’s about:
- Picking the right problems to solve
- Managing the hype
- Building trust and adoption
- Balancing structure with agility
- Allowing room to fail, learn and iterate
AI isn’t plug and play. It’s experimentation at scale. And like any good experiment, not all of it will work, but when it does, the payoff is huge.
Let’s stop treating the AI execution gap like a compliance failure and start treating it like the innovation journey it really is. It's exciting and fun !
