Organisations everywhere are experimenting with chatbots, copilots and intelligent assistants. Yet the latest MIT NANDA report highlights a sobering statistic: 95% of GenAI initiatives fail to deliver measurable return on investment within six months.
At first glance, this seems to reinforce the idea that GenAI is little more than hype. But a closer look at the report reveals a more nuanced picture. “Failure” in this context does not mean the technology doesn’t work. Rather, it means that within the six-month window following a pilot, no clear profit and loss impact was recorded. For complex transformations, that's an exceptionally short horizon.
This reflects a reality many leaders already recognise: AI is not a quick win. Success requires more than a proof of concept or a flashy demo that dazzles the boardroom. The real challenge lies in integration and adoption, embedding AI into everyday processes, enabling it to learn from context and ensuring it delivers tangible business outcomes.
The reasons are all too familiar. Many projects get stuck in what’s often called “pilot purgatory”: a demo that works in isolation but never evolves into a scalable solution.
A key factor is the learning gap. Most AI systems don’t retain context across sessions, fail to learn systematically from feedback and struggle to adapt to real workflows. What impresses in a demo often delivers little lasting value in daily operations. On top of that, many initiatives lack a clear connection to strategic objectives and KPIs. The result: frustration, wasted investment and a growing gap between promise and reality.
Budget allocation compounds the issue. More than half of AI spending goes to sales and marketing, where results can be showcased quickly on dashboards. Yet, as MIT highlights, the less glamorous back-office functions like finance, document management and operations, often provide the most substantial and sustainable ROI.
The organisations that succeed in creating value with GenAI share various common traits:
In short: success does not come from experimentation for the sake of it, but from a deliberate strategy with a clear focus on value.
The MIT report is not a reason to question the potential of GenAI. It is a wake-up call to approach it differently. At AE, we see it every day: organisations that invest in strategy, integration and adoption today secure a competitive edge tomorrow.
Our teams help organisations define realistic use cases, validate them and embed them in day-to-day operations. Not with lofty promises, but with measurable impact built step by step.
This user-driven success model explains why AE is part of the rare 5% of organisations that turn GenAI pilots into lasting business value:
The SD Worx AskMe story shows that with the right approach, clear KPIs, user-centred design and a focus on adoption, GenAI can evolve from a promising experiment to a true driver of business innovation and transformation.
The headline “95% fail” may sound stark, but the reality is more nuanced. Generative AI itself is not failing; it often remains stuck in pilot mode at organisations that never make the leap to integration. The real challenge lies not in the models, but in the demanding work of process change, adoption and rigorous evaluation.
The real question is not whether AI can deliver value, but how organisations prepare themselves to be among the 5% success stories. Those with digital ambition take the lead and the time to act is now.