Moving Beyond AI Hype And Headlines
AI is everywhere, but are organisations getting the value they expected?
The research raises some important questions.
MIT NANDA (2025) reports that 95% of generative AI pilots show no measurable profit and loss impact.
S&P Global (2025) found that 42% of enterprises had abandoned most AI initiatives.
RAND (2024) identified leadership misalignment as a key contributor to AI project failure, while Deloitte (2026) reports that only one in five companies has mature governance for autonomous AI agents.
These findings point to a challenge I'm seeing with organisations. AI adoption is moving ahead, but leadership, governance and business expectations aren't always keeping pace.
How do you manage the AI hype?
1. Getting the Foundations Right
Within technology teams, AI is being used to support software development, code generation and other technical activities. This can improve productivity, provided people review the output, test the results and remain accountable for what is implemented.
AI has a role to play, but it needs appropriate governance, clear responsibilities and sound human judgement. The objective isn't to introduce new tools, but to improve how work gets done and deliver tangible business outcomes.
2. When More Output Creates Less Clarity
The bigger challenge I'm seeing is the broader adoption of AI across organisations.
People are using AI to respond to emails, create presentations and produce documents at speed. On the surface, this looks productive.
But what happens when everyone generates more content without agreeing on the problem they're trying to solve?
We can end up with more material to review, conversations that go around in circles and decisions that remain unresolved. Output increases, but understanding doesn't necessarily improve. This is where leadership matters.
3. Bringing People Together Around AI
I'm running more workshops with leadership teams because organisations need to step back and establish some practical principles.
What business problem are we solving?
Where can AI make a difference?
What should we challenge or stop?
How will we measure success?
These questions require discussion, judgement and a shared understanding of priorities.
Leaders need to set clear expectations, guide their people and create an environment where assumptions can be challenged.
AI presents real opportunities, but progress requires more than experimentation. It requires clarity, accountability and a focus on business value.
If you're exploring AI adoption or would like independent assurance around your AI activities, feel free to reach out.
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