If you’re feeling confused about AI but pressured to get it right, you’re not alone.
Everyone else is just better at hiding it. Between 70–85% of AI projects fail to deliver their intended value. In 2024, 17% of companies scrapped most initiatives. By 2025? 42%. £252.3 billion spent. 74% showing no tangible value. £7.2 million lost per failed initiative.
Nobody’s cracked this yet. Not really. And here’s the part that stings: the technology works.
We’re Doing It Backwards
Boston Consulting Group found something revealing:
- 70% of AI implementation challenges = people and process issues
- 20% = technology problems
- 10% = the algorithms themselves
Yet we spend most of our time obsessing over algorithms.
BCG’s rule for organisations that actually succeed? Invest 10% in algorithms, 20% in technology, and 70% in people. We do the opposite. We pour resources into platforms, fine-tune models, debate specs. Then wonder why staff resist, customers complain, ROI vanishes.
It’s a Leadership Problem
The data doesn’t lie:
Nearly half of employees say their manager doesn’t know how to help them with career development. Another 46% say management simply doesn’t know how to help with career advancement.
- 73% lack clear executive alignment on success metrics
- 68% underinvest in data governance
- 61% treat AI as an IT project rather than business transformation
- 56% lose active C-suite sponsorship within six months
None of these are technology failures.
Projects with sustained CEO involvement? 68% success rate. Those that lose sponsorship? 11%. That gap isn’t about executive presence. It’s about leaders who can build trust, navigate resistance, and actually take people through transformation – not just announce it.
McKinsey’s conclusion? The barrier isn’t employee readiness. It’s leadership.
Only 33% of senior leaders even somewhat understand how AI creates value. But that’s the easy part. The hard part? Developing leaders who challenge assumptions, admit uncertainty, build psychological safety, and bring teams along.
Contact Centres Will Always Need People
AI can augment. It should augment. But customers still need to speak to a person. The AI itself needs overseeing.
Without investment in people, they can’t move up the value chain. Can’t offer genuine support when things get complex.
Yet 52% of employees get only basic training. 20% get little to none. And 48% believe better training would transform adoption.
The 14% of companies described as AI ‘pacesetters’? Three times more likely to have proper change management. They know: technology without culture equals failure.
Nobody’s Talking About Trust
Trust in company-provided AI fell 31% between May and July 2025. Trust in agentic AI? Down 89%.
PwC surveyed 50,000 workers globally. Workers under financial pressure are less trusting, less motivated, less likely to believe the AI narrative.
This isn’t a capability crisis. It’s cultural.
65% of people in the bottom income quartile believe AI will leave them behind. Half of middle-income earners feel the same. We’re facing resistance before we deploy a single model. Our AI didn’t fail because the algorithms weren’t sophisticated enough.
It failed because we treated transformation as a purchasing decision…technology was never the problem.
Stop Buying Technology. Start Building Leaders.
The organisations that succeed with AI aren’t the ones with the best platforms.
They’re the ones with leaders who know how to bring people through change. Who invest in trust before tools. Who create environments where staff see AI as support, not threat.
When leaders get this right, AI becomes what it should be: something that frees people to do their best work.
If you’re ready to approach AI implementation differently then let’s chat!