The budget is approved. The licences are purchased. The pilot is live. And yet, weeks later, the tools sit underused, the numbers are flat, and the ground-floor anxiety is unmistakable. If this sounds familiar, you are not alone – and the problem almost certainly has nothing to do with the technology.
Across boardrooms in 2026, a stubborn and expensive pattern is repeating itself: organisations invest heavily in AI capability and almost nothing in people readiness. The result is predictable. Low adoption, wasted spend, and a workforce that is quietly – or not so quietly – struggling.
The Investment Gap Is Enormous – and Growing
Gartner forecasts worldwide AI spending will reach $2.52 trillion in 2026, a 44% increase year-over-year. That is a staggering commitment by any measure. Yet despite that momentum, 88% of organisations now use AI in some form, while 37% apply it only at a surface level with little or no meaningful process change. The tools are in the building. The transformation is not.
Kyndryl’s second annual People Readiness Report, released in June 2026, puts the sharpest point on this yet. The global study of 1,100 senior business and technology leaders found that 57% of enterprises now have AI embedded in core business processes – up from 35% just one year prior. But here is the number that should stop every CIO cold: only 11% of those same organisations have achieved both of their top two AI objectives.
Deployment and outcomes are not the same thing. The gap between them is almost entirely a people problem.
Readiness Is Falling as Expectations Rise
The same Kyndryl report found that only 23% of business leaders believe their workforce is fully prepared for AI – a six-point drop from 2025. That decline happened in a year when AI investment accelerated sharply. In other words, the more organisations have spent on AI, the less ready their people feel to use it effectively.
ManpowerGroup’s Talent Solutions division reinforced this picture in research published on 22 July 2026. The finding was blunt: only 3% of organisations say their leaders are highly prepared to manage AI-enabled ways of working. At the same time, 78% report employee concern about how AI will affect their jobs. Leadership is being asked to guide teams through one of the most significant workplace shifts in a generation, and almost none of them feel equipped to do it.
That is not a technology gap. That is a readiness crisis.
The Anxiety on the Ground Is Real and Widening
For IT decision-makers focused on delivery timelines and technical milestones, the emotional dimension of AI rollouts can feel like someone else’s problem. It is not.
A 2026 workplace survey from Beautiful.ai found that 72% of managers believe employees fear that AI tools will make them less valuable at work – an 8-point increase from the previous year. Seventy percent believe employees fear AI will eventually lead to job loss, up 12 points year-over-year. These are not fringe anxieties. They are the dominant sentiment in most organisations rolling out AI today, and unaddressed fear is one of the most reliable predictors of non-adoption.
When employees do not understand why AI is being introduced, how it affects their role, or what happens to them if the tool does their task better than they do, they disengage. They find workarounds. They perform compliance without genuine adoption. The licence gets used; the value does not materialise.
Training Is the Most Underinvested Lever
The training picture is, frankly, poor. SurveyMonkey’s 2026 research found that only 13% of US workers received any AI training from their employer. A separate report noted that the share of organisations offering formal AI upskilling actually fell to around 26% in 2026, down from roughly 35% the prior year.
A Workday study captured the contradiction at leadership level: 66% of business leaders say AI skill training is a top investment priority, yet only 37% of the employees who use AI most heavily reported increased access to that training. Organisations are talking about upskilling while systematically under-delivering it.
BCG’s research offers a useful corrective. Their data shows that organisations that put at least 10% of their AI budget into training and change management were one-and-a-half times more likely to succeed than those that did not. BCG’s broader 10/20/70 framework – 10% on algorithms, 20% on technology and data infrastructure, and 70% on people and processes – has become the most-cited allocation model in enterprise AI strategy for good reason. Most organisations are doing roughly the inverse.
What Separates the 11% That Are Succeeding
Kyndryl’s research identifies a group it calls Pacesetters – the organisations that are closing the gap between AI investment and business outcomes. What distinguishes them is not better models or bigger budgets. They are redesigning work around AI, investing in workforce development, implementing structured change management, and building governance frameworks that help employees trust the tools enough to actually use them.
That last point matters more than most technical programmes account for. Trust is not a feature you can configure. It is built through transparency about how AI decisions are made, clarity about what AI does and does not replace, and consistent communication from leaders who are themselves visible and confident in the transition.
Pacesetters are not waiting for adoption to happen organically. They are engineering it deliberately.
What This Means for IT Leaders Right Now
If you are a CIO or CTO with AI tools already in deployment, here are the three most important questions to pressure-test your current approach:
1. Do your people understand the “why” before the “how”?
Technology rollouts that skip the narrative – why this tool, why now, what changes, what does not – generate resistance that no training programme can fix retroactively. Communication must lead, not follow.
2. Is change management a line item or an afterthought?
If your AI budget allocation does not explicitly fund change management, training, and adoption support, you are building a case study in wasted spend. The BCG evidence is clear: the people investment is where the ROI lives.
3. Are your leaders equipped to lead AI-enabled teams?
With only 3% of organisations reporting leadership readiness, the odds are that yours need support too. Middle managers and team leads are the primary trust-builders at the point of adoption. Equipping them is not optional.
The Technology Was Never the Hard Part
AI tools in 2026 are more capable, more accessible, and better integrated than at any point in the technology’s history. The barriers to deployment have largely been solved. The barriers to value have not – and they are human ones.
Organisations that treat people readiness as a downstream concern – something to handle after the rollout – are consistently the ones reporting low adoption, frustrated teams, and AI spend they cannot justify to the board. The ones succeeding are treating the human challenge as the primary design constraint from day one.
At Insentra, we work with organisations navigating exactly this challenge – helping bridge the gap between AI investment and real, measurable outcomes by putting people at the centre of every AI transformation.
If your organisation has the tools but not the traction, it is time to shift focus. Explore Insentra’s AI practice hub at AI Momentum to find out how we help organisations build the people readiness that turns AI spend into AI value.
