AI is everywhere, but most organisations are finding it’s not delivering promised value. And as with most technology trends, we must ask: Are we forgetting the humans?
Digital transformation is no longer seen as revolutionary – it’s become part of business as usual. Its organisational role has shifted too – for years ‘digital leadership’, ‘digital behaviours’, ‘digital ways of working’ were shorthand for being fit for the future, yet today this framing is almost anachronistic.
Gate One’s recent Transformation Index shows almost 30% of the C-suite now see transformation as continuous change at scale, reinforcing the shift away from digital as a primary force of disruption.
AI is different – its revolutionary credentials are unquestionable. AI is on every transformation roadmap, mentioned in every executive conversation, and found within every strategy. The relentless pace of innovation and fear of falling behind puts pressure on organisations to adopt AI solutions, even before understanding where value can be created. In the same Transformation Index, almost one-third of C-suite leaders cite AI advancing faster than they can keep up as their top strategic challenge.
Yet paradoxically, AI has not delivered its promised value. Too many projects stall before they start. Others remain underused. A 2025 report by MIT found that 95% of gen AI programmes fail to deliver business value, with only 5% progressing successfully from pilot to production1. There are indications that employee AI adoption tends to plateau, before productivity gains are realised, with some placing this at around 10%, even in early adopter or high-tech sectors. Most AI programmes are not (yet) delivering business outcomes and value – our Transformation Index found that 64% say demonstrating impact is a major challenge.
So, what’s getting in the way?
It’s not tech, it’s people. Organisations depend on their people – employees across roles, teams, processes and functions – to identify and unlock the value of AI.
This is not just about individuals using AI, its about employees identifying where AI can create breakthrough gains – in productivity, in growth, in insight.
Despite best intentions, most organisations treat AI as the latest in a long line of technology to adopt. And, even those who practice employee-centric engagement and adoption, tend to swerve the underlying human tension that AI introduces.
We frequently hear how AI triggers anxiety amongst employees, worry about job cuts, mistrust of the tools, or existential fear for the future. The social and psychological burden around AI is high, and employee upskilling and increased use doesn’t fully extinguish them.
On top of this, AI is entering the workplace at a moment when employee resilience is low and overwhelm is high. Our Transformation Index found 63% of leaders say their employees are fatigued by continual change.
1. Behavioural: Resistance to change.
Even when AI promises efficiency or innovation, individuals may resist adopting new tools or workflows. This resistance often stems from:
- Fear of job displacement or reduced personal relevance.
- Lack of understanding of how AI works or how it benefits them.
- Comfort with existing processes, especially if they’ve been successful in the past.
2. Psychological: Lack of trust and confidence.
AI systems can feel like black boxes. If people don’t trust the outputs or feel confident using them, adoption stalls. This is particularly true in high-stakes environments like financial services.
- Low trust in AI decisions, especially if they’re opaque or inconsistent.
- Anxiety about making mistakes when using AI tools.
- Cognitive overload from too many new systems or interfaces.
3. Cultural: Misalignment with team norms.
AI adoption often clashes with how teams work and what they value. For example:
- Top-down mandates without team buy-in.
- Lack of cross-functional collaboration between tech and business teams.
- Inflexible cultures that don’t reward experimentation or learning.
So, how do we build better collaboration?
AI must move from being a technical tool to a trusted team member. That means rethinking not just culture, but behaviour.
1. Focus on the behaviour, not just the culture
Culture shapes how people behave. Behaviour is the action.
To collaborate effectively with AI, build habits such as curiosity, questioning, and reflection into the daily workflows of your teams. The most effective teams treat the output from AI as a conversation starter.
To shift behaviour, your team needs space to reflect and question AI outputs.
Action tips:
- Train for human-AI interaction, not just AI literacy. Introduce short scenario-based sessions where employees can practice questioning an AI’s rationale, comparing human and AI conclusions, and reflecting on when to trust the system (and when to override it).
- Make space to pause, reflect and learn. We found that leading organisations use ‘pausing’ as a strategic level, deliberately stopping or slowing down work that is not delivering value. These reflective loops turn every AI interaction into a learning cycle. Use project reviews or mid-sprint retros to review how AI changed your decision-making, and what could be done differently next time.
2. Understand the psychology
People respond more effectively to AI agents that use natural language, as if they were colleagues. This humanises the tool, attributing authority, intelligence and intent, building trust and psychological safety. If not managed consciously, this can lead teams to over-trust the machine and under-value their own judgment.
Action tip: Ensure you build awareness into your AI workflow – encouraging your team to constantly question, interpret and validate. Prompts should position AI as a partner in thinking, not an oracle of truth.
3. Rebalance the creativity equation
AI is brilliant at pattern recognition and probability. But creativity is something that needs to come from people.
Outsourcing ideation to AI reduces our human skills of curiosity and imagination. The convenience of immediate answers can crowd out the messy, human process of exploration.
Action tip: Start with human exploration and brainstorming, and then use AI to expand, stress-test and refine ideas. In this model, creativity leads and AI amplifies. You want your team to set the direction, and let AI accelerate the journey.
Make AI work for your people
AI transformation must take a human-centric approach, putting your people at the heart of the adoption and experience. The potential is huge — but unlocking it means shifting the focus from technical deployment to collaborative adoption. When humans and machines work in sync, transformation sticks.
Looking to rethink your workforce strategies to thrive in an AI powered future?
Get in touch to find out how our human-centric approach helps you shape your strategic business decisions to harnessing the power of tech.
