The 5 behaviours required for AI adoption

According to the RAND corporation, organisations spent approximately $685bn on AI initiatives in 2025 and found that 80% failed to realise the expected value from them.

Microsoft meanwhile found that the single biggest predictor of AI adoption isn't the technology itself, it's manager role-modelling and whether the culture has the collective behaviours to get the most from it.

As someone who helps organisations to build 'AI-ready' cultures, here are five key behaviours from my work to help you realise value from your own AI investment:

Curiosity over compliance

PwC found that organisations leading on AI adoption fostered curiosity, experimentation and exploration - a culture decision not a procurement one. Meanwhile, research from Manpower Group shows nearly two-thirds of workers report burnout from stress and heavy workloads. Burnt-out people don't experiment - they just try to survive. Leaders who want curious teams have to stop filling every hour of the working week and wondering why nobody is innovating. 

Psychological safety

Research from Henley Business School found 61% of workers feel overwhelmed by AI's development, with nearly a quarter saying their employer isn't providing enough support. A Culture Amp study found 29% admit using AI without telling their manager. Whilst MIT Sloan found managers who lead by example are 3.4x as likely to boost regular AI use in their teams. The most powerful thing a leader can say right now is: 'I'm still figuring this out too.'  

Continuous learning as identity, not event

The World Economic Forum's Future of Jobs Report estimates 59% of workers will need soft skills training by 2030. Yet employers spent $103bn on training in 2025, with only 27% going towards soft skills. The fastest-adapting organisations won't necessarily have the biggest budgets - they'll have learning embedded in daily behaviour, not bolted on as a ‘technology learning event’. 

A willingness to let go

Many people have spent years developing skills that AI now does faster. The WEF notes nearly 40% of existing job skills will change (though there's plenty of argument around this), with AI literacy and adaptive thinking replacing routine tasks. Those who transition well are the ones prepared to let go of what they do now and grab onto what's new. 

Collaboration across boundaries

The most common AI challenge is cultural silos - inconsistent experiences and the same problems solved separately, repeatedly. MIT Sloan highlights that embedding ‘business translators’ - between teams - drives better AI adoption. Reorganisations don't fix silos; they redraw them. What's required is a willingness to share information, failure, credit and uncertainty across org chart boundaries. 

The data is unequivocal, cultural readiness is the critical factor in how organisations respond to AI; and it’s not just about individual behaviour. It’s collective.