Leading with Intelligence: A guide to successful AI adoption in the workplace

AI adoption is accelerating, but impact is lagging. 59% of companies using AI are struggling to integrate it into everyday work (Bain & Company, 2025). The challenge isn’t access to tools. It’s how people across organisations use AI, question it, and learn from it over time.

In practice, many teams fall into one of two traps: some over-trust AI outputs, whilst others hesitate to experiment at all. Both slow progress and introduce risk.

That risk is already visible. 66% of employees now rely on AI outputs without checking accuracy (KPMG, 2025). At the same time, organisations that delay hands-on learning are watching competitors move ahead while internal debates continue.

Our new whitepaper, Leading with Intelligence, looks beyond tools and prompts to ask a more important question: what human capabilities enable AI to create value at work?

Rather than positioning this as a leadership-only challenge, the research shows these capabilities matter across every layer of the organisation. Leaders play a critical role in reinforcing and role-modelling them, but they are skills everyone needs as AI reshapes how work gets done.

What really drives successful AI adoption at work

The whitepaper identifies four human capabilities that consistently show up in organisations making real progress with AI.

1. Curiosity

Not surface-level curiosity or one-off experimentation. This is about going deeper. Teams that get value from AI ask better questions, explore how AI changes the work itself, and invest time in understanding both its strengths and limits.

2. Discernment

AI can generate answers quickly, but speed does not equal quality. Discernment is about applying judgment and critical thinking, knowing when to trust outputs and when to challenge them.

3. Humility

AI increases speed and scale, placing pressure on traditional control models. No one, regardless of role or experience, can hold all the expertise. Progress depends on being comfortable learning, adapting, and sharing judgment across people and systems.

4. Connection

AI can boost individual productivity, but its value stalls when learning stays local. Around 33% of work hours still rely on human judgment, empathy, and communication (McKinsey, 2025). Connection turns individual insight into collective progress and prevents productivity islands.

When organisations develop these capabilities, they see faster decision-making, stronger collaboration, and teams that continue to learn as AI evolves.

The full whitepaper goes deeper into:

• How these capabilities show up in real work

• Why organisations get stuck between experimentation and control

• Practical frameworks leaders and teams can apply immediately

Download Leading with Intelligence to explore the frameworks behind successful, human-centred AI adoption.