Something unexpected happens when you put people in a room to learn artificial intelligence (AI) skills together. They stop being passive recipients of content and start solving real problems.

This pattern has emerged consistently across industries, geographies and seniority levels, and I think it points to something missing in the global AI skills conversation.

Many industries have invested heavily in AI platforms, certifications and self-directed learning tools. These tools have a role, but they’re not closing the gap on AI skills.

What’s holding most people back from AI is simply the confidence to start using AI.

Building AI skills – and confidence

That’s just one of the lessons we’ve learned after presenting Cognizant’s AI for Impact Community Labs programme across the ASEAN region.

The programme brings together nonprofit staff, mid-career professionals and senior leadership teams for structured, in-person AI skills workshops. Trained facilitators guide participants through progressive prompt engineering frameworks, while volunteer mentors sit at every table to help attendees apply new skills to their own real work challenges. The format is deliberately tool-agnostic, with participants using whatever AI products they already have access to.

Sessions close with a structured activity in which each group identifies a specific challenge, opportunity or workflow in their organization and collaborates to design a solution that brings out the best of people and AI working together.

After 2.5 years of AI for Impact delivery, including the Community Labs series launched in early 2026, the results are consistent enough to draw some clear conclusions:

1. The AI barrier is skills and the confidence to apply it

Across every cohort we have worked with, there is a consistent pattern: No matter their seniority, sector or background, most participants arrive believing they cannot prompt well.

People have access to the tools. What they lack is the ability to structure their thinking to get the best out of AI. This includes directors, heads of function, transformation leads and senior leaders with decades of expertise.

Their challenge with AI begins with confidence. A platform can present content, track completion and issue a certificate. What it cannot do is something more human, which is convincing people they already know how to think, and explaining how to apply that to AI.

2. A single session can produce a measurable AI skills lift

Across every cohort measured, average prompting ability rises by more than one full point on a five-point scale in a single AI skills session.

In one senior leadership cohort at a global pharmaceutical company, prompting ability rose from 2.67 to 4.07 over one session. And 100% of participants rated themselves at 4 or above in terms of AI prompting skills afterwards.

Among a broader nonprofit cohort of 103 participants, 95% said they expect to save 30 or more minutes a day with generative AI following a training session.

3. Groups unlock AI use cases that individuals can’t find alone

My favourite moments in AI workshops come when people at a table start talking to each other. A fundraising manager hears how a colleague uses AI to draft reports and immediately sees an application for grant writing. Or a clinical educator hears a peer describe AI-assisted scenario planning and recognizes a fit for simulation training.

In one session with 37 non-profit organizations, groups generated use cases spanning donor fundraising strategies, multilingual chatbots for seniors, board paper preparation, volunteer event management and clinical training materials – all within a few hours.

Nearly every participant agreed that group work helped them recognize the importance of human skills like ideation, collaboration and critical thinking. Connections like these don’t happen in isolation.

4. Demand for AI skills says something important

Human-led AI workshops fill faster than they can be run. One of our sessions designed for 73 participants received more than 200 registrations from more than 40 organizations before we had to close the list.

What’s equally striking is who is registering. Senior leadership teams from global organizations – who already have enterprise licenses for every major AI platform on the market – are choosing to attend these volunteer-facilitated workshops. When asked why, they consistently say something along these lines: Platforms tell me what AI can do, but they don’t help me figure out what I should do with it in my specific role, in my specific organization, right now.

Across a sample of 40 senior leadership registrations, lack of skills and talent was cited 28 times as a barrier to AI adoption, outranking unclear use cases, data security concerns, compliance and cost.

5. Learners become teachers

Participants often say their first planned action after a workshop will be to pass along their new AI skills to their teams. When senior leaders leave the room, many are already planning internal sessions for their functions. Frontline workers almost universally say they will share what they learned with colleagues who could not attend.

Our volunteer mentors themselves illustrate this dynamic. Across 43 volunteer responses, average AI confidence rose from 3.45 to 4.40 (out of 5) through the act of volunteering alone. And 91% said mentoring increased their own understanding of generative AI.

Teaching accelerates learning. Organizations that provide AI skills mentors should view this as a capability-building investment.

Turning AI content into capabilities

The world has no shortage of AI content. The real challenge is building the human infrastructure to turn that content into capabilities.

This requires confidence, and confidence scales through people – the colleague who sits with you and works through a real problem, the mentor who recognizes your hesitation and names it or the the room of people that remind you that everyone else is figuring this out too.

The organizations that will move fastest to develop AI skills are those investing in the humans who can bring others closer to understanding, applying and eventually shaping how AI works in their specific context. This means creating the conditions for peer learning, recognizing mentors as capability builders and trusting that when humans and AI work well together, it produces something neither could reach alone.

The most important moment in any AI skills journey is the conversation that makes someone believe they belong in this future.

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