For a long time, technical capability was a barrier to progress.

An idea could only go so far without access to people who knew how to build, analyze, design, or communicate it. Inside organizations, progress often depended on specialist teams, sufficient budgets, and available resources.

AI is changing that.

It gives more people access to capabilities they do not personally possess. We can enter unfamiliar territory, learn the basics, test an idea, create an initial version, and work through problems as they arise.

This does not make everyone an expert. Technical expertise still matters, particularly when work must be reliable, secure, or scalable. But AI allows us to make meaningful progress before that expertise is required.

AI does not remove the barriers to meaningful accomplishment. It moves them.

The old barrier was often access to technical capability. The emerging barrier is our capacity to use widely available capability well.

Can we identify a problem worth solving? Can we give clear direction? Can we assess work we did not personally produce? Can we recognize weak assumptions, involve the right people, and remain accountable for the result?

These are leadership questions.

Working with AI requires many of the same behaviours as leading through others. We must provide context, define the outcome, delegate work, review what comes back, and offer clear feedback.

Our AIR framework describes the leadership capacities this demands.

Awareness helps us understand ourselves and the situation. We need to recognize the assumptions, motivations, and expectations we bring to the work. We must notice when we are reacting to an output rather than evaluating it, and remain conscious of how our decisions may affect others. 

Influence is our ability to engage and collaborate with less resistance. Clear direction matters, but so do the relationships, processes, tone, and culture surrounding the work. AI may help produce an answer, but people still need to be engaged in shaping it, improving it, and moving it forward. 

Resilience allows us to remain effective as we manage pressure, changing information, and repeated revision. It requires us to prioritize wisely, recognize what is draining our effectiveness, and adjust our perspective and behaviour. 

AI can produce a polished result quickly. That makes it easy to become attached to the work before properly challenging it.

We need enough distance to ask what is missing, invite other perspectives, and change course when the work is not good enough. We also need to manage our own energy and attention so urgency and output do not crowd out judgment.

AI gives more of us the ability to direct capabilities beyond our own. With that ability comes responsibility: to understand the situation, engage others constructively, remain effective under pressure, and be accountable for the outcome.

That is why we are all leaders now.