Sometimes that means discovering that the data needed to support an AI solution isn't as complete or reliable as expected. It might lead to the identifying of gaps or weaknesses in existing processes. In many cases, it means recognising how staff will need to work differently or where additional oversight is required.
Looking beyond the technical outcome
Most AI pilots start with a specific objective. It might be reducing the time spent on repetitive administrative tasks, improving forecasting, speeding up customer service responses or helping staff find information more quickly.
Whether the pilot succeeds or fails, organisations usually learn something useful.
A pilot might confirm that an AI solution can deliver meaningful benefits. Equally, it might reveal issues that need to be addressed before moving further. Data may require cleaning. Existing processes may need to change. Staff may need additional training. Governance arrangements may need strengthening.
These are practical lessons that rarely emerge from planning discussions alone.
Importantly, they help organisations understand not just whether AI can work, but what is required to make it work in their environment.
Building confidence through experience
One of the less obvious benefits of a pilot is the confidence it can create across an organisation.
For many teams, a pilot is the first opportunity to use AI in the context of their day-to-day work. Staff gain a better understanding of what the technology does well and where human judgement remains important. Leaders gain experience making decisions about how AI should be used and monitored.
That practical experience helps move conversations beyond assumptions, hype and uncertainty.
It gives organisations something far more valuable: evidence from their own environment.
Rather than asking what AI might do, they can start making decisions based on what they have already observed and learned.
Deciding what comes next
As organisations move beyond their first pilots, the focus shifts from testing individual use cases to deciding where AI can deliver value across the organisation.
Answering that question requires more than enthusiasm for new technology. It requires clear priorities and a practical understanding of what has been learned along the way.
The 6 Essential Practices outlined in the Guidance for AI Adoption help organisations take a structured approach to adoption. Working through the practices can help identify where additional governance, oversight or support may be needed as AI use expands.
But successful AI adoption starts with people. Involving and supporting your team through change can help build confidence, encourage responsible use and improve the likelihood of long-term success. That means creating opportunities for people not just to explore AI, but to experience it in the context of their day-to-day work and help shape the outcomes.
What matters is that every pilot leaves the organisation better informed than when it started. The most valuable outcome is often not the technology itself, but a clearer understanding of where AI can create value, what challenges need to be addressed and what should happen next.
Lee Hickin
Executive Director, National AI Centre
