Turning Goals Into Action: Implementation Intentions

People can understand a change, agree that it is useful and still return to the old way of working when pressure hits. In this episode, I explore how implementation intentions—a simple when–then planning strategy—can make new workplace behaviours easier to remember and act on.

Why understanding does not always lead to action

When people are asked to use a new tool or process, they are not choosing between the old and new ways of working in a calm, empty room.

They are usually busy. The old way is already familiar, while the new behaviour has to be remembered, interpreted and fitted into the work. So people often fall back into the existing pattern.

This is one reason software rollouts struggle to deliver the expected return, even when people have attended the training and understand how the technology works.

What is an implementation intention?

An implementation intention is simply a when–then plan:

When this situation happens, I will take this specific action.

A vague intention might say:

I will use AI more.

A more useful version would be:

When a new regulatory update arrives, the policy owner will use AI to compare it with the current policy and identify sections that may need review. They will then check the suggestions against the source regulation before escalating anything to the accountable subject matter expert.

The second version defines the trigger, the action, the owner and the point where human judgement is required.

Peter Gollwitzer’s research on implementation intentions shows that people are more likely to follow through when they connect a future situation to a specific action. The plan does not make the task magically easy. It reduces the amount of deciding required when the moment arrives.

The question many adoption programmes miss

AI and technology adoption programmes often create good intentions.

The launch creates awareness. Training builds understanding. Leadership messages create permission. Case studies make the technology feel relevant.

All of that matters. But programmes can still miss a small question that changes the outcome:

When exactly should this new action happen within the work?

“Use AI to improve productivity” gives people very little to work with on a busy Tuesday.

A clearer prompt might say:

When a proposal is requested, use AI to find three successful proposals for a similar client and prepare a first draft. The account owner then rewrites the sections that depend on relationship context the AI does not have.

This specificity helps move AI from occasional experimentation towards genuine adoption within the workflow.

Three practical questions

When translating a goal into workplace behaviour, ask:

What is the exact behaviour?
What will someone actually do?
When should it happen?
What situation, task or event will trigger it?
What prompt will make it visible at that moment?
Could it appear in a checklist, template, manager conversation or system notification?

Implementation intentions will not fix poor tools, weak leadership, bad incentives or processes that make the new behaviour harder than the old one. Those wider barriers still need to be diagnosed.

But when the behaviour is worthwhile and the challenge is follow-through, a when–then plan can make it far more actionable.

If you cannot write the behaviour as a when–then statement, it is probably still too vague.

Explore how Blue Jay Learning uses behavioural science to design learning that changes what people actually do.