Three Mistakes That Derail AI Adoption

Here are the top three mistakes I see some organizations making while attempting to get AI adopted by their workers (later, we will also see more effective ways of doing so).

1. They just focus on providing a tool without also ensuring it gets used and used well.

2. They do not see supervisors (their buy-in and their leadership skills) as the #1 determinant of whether teams adopt new tools and processes.

3. They focus on using AI on a worker’s core tasks, forgetting about its ancillary ones (which are often better targets).

Let’s examine each point and provide examples and solutions.

1. Examples, examples, examples

We can divide the population into four types based on how eagerly they adopt a new tool or technology, such as AI:

• Alpha users: just give them the tool, and they will figure out how to use it.

• Early users: they need both a tool and relevant and concrete examples of how to use it.

• Late users: in addition to the above, they need to see other people like them to use the tool successfully.

• Resistant users: they won’t use the tool until forced to.

Unless you deliberately configured your hiring process to only target alpha or early users, your organization probably contains all four types.

Your AI adoption strategy should take this into account. Hence, it should not only make AI available to workers but should also give them relevant and concrete examples of how to use it, ideally in person by their direct supervisor or peers.

Note that it’s not enough to provide generic training – such as “how to use this AI tool regardless of whether you’re a project manager, salesperson, or engineer.” People need relevant and concrete examples.

As a rule of thumb, if your training material could be given to multiple roles within your organization, it’s not relevant enough and won’t drive the adoption of the new tool.ShareCopy

2. Get supervisor buy-in and train them on training others

People won’t change their ways just because their CEO asked them in a corporate-wide email. They need to see that their direct supervisor is actively committed to it, too.

If their supervisor doesn’t use AI, they won’t use it either.

If their supervisor doesn’t care daily about whether they use AI, they won’t care either.

Supervisors are the lynchpin of any tool or process adoption strategy.ShareCopy

You must work closely and frequently with them to ensure they are committed and transform this commitment into visible yet genuine actions – such as using AI themselves or coaching individuals into integrating AI into one of their sub-tasks (more on this in the next point).