How AI is changing what each of us brings to the table.

Collaboration tools changed how teams worked together. AI is now changing what each person can bring into the work before the collaboration even begins.

I have spent years helping organizations change how work gets done.

Sometimes that meant introducing a new ERP or CRM. Other times it meant moving thousands of employees onto collaboration platforms like Google Workspace and Microsoft 365.

The technology changed, but the real work was always getting people, processes and culture to move with it.

Collaboration tools introduced the concept of Work Reimagined, shifting work from individual productivity toward shared work, making it easier for teams to create, solve problems and build together.

Now AI is pushing us into the next version.

And this time, the shift is not only about how we work together.

It is changing what each of us can bring to the table before the collaboration even begins.

What each person brings to the work is changing

AI can help someone get further on their own before they bring the work to the team.

They use it to sort through information, test an idea, improve a draft or think through a problem from a few different angles.

So when they show up to a meeting, they are more prepared. They have better questions. They already have a stronger starting point.

The team still matters. People still need to use judgment, challenge ideas and make decisions together.

But AI can help each person bring more into that conversation.

Are we using AI to rethink the work or just repeat it faster?

This is the question I think organizations need to spend much more time on.

Right now, many people are still using AI almost like a better Google search.

They have a task to complete. They pull up something from a previous project, give it to AI and ask it to help create the next version.

There is nothing wrong with that. It saves time.

But it is still largely the same work.

The real opportunity starts when people stop asking only, “How can AI help me do this?” and start asking, “Is this still the best way to do this?”

Instead of taking the process we already have and making it faster, where could we remove a step completely?

Where could AI help us see something we were not able to see before?

Where could an employee spend less time producing the work and more time thinking about the quality of it?

And where could we create something better rather than simply recreating what worked on the last project?

That requires more than access to a tool.

It requires people to understand the work well enough to question it.

And it requires leaders to give them enough room to do that.

The value is in what happens next

Giving people access to AI creates possibility. It does not automatically create value for the organization.

The real opportunity comes when you start paying attention to what people are learning through their own use.

Individual wins are useful. But if they stay with the individual, that is where the value stops.

The next step is to ask what is worth sharing, what could become part of the way the team works, and what might point to a process that needs to be redesigned altogether.

This is where I think organizations need to be careful about trying to manage AI entirely from the centre.

IT can choose the tools. The organization can set rules for security, privacy and responsible use. Leaders can set the direction.

But the people doing the work are often going to see the opportunity first.

The job is to create a way for those ideas to surface, be tested and, when they work, spread beyond the person who discovered them.

McKinsey’s 2025 State of AI research found that redesigning workflows had the largest effect of the 25 organizational factors it tested on whether companies reported EBIT impact from generative AI. Yet only 21 percent of respondents using generative AI said their organizations had fundamentally redesigned at least some workflows.

That is an important distinction.

A person finding a faster way to do a task is useful.

A team changing how that work gets done is transformation.

People need room to keep learning

This next version of work will not come from one training session.

AI changes too quickly for employees to learn a tool once and consider the job done. New capabilities appear, tools improve and the way people can use them keeps changing.

So the question cannot simply be:

“Have our employees been trained?”

It has to become:

“Can our people keep learning as the technology changes?”

And that is not only a learning issue.

It is a leadership issue.

For years, we have talked about trust, transparency, psychological safety, empowerment and giving people room to innovate.

And yet I still see leaders operating through micromanagement, limited transparency and a reluctance to give people real space to make decisions.

Employees are told to innovate and take risks.

Then every decision is questioned. Every mistake is scrutinized. Every new idea has to move through layers of approval.

People quickly learn that it is safer to wait for direction.

That becomes a much bigger problem in the era of AI.

You cannot ask employees to experiment, rethink how work gets done and surface better ideas if the culture still punishes uncertainty.

Leaders need to be willing to learn openly, admit what they do not know and give people enough trust to test, learn and adjust.

If employees believe every AI mistake will be judged, they will not experiment.

And if managers cannot talk openly about how roles may change, what people are worried about or what is still uncertain, employees will fill in the blanks themselves.

This is where leadership communication matters.

Not another polished announcement about “embracing AI.”

People need leaders who can explain what the organization is trying to achieve, what is changing, what is still being figured out and where the boundaries are.

They also need leaders who listen.

Because the person closest to the work may see the AI opportunity before the leader does.

What should leaders be looking for?

The goal is to create the conditions where people can use AI to improve work, learn from one another and turn individual gains into something the wider organization can benefit from.

If you are leading a team, start by looking at what is actually happening around you.

Ask:

• Where is AI already making the work better, not just faster?
• What have people figured out that the rest of the team could learn from?
• Where are we taking an old process and simply using AI to repeat it faster?
• What could we stop doing, simplify or rethink completely?
• Where are people holding back because they need more skill, clearer boundaries or greater trust?
• Are leaders giving people enough room to experiment and learn?
• What needs to move from individual success to a team practice?

These are the questions that move the conversation from AI access to work reimagined.

This next version of work asks organizations to do more than introduce another tool.

It asks them to pay attention to what people are discovering, give them room to challenge how work has always been done, and build on what is actually working.

That is how the value moves beyond the individual and into the organization.

Not sure where your organization stands?

Before deciding what comes next, it helps to understand where your organization is today.

I work with organizations to assess the people-side of AI readiness, including leadership, trust, culture, communication and the conditions employees need to adopt new ways of working.

The assessment gives leaders a clearer picture of what is already working, where adoption may be getting stuck and what needs attention before pushing further investment or another rollout.

[CTA: Learn more about an AI Change Readiness Assessment]