35. Project Management Trends 2026 | The Strategic Value of AI Beyond Productivity

Artificial intelligence has become one of the biggest conversations in project management. Much of that conversation has focused on productivity: summarizing meetings, drafting communications, identifying risks, analyzing data, and automating routine tasks.

But the value of AI extends beyond productivity.

In this episode of Project Management Masterclass, we begin our Project Management Trends 2026 series by examining the strategic value of artificial intelligence and what it means for project leaders.

We explore how AI connects to corporate strategy and business value, what the changing demand for AI skills signals about the future of work, and why governance must become part of the conversation as organizations expand their use of AI.

Because adopting AI is only part of the challenge. Organizations must also understand where AI is being used, what risks it introduces, who owns the decisions, and whether those investments are actually delivering value.

For project managers, the opportunity is bigger than learning another tool. It's understanding how AI, strategy, governance, risk, and execution come together to deliver successful outcomes.

The technology may be changing, but the fundamentals of strong project leadership still matter.

If you are ready to strengthen the skills that separate project managers from project leaders, explore the Power Skills Accelerator, a course designed to help professionals master the leadership capabilities needed to thrive in complex project environments.

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If you want to assess where execution may be breaking down in your current projects, take the Execution Intelligence Diagnostic to identify gaps across leadership, decision making, and team alignment.

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Join the waitlist for Brittany Wilkins’ upcoming book, Execution Intelligence, focused on the mindset, systems, and discipline required to turn strategy into measurable results.

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To learn more about how organizations eliminate execution friction and turn strategy into measurable results, visit Makoway Consulting.

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Transcript

Welcome back to Project Management Masterclass, where we help you master the fundamentals of project management, transform the way you lead projects, and stay informed about the trends shaping the future of our profession. I'm your host, Brittany Wilkins.

Let me ask you a question.

What trends are shaping the way projects are delivered today?

Whether you're leading projects, managing portfolios, or overseeing organizational change, the environment around you continues to evolve.

New technologies emerge.

Expectations shift.

Teams work differently.

And even the way project success is defined continues to change.

With everything on your plate as a project manager, it's easy to keep your head down.

You're focused on the next meeting.

The next deadline.

The next issue that needs your attention.

The stakeholder who's waiting on an answer.

And getting the next deliverable across the finish line.

Before you know it, weeks turn into months, and you rarely stop to ask:

What's changing around me?

But every once in a while, I think it's important to look up from the project plan and pay attention to what's happening around our profession.

Because the forces shaping business eventually shape projects.

And the forces shaping projects eventually change what's expected of you as a project leader.

That's what I want to spend some time exploring over the next several episodes of Project Management Masterclass.

A while ago, I attended a webinar hosted by a leading project portfolio management software provider and one of its strategic partners.

They identified several trends they believed would influence project management in 2026.

Then, last month, I attended their mid-year discussion where they revisited those trends and talked about what they were seeing across organizations.

As I listened, I found myself doing what I often do.

I started connecting what they were saying with other things I've been reading, conversations I've been having, projects I've led throughout my career, and broader changes happening across business.

And the more I thought about these trends, the more I realized that this shouldn't be one episode where I quickly give you five bullet points.

Some of these conversations deserve more room than that.

So I'm turning this into a series.

We'll take the trends one at a time, unpack them, and most importantly ask:

What does this mean for you as a project manager or project leader?

Today we're starting with the first trend.

The value of artificial intelligence.

And before you think this is going to be another episode about writing prompts or having AI create your meeting notes for you, stay with me.

Because that's where the conversation starts.

But it's not where we're going to finish.

AI AS A PRODUCTIVITY TOOL

If there is one topic that has dominated business conversations over the past few years, it's artificial intelligence.

You see it at conferences.

You see it in webinars.

You see it in software demonstrations.

You see it in your LinkedIn feed.

And if you're a project manager, you've probably heard some version of the same message.

Artificial intelligence can help you summarize meeting notes.

It can draft stakeholder communications.

It can help generate status reports.

It can analyze large amounts of project information.

It can help identify risks.

It can assist with schedules.

It can automate repetitive tasks.

And yes, all of that has value.

I don't want to dismiss the productivity side of artificial intelligence because productivity matters.

If you spend thirty minutes cleaning up meeting notes and AI helps you do it in five, that's useful.

If you have to synthesize information from several reports and AI helps you find patterns faster, that's useful.

If it helps you create the first draft of a communication so you can spend more time thinking about the message instead of staring at a blank screen, that's useful.

Project managers carry a significant administrative load.

So if technology can reduce some of that burden, I'm all for it.

Because ideally that gives you more time for the things technology cannot easily replace.

Leading people.

Building relationships.

Talking with stakeholders.

Solving difficult problems.

Making decisions.

Working through ambiguity.

Understanding what isn't being said in a meeting.

Helping a team get unstuck.

Those things still matter.

But here's where this trend became more interesting to me.

When I looked at the webinar material, the trend wasn't called:

The productivity of AI.

It was about the value of AI.

And that word—value—changes the conversation.

Because productivity is one form of value.

It isn't the only one.

So instead of asking:

How can AI make me more productive as a project manager?

I think we need to start asking a much bigger question.

Why is my organization investing in artificial intelligence in the first place?

That's when you move from thinking tactically to thinking strategically.

AI AND CORPORATE STRATEGY

Artificial intelligence is not the strategy.

Let me say that again.

Artificial intelligence is not the strategy.

It is a capability organizations are investing in because they believe it can help them execute their strategy more effectively.

There is a difference.

Think about what executive leadership teams are responsible for.

They're trying to grow revenue.

Control costs.

Improve margins.

Increase productivity.

Create better customer experiences.

Innovate faster.

Protect market position.

Enter new markets.

Develop new products.

Build resilience.

Allocate capital.

Develop talent.

Artificial intelligence can potentially influence every one of those conversations.

So when an organization announces a major AI initiative, the most important question isn't necessarily:

What AI platform are we using?

The more important question is:

What are we trying to accomplish as a business?

That question matters for project managers because every project should exist for a reason.

Somewhere, somehow, the project you're managing should connect to an organizational objective.

And AI projects are no different.

If your organization is investing millions of dollars—or in some cases billions—into artificial intelligence, you should be asking:

What strategic objective is this investment supporting?

Are we trying to reduce operating costs?

Are we trying to increase sales?

Are we trying to improve customer retention?

Are we trying to reduce product development cycle time?

Are we trying to improve quality?

Are we trying to create an entirely new business model?

Because once you know the answer, the project looks different.

You're not just deploying software.

You're building capability.

You're executing strategy.

And that distinction affects the decisions you make throughout the project.

What gets prioritized.

What gets measured.

Who needs to be involved.

What risks matter.

What success actually looks like.

A project could technically launch an AI solution on time and on budget and still fail if it doesn't create the business outcome the organization invested in it to achieve.

That's why I think project managers have to understand the strategy behind the project.

You don't need to sit in the CEO's chair.

But you should understand what the CEO is trying to accomplish.

THE MARKET IS ALREADY SENDING A SIGNAL

Around the same time I was thinking about this, I came across an article with a headline that caught my attention.

The headline suggested that AI skills could become more valuable than an MBA.

Now, headlines are designed to get your attention.

And that one certainly did.

But rather than stop at the headline, I looked at the research behind the broader conversation.

PwC's 2026 Global AI Jobs Barometer analyzed more than one billion job advertisements across six continents. PwC found that jobs requiring specific AI skills were growing substantially faster than the overall job market and that workers with AI skills were commanding an average wage premium of 62 percent. (PwC)

But another finding caught my attention even more.

In U.S. data, PwC found that AI-exposed entry-level positions were significantly more likely to require skills traditionally associated with more senior roles—things like judgment and leadership. (PwC)

Think about that.

The technology is becoming more capable.

But instead of making human judgment irrelevant, in many roles the market is placing more emphasis on it.

That's important.

Because when people hear "AI skills," they sometimes immediately think:

Prompt engineering.

Learning ChatGPT.

Learning Copilot.

Learning Claude.

Learning Gemini.

Knowing the latest application.

Those things may help.

But I think we're thinking too narrowly if that's where we stop.

The market isn't just going to reward someone because they know where the AI button is.

The higher-value skill is going to be knowing what to do with the capability.

Can you take an AI capability and connect it to a business problem?

Can you exercise judgment?

Can you determine when an AI recommendation doesn't make sense?

Can you lead people through the change?

Can you ask better questions?

Can you understand the consequences of a decision?

Can you connect technology to strategy?

That's a very different skill set.

So I don't think the takeaway for project managers is:

Go become an AI engineer.

The takeaway is:

Become AI literate enough to lead in an AI-enabled organization.

Understand what the technology can do.

Understand what it cannot do.

Understand where it creates value.

Understand where it introduces risk.

And understand how it fits into the broader business.

Because that's where this conversation takes another turn.

If organizations are rapidly integrating AI into their strategy...

Who is governing it?

THE GOVERNANCE QUESTION

A few days after the project management webinar, I attended another presentation.

Completely different setting.

Completely different emphasis.

This presenter wasn't talking about better prompts.

He wasn't teaching people how to automate their email.

He wasn't telling us about the newest AI application.

He was talking about AI governance and risk.

And one of the ideas from that presentation stayed with me.

Many organizations know they're using AI.

But they may not actually know everywhere AI is being used inside the organization.

That's a very different problem.

Think about your own organization.

Your company may officially license Microsoft Copilot.

Great.

But what about the employee using another public AI tool?

What about AI capabilities embedded inside software your team already uses?

What about the vendor who has incorporated AI into its product?

What about the engineering team experimenting with an AI agent?

What about marketing?

Finance?

Human resources?

Operations?

AI can spread through an organization much faster than governance structures can catch up.

And one of the ideas presented was straightforward:

Build an inventory.

Understand where AI touches the business.

Understand what those systems can access.

Understand who owns them.

Understand what risks they introduce.

Then decide what level of risk the organization is prepared to accept.

There was one statement in that presentation that I wrote down because it applies far beyond AI:

Accepted risk is fine. Unseen risk is what gets you.

That is a project management lesson.

Think about your risk register.

The reason you identify risk isn't because you believe you can eliminate every risk from a project.

You can't.

The purpose is visibility.

You identify the risk.

You assess it.

You determine likelihood and impact.

You decide how you're going to respond.

Maybe you mitigate it.

Maybe you transfer it.

Maybe you avoid it.

Maybe you accept it.

But at least somebody knows it exists.

Unseen risk is different.

You can't manage what you don't know is happening.

And that is why I think governance is going to become a much bigger part of the AI conversation.

Who owns AI governance?

Who determines which applications are approved?

What data can employees put into those systems?

What information should never leave the organization?

Who monitors compliance?

Who determines whether an AI model is appropriate for a particular decision?

What happens when AI produces inaccurate information?

What happens when an employee relies on AI-generated information without validating it?

Who is accountable?

Where does Legal enter the conversation?

Where does IT enter?

Cybersecurity?

HR?

Operations?

The PMO?

Executive leadership?

Those are not just technical questions.

They are organizational design questions.

They are decision-right questions.

They are accountability questions.

They are governance questions.

And project managers understand governance.

At least—we should.

Who makes the decision?

Who needs to be consulted?

Who owns the risk?

What is the escalation path?

What are the boundaries?

What does success look like?

AI changes the technology.

It doesn't eliminate the need for those fundamentals.

If anything, it makes them more important.

AI DOES NOT EXIST IN ISOLATION

There's another reason I want you to think about AI beyond productivity.

If you listened to the previous episode of Project Management Masterclass, we talked about Scope 2 emissions and how the energy landscape is changing.

At first glance, Scope 2 emissions and artificial intelligence sound like two completely unrelated topics.

But take another look.

AI doesn't exist in the cloud in some magical, invisible place.

There is physical infrastructure underneath it.

Data centers.

Servers.

Cooling systems.

Power generation.

Transmission.

Substations.

Backup generation.

Energy storage.

Maintenance.

An entire physical system supports the digital capability.

And the rapid expansion of AI is contributing to growing electricity demand from data centers.

So now think from the perspective of corporate strategy.

An organization may have one strategic objective that says:

Accelerate the adoption of artificial intelligence.

At the same time, another strategic objective may say:

Reduce greenhouse gas emissions.

Both can be legitimate priorities.

Both can create value.

And yet the execution of one may create new challenges for the other.

That's where strategic execution becomes complicated.

Organizations don't execute one objective at a time in isolation.

They may have dozens of strategic initiatives interacting simultaneously.

AI.

Sustainability.

Cybersecurity.

Digital transformation.

Talent.

Growth.

Operational efficiency.

Resilience.

Capital projects.

And somebody has to connect the dots.

That's one of the reasons I keep pushing project managers to look beyond their individual project.

Your project sits inside a system.

And decisions made in one part of the system can create consequences somewhere else.

So if you're managing an AI initiative, don't just ask:

What does the software do?

Ask:

What business strategy does it support?

What infrastructure does it depend on?

What risks does it create?

What other strategic objectives could it affect?

Who governs it?

How will we know whether it created value?

Those questions elevate you from managing activity to understanding execution.

SO WHAT SHOULD PROJECT MANAGERS DO?

I don't want you to finish this episode thinking you need to run out and become an AI expert overnight.

That's not the message.

I would start with five questions.

The next time artificial intelligence enters a conversation around one of your projects, ask yourself:

Number one: What business problem are we actually trying to solve?

Not:

Where can we insert AI?

What problem exists?

Start there.

Number two: How does this initiative support organizational strategy?

If nobody can explain the connection, you may have a technology experiment rather than a strategic initiative.

And that's okay—as long as everyone understands that's what it is.

Number three: How are we defining value?

Time saved?

Revenue generated?

Cost avoided?

Customer satisfaction?

Quality?

Cycle time?

Risk reduction?

You can't prove ROI if nobody defined what value meant in the first place.

Number four: What new risks does this capability introduce?

Data.

Security.

Accuracy.

Bias.

Dependency.

Governance.

Compliance.

Reputation.

Don't wait until implementation to ask.

And finally:

Who owns the decisions?

Who has authority?

Who approves the use case?

Who owns the outcome?

Who accepts the risk?

Who shuts it down if something goes wrong?

That is governance.

And governance should not be an afterthought.

CLOSING

When I first started thinking about this trend, I thought the story was straightforward.

AI was changing project management.

And yes—it is.

It can make you faster.

It can automate administrative work.

It can help you analyze information.

It can change how projects are planned and delivered.

But the more I thought about it, the more I realized that's only the surface.

The bigger story is that artificial intelligence is forcing organizations to rethink how they execute strategy.

Where they invest.

What capabilities they build.

How they structure work.

What skills they value.

How they manage risk.

How they govern technology.

And how they define value.

That's why I think the conversation for project managers has to mature beyond:

What prompt should I use?

The better question is:

How does this capability help my organization execute its strategy—and what needs to be true for us to realize that value responsibly?

Artificial intelligence isn't the strategy.

It's a capability organizations are investing in to execute strategy more effectively.

And the project managers who become more valuable in this next era won't simply be the ones who know how to use AI.

Until then, continue mastering the fundamentals, continue transforming the way you lead projects, and stay curious about what's shaping the future of our profession.