Artificial Intelligence is everywhere.
Every day, we're told that AI will transform business, automate work, and redefine how organizations operate. Some predictions are exciting. Others are alarming. Many are exaggerated.
For project and program leaders, the real question isn't whether AI will change how we work, the question is:
How can we use AI responsibly to improve organizational outcomes without sacrificing critical thinking, leadership, and sound decision-making?
After working with project teams, leaders, and organizations across all sorts of industries, I've come to a simple conclusion:
Generative AI is not a replacement for strong thinking. It is a tool that can help thoughtful professionals think better, work faster, and make more informed decisions; provided they don't take shortcuts.
The organizations realizing the greatest value from AI are not replacing people. They are empowering people to use it as a tool to accelerate their productivity and have more time to leverage their judgement.
The Evidence Is Clear
Much of the public conversation about AI focuses on automation and job displacement. Yet the research tells a different story.
A study conducted by researchers from Stanford University and MIT involving more than 5,000 professionals found that employees using Generative AI improved productivity by approximately 14 percent overall. Less experienced workers saw improvements as high as 35 percent. The technology did not replace employees; it helped them perform more like top performers.
Similarly, Microsoft's Work Trend research found that business leaders are far more interested in using AI to improve productivity than to reduce headcount. Employees using AI reported saving time, increasing focus on higher-value work, improving creativity, and experiencing greater job satisfaction.
McKinsey estimates that Generative AI could create trillions of dollars in annual productivity gains across industries. Yet McKinsey's research also emphasizes that value is realized when organizations redesign work around a partnership between humans and AI, not when they attempt to remove humans from the process.
The lesson is straightforward: The greatest value of AI comes from combining machine efficiency with human judgment.
Why Leaders Should Pay Attention
Project managers and program leaders spend much of their time performing activities that AI can accelerate:
Reviewing information
Drafting communications
Preparing reports
Identifying risks
Evaluating alternatives
Facilitating decision-making
Organizing stakeholder input
These activities remain essential, but they are often time-consuming. Generative AI allows leaders to spend less time creating information and more time analyzing it:
Less time formatting
More time leading
Less time gathering information
More time making decisions
Less time documenting problems
More time solving them
Where AI Creates the Greatest Value
The most successful organizations are using AI to support, not replace three critical leadership activities.
1. Identifying Risks Before They Become Problems
Most project teams identify obvious risks. Fewer identify the risks that haven't yet been considered. AI can serve as an independent reviewer that challenges assumptions and uncovers blind spots.
Prompt Example:
"Act as a senior program reviewer with experience leading large technology, operational improvement, and business transformation initiatives. Review the following project summary and identify 15 risks the project team may be overlooking. Categorize each risk, explain why it matters, identify early warning indicators, and recommend mitigation actions."
This approach frequently reveals stakeholder concerns, resource constraints, dependencies, organizational resistance, and operational impacts that might otherwise remain hidden until they become issues.
2. Improving Stakeholder Communication
Projects rarely fail because schedules exist. Projects fail because people misunderstand expectations, resist change, or lack alignment. AI can help leaders tailor communications for different audiences.
Prompt Example:
"Act as an experienced change management advisor. Rewrite the following project update for executives, managers, and frontline employees. Identify the concerns each audience is likely to have, the messages most important to them, potential objections, and recommendations for communicating effectively."
The result is more targeted communication, improved stakeholder engagement, and greater organizational alignment.
3. Strengthening Decision-Making
One of the most powerful uses of AI is not generating answers. It is challenging assumptions.
Strong leaders do not seek validation. They seek clarity.
Prompt Example:
"Act as an independent executive review board. Analyze the following recommendation and identify hidden assumptions, unintended consequences, second-order effects, risks of inaction, and alternative approaches. Present arguments both for and against the recommendation."
Used properly, AI becomes a constructive skeptic that helps teams make more informed decisions before committing significant resources.
What High-Performing Organizations Are Doing Differently
Organizations that are seeing meaningful value from AI tend to follow several common practices.
AI Drafts. Humans Decide.
AI is often used to generate first drafts of plans, reports, communications, analyses, and recommendations.
Humans review, refine, validate, and approve the final product.
The accountability remains with people.
Use AI to Challenge Thinking, Not Confirm It
Many professionals unintentionally use AI to validate ideas they already support. The best leaders use AI to expose weaknesses in their thinking. They ask AI to identify flaws, alternative perspectives, and hidden risks.
Maintain Human Accountability
AI can recommend.
AI can summarize.
AI can analyze.
But AI cannot own outcomes.
Successful organizations maintain clear human ownership for decisions, approvals, and accountability.
Use AI to Elevate Team Capability
Research suggests AI often provides the largest productivity gains for less experienced professionals.
Organizations are using AI to help team members think more like experienced practitioners by improving planning, communication, risk identification, and problem-solving.
A Simple Framework for Responsible AI Use
Project leaders do not need a complicated methodology to begin leveraging AI effectively.
A simple framework is often enough.
Ask
Generate ideas, alternatives, risks, assumptions, and options.
Analyze
Evaluate patterns, trade-offs, dependencies, and implications.
Assess
Apply experience, organizational context, stakeholder knowledge, and professional judgment.
Act
Make decisions, accept accountability, and execute.
AI can significantly enhance the first two steps.
Leadership remains essential for the last two.
The Future Belongs to Leaders Who Learn to Think With AI
Throughout my career, I've seen organizations invest heavily in tools while underestimating the importance of people.
There is a lesson to be learned from Lean Thinking where respect for people is a foundational principle. Building on this, the first value in Agile is to value, "Individuals and interactions over processes and tools".
What these really refer to is getting the culture right, where people drive the decision making and benefit because of the tools they have available to help them. They understand the tools won't save them.
Generative AI should not become another example. The organizations that will benefit most from AI are not those seeking to replace human expertise, they are seeing to enhance it. People make better decisions, and they make them faster.
They are those seeking to amplify it. Technology can process information faster than people. It can identify patterns, generate options, and accelerate routine work.
But it cannot replace judgment.
It cannot replace leadership.
It cannot replace accountability.
And it cannot replace the ability to navigate uncertainty, build trust, resolve conflict, and make difficult decisions.
Those responsibilities will remain firmly in human hands. The future does not belong to leaders who compete against AI, it belongs to leaders who learn how to think with it. When used thoughtfully, Generative AI becomes more than a productivity tool. It becomes a catalyst for better decisions, stronger collaboration, and ultimately, better project outcomes.
