PMI and AI: from Project Manager to Strategic Leader

What is your role and what is it that you actually do?

I serve as PMI’s Director, AI Engagement & Community, leading our PMIxAI initiative to help project professionals adopt AI responsibly, effectively, and at scale. My role combines strategy, education, and community-building. In short, I help project professionals and their organisations lead AI transformation. That means equipping them with the right methodology (CPMAI), skills, and community support to deliver AI outcomes reliably and ethically.

How did you arrive at your current position?

I joined PMI about a year and a half ago through the acquisition of Cognilytica, the AI-focused research and advisory firm I co-founded. At Cognilytica, I co-developed the CPMAI methodology which is a vendor-neutral, data-centric framework for managing AI projects and built programs to guide organisations in delivering successful AI initiatives. I also launched and hosted the AI Today podcast, which became a leading source of practical insights on AI adoption. The podcast is now in its 9th season.

When PMI acquired Cognilytica, they brought in CPMAI, the podcast, and a wealth of AI content to accelerate their AI strategy. My role evolved naturally from that integration: I now lead PMI’s AI Engagement & Community efforts to help PMI lead the AI transformation of project management and the project management of AI transformations.

Let’s face it; AI for Project Management – Why is this important?

AI is transforming how work gets done across many industries and roles, and project management is no exception. Projects are becoming more complex, data-driven, and fast-paced. AI helps project professionals make better decisions, automate routine tasks, and uncover insights from data that humans alone would struggle to process. Incorporating AI is not about replacing project managers – it is about augmenting their capabilities so they can focus on strategy, leadership, and delivering value.

Why is this important? Because organisations that leverage AI in project management gain a competitive edge including:

• Improved forecasting and risk management through predictive analytics.
• Smarter resource allocation and scheduling with AI-driven optimisation.
• Enhanced stakeholder communication using AI-powered tools for reporting and visualisation.

Ultimately, AI enables project managers to deliver outcomes faster, with greater confidence and efficiency, while freeing them from repetitive tasks. It is a game-changer for the profession and a critical skill for the future.

What are the most promising use-cases of AI in Project Management that you believe are underutilised today?

Some of the highest-impact use cases for AI in Project Management include:

1. Predictive Risk Management

AI can analyse historical project data and external factors to predict risks before they materialise. Few teams are leveraging this for proactive mitigation, even though it can dramatically reduce project failures.

2. Resource Optimisation
AI-driven tools can forecast resource needs and dynamically adjust allocations based on real-time changes. This goes beyond static planning and helps avoid bottlenecks and cost overruns.

3. Intelligent Decision Support
AI tools can synthesise large volumes of project documentation, stakeholder feedback, and market data to provide actionable insights for decision-making. Many organisations still rely on manual analysis.

4. Automated Reporting & Status Updates
AI can generate tailored dashboards and summaries for different stakeholders, saving hours of manual reporting and improving transparency.

5. Requirements and Scope Analysis
AI can detect ambiguities, inconsistencies, or gaps in requirements early in the project lifecycle reducing costly rework later.

These use cases do not just improve efficiency, they elevate the role of project managers from task coordinators to strategic leaders, enabling better outcomes and stronger business impact.

What are the biggest organisational or cultural barriers you see when integrating AI into established Project Management practices?

The biggest challenges are not technical. Rather, they are human and cultural. Here are some the top barriers I see:

1. Fear of Job Displacement
Many project professionals worry that AI will replace them, rather than augment their role. This fear can lead to resistance and slow adoption.

2. Lack of AI Literacy
Organisations often underestimate the need for AI education and upskilling. Without understanding what AI can and cannot do, as well as how to properly utilise AI tools, teams do not always use AI tools to their full potential.

3. Change Resistance
Established processes and the “we have always done it this way” mindset often create friction when introducing AI. Integrating AI is not just a technology shift, it requires rethinking workflows, roles, and decision-making, which can feel disruptive to teams. Successful AI adoption is fundamentally a change management exercise: it demands clear communication, stakeholder engagement, and a structured approach to guide people through the transition. Without addressing the human side of change, even the best AI tools will struggle to gain traction.

4. Trust and Transparency
People hesitate to rely on AI-driven recommendations if they do not understand how decisions are made. Building trust through explainability is critical.

5. Leadership Alignment
If leadership does not champion AI adoption and model its use then often these AI initiatives stall. Cultural change starts at the top.

Ultimately, overcoming these barriers means focusing on people first including clear communication, training, and positioning AI as a tool to empower, not replace, project managers.

How should Project Managers’ roles evolve in an AI-augmented environment, and what new skills will become essential?

In an AI-augmented world, the role of the project manager shifts from task coordinator to strategic leader. AI will handle much of the routine tasks such as status updates, scheduling, risk calculations. This frees up time for project managers to focus on value delivery, stakeholder alignment, and change leadership.

To thrive, project managers need to develop new capabilities including:

• AI Literacy: Understand what AI can and cannot do, understanding which AI tools to use and when, and how to interpret AI-driven insights.
• Data-Driven Decision Making: Be comfortable with understanding data and have the ability to translate data into actionable strategies.
• Change Management Expertise: AI adoption is a transformation, not just a tool upgrade. Project managers must help guide teams through cultural and process shifts.
• Ethics and Governance: Ensuring the responsible use of AI will be critical including addressing bias, transparency, and compliance.
• Strategic Thinking and Adaptability: PMs need to focus on outcomes, not outputs, and lead projects in environments where technology and business models evolve rapidly.

In short, project managers will need to become AI-enabled leaders, blending human judgment with machine intelligence to deliver better results.

With more organisations looking to adopt or create AI tools for their needs, what professional opportunity does this present for project managers? And what makes leading an AI project different than leading an IT project?

AI adoption opens a tremendous opportunity for project managers to lead one of the most transformative waves in business. Organisations need professionals who can manage AI initiatives responsibly, align them with business goals, and deliver measurable outcomes with positive ROI. This is where project managers can step up, not just as coordinators, but as strategic leaders of AI-driven change.

Unlike traditional IT projects, AI projects are data-centric and iterative. Success depends on data quality, model training, and continuous refinement and not just writing code or deploying software. AI projects also involve ethical considerations, bias mitigation, and governance, which require a different mindset and skill set. Leading an AI project means managing uncertainty, guiding cross-functional teams, and balancing technical complexity with business impact.

To seize this opportunity, project managers should upskill in AI and data practices and earn credentials like PMI-CPMAI certification. PMI-CPMAI provides a proven, vendor-neutral methodology for managing AI projects effectively, ensuring you can deliver results while addressing risk, ethics, and change management. Becoming PMI-CPMAI certified positions project managers as trusted leaders in this fast-growing space.

How can project professionals learn the skills and methodologies they need to lead AI projects?

The best way to prepare for AI-driven work is to learn a structured, proven approach to managing AI projects and that is exactly what PMI-CPMAI certification offers. CPMAI (Cognitive Project Management for AI) is a vendor-neutral methodology designed specifically for AI and data-centric projects. It teaches you how to handle the unique challenges of AI initiatives, such as iterative development, data quality and preparation, model training, and ethical considerations.

What makes this a great opportunity? There are no prerequisites or other certifications required. Anyone interested in leading AI projects, whether you are a seasoned project manager or new to the field, you can start right away. PMI-CPMAI equips you with practical steps, a hands-on workbook, and case studies so you can confidently deliver AI projects that meet business goals.

In short: AI is reshaping project management, and PMI-CPMAI is your gateway to becoming an AI-ready project leader.

On a more personal note, how do you see your professional growth in the coming years? What can we expect from you?

I am focused on helping project professionals lead AI transformations, not just adopt AI tools. Over the next few years, you can expect me to deepen three areas of impact:

1) Scaling PMIxAI programs and PMI-CPMAI globally
I will continue expanding the reach of PMI-CPMAI, PMI’s gold-standard certification built on the CPMAI methodology, so more practitioners can learn a structured, vendor-neutral way to run AI projects responsibly and effectively.

2) Building a global AI community
Community is how change scales. I am launching and nurturing an AI Champions programme, partnering with regional leaders and chapters around the globe, to showcase real use cases, share lessons learned, and accelerate responsible AI adoption across industries.

3) Elevating AI thought leadership
I will keep amplifying applied insights through the “AI Today” podcast including interviewing CPMAI certified folks to showcase how CPMAI is being applied across organisations, industries, and regions. Moreover, I will do so by curating industry series and case-driven conversations, and contributing to PMI’s AI guidance and standards so practitioners have clear, ethical, and executable guardrails. My goal is to connect the dots from research and standards to day-to-day delivery, making AI project success repeatable.

In short, you can expect me to keep bringing no-hype, real-world AI to project management as well as continuing to champion PMI-CPMAI, scaling community leadership, and turning insights into action for teams everywhere.