The Human-AI Laser: Professor Rich Maltzman on Collaborative Intelligence in Project Management

The world of project management is experiencing a seismic shift as artificial intelligence transforms traditional approaches to planning, execution, and leadership. We recently had the pleasure of hosting Professor Rich Maltzman, master lecturer at Boston University, on the Project Flux podcast. With his extensive experience in project management education and as co-author of the insightful book "AI-Powered Leadership," Professor Maltzman offered a refreshingly balanced perspective on how AI and humans can work together to create something greater than the sum of their parts.

The Laser Metaphor: Amplifying Human Intelligence

One of the most compelling insights from our conversation was Professor Maltzman's laser metaphor, which elegantly captures the essence of effective human-AI collaboration. The cover of his book "AI-Powered Leadership" features a laser beam—a visual representation of what happens when human intelligence and artificial intelligence work in harmony.

"What's a laser? The nerdy name for it is light amplification by stimulated emission of radiation," Professor Maltzman explained. While that might sound technical, the principle is beautifully simple: light reflects back and forth between partially reflective mirrors, creating cohesive, focused, powerful light of a single colour—unlike the scattered beam of a torch.

This metaphor perfectly illustrates what we should strive for in AI-enhanced project management: "We want cohesive, powerful teams. We want answers that are cohesive and can do things like cut through metal, carve sculptures, and solve problems."

The key insight is that this focused beam emerges from the back-and-forth between humans and AI—a collaborative process where "AI is contributing its opinion and its value, and we take that and go, 'Good idea. How about this?'" It's this iterative dialogue that yields results that are "focused and cohesive and powerful."

AI as Conversation, Not Search Engine

A common mistake Professor Maltzman observes, particularly among his students, is treating AI like a search engine rather than a conversational partner. "What's been on my mind all along is this interaction between AI and humans and how it can be so misused and misunderstood as a search engine," he noted. "People will ask a question, take the answer, and then run with it, as opposed to having it be a conversation."

This misunderstanding leads to suboptimal results and reinforces misconceptions about AI's capabilities. The real power emerges when users engage in an ongoing dialogue, refining their prompts and building upon AI's responses. As Professor Maltzman emphasised, "It's much more about collaboration."

This conversational approach has profound implications for education. At Boston University, Professor Maltzman and his colleagues have been experimenting with different approaches to assignments and tests, recognising that AI has fundamentally changed how students learn and demonstrate knowledge. The goal isn't to prevent AI use but to encourage thoughtful, collaborative engagement that enhances rather than replaces human learning.

The Empathy Paradox

Perhaps one of the most intriguing paradoxes Professor Maltzman highlighted is how AI—a technology without true empathy—can actually help humans become more empathetic leaders. "There's a whole section here on how AI can make you a more empathetic leader. That's the irony of this," he explained.

Consider the scenario of writing a letter to a vendor about a poor delivery. If you write it when you're angry, or even after you've calmed down somewhat, it might contain subtle negative undertones that could damage the relationship. Professor Maltzman suggests using AI as an impartial reviewer: "You could say, as an impartial listener, 'Look at this letter I've written. Do you see any improvements?' It comes back and will give you perhaps a more empathetic letter that might get you a better result."

This approach extends to performance reviews, requests for additional team members, and handling disgruntled team members. While humans excel at interpersonal interactions, AI can provide valuable perspective that helps us communicate more effectively and empathetically.

James shared an excellent example of using AI to practice difficult conversations: "You can actually use AI to practice it because you can feed in that person's persona from their online presence and then explain the role or explain the context in terms of what the situation is." This allows project managers to rehearse various scenarios and responses, building confidence and improving outcomes.

Digital Twinning: The Double-Edged Sword

Our conversation took an interesting turn when discussing digital twinning—the creation of virtual replicas of physical objects or processes. Professor Maltzman highlighted the stark contrast between digital twinning in construction versus digital twinning of people.

In construction, digital twins offer tremendous benefits: "It's just absolutely amazing to see what you can do to look for what happens if this valve fails, what happens if this fire detector misfires or gives a false alarm and people are now all lining up in the wrong exit." These applications can improve safety, efficiency, and decision-making.

However, when it comes to creating digital twins of people—particularly with the advancement of AI avatars—Professor Maltzman expressed serious concerns: "I think there is a concern around digital twinning of people, not just in the sense of fraud or something like that, but in terms of your identity." He described his unsettling experience of seeing an AI avatar of himself delivering a lecture he had scripted but never actually delivered.

While he acknowledged limited legitimate uses, such as pre-recording an introduction to a course, Professor Maltzman was clear about the boundaries: "To take a gig, or to have this podcast with not me, but an avatar—no, it's got to be human. It's got to be real." As these technologies become more convincing, the need for robust authentication systems will only grow.

Standards and Guidance: Finding the Right Balance

A significant portion of our conversation focused on the challenges of creating effective guidance for AI use in project management. Professor Maltzman shared his critique of the PMI's draft AI standard, which spans over 360 pages—a length he believes undermines its practical utility.

"It's called a standard and it's 300 and something pages long, which is, as the kids say, TLDR, too long didn't read," he noted. While he praised PMI for addressing the topic, he argued that "they've effectively done in our humble opinion is try to rewrite the so-called PMBOK guide, the project management body of knowledge with reference to AI." The result is that the AI-specific guidance gets "lost in this universe of 300 and something pages of text."

Professor Maltzman and his co-authors didn't simply criticise; they provided constructive feedback, going through all 362 pages line by line with suggestions for improvement. Their recommendation? "It should have been a practice guide rather than a standard, and it should have been much more concise, maybe 12 to 100 pages at the absolute most."

This critique highlights a broader challenge: creating guidance that is neither too vague nor too prescriptive, especially for rapidly evolving technologies. As James noted, many organisations face similar challenges when developing AI policies: "The first draft is 30 pages long because they're trying to think of every eventuality that could ever happen. But of course, the day after it's published, it's already out of date."

The ideal approach, according to our conversation, is concise, principle-based guidance that can adapt as technology evolves—something closer to the RICS approach of about 15 pages that Professor Maltzman seemed to favour.

Sustainability and AI: A Complex Relationship

Another fascinating paradox we explored was the relationship between AI and sustainability. On one hand, AI systems—particularly large language models—require enormous computing power and energy. On the other hand, they can help organisations make more sustainable decisions.

Professor Maltzman highlighted this tension: "AI is very power hungry, as you've just mentioned. And the infrastructure is very carbon intensive." However, he remains optimistic that "that energy need will drop as microelectronics advances and the devices require less power."

He shared an example from his telecom industry experience, where a simple protocol change in how optical amplifiers switched on and off resulted in energy savings equivalent to "taking 100,000 cars off the road." This illustrates how seemingly small optimisations can have significant environmental impacts—optimisations that AI could potentially help identify and implement.

Professor Maltzman also emphasised how AI can promote more holistic, long-term thinking in project decisions. He introduced the concept of Life Cycle Assessment (LCA), which many project managers aren't familiar with: "AI could be asked as an advisor... look, it is going to be less money for us to build this road if we use vendor A at one-third the cost of vendor B. But vendor B's product, although more expensive for purchase, is going to result in a much better picture five, 10 years from now."

By helping project managers quantify and communicate these long-term benefits, AI can shift decision-making toward more sustainable outcomes—even if the initial development of AI itself poses sustainability challenges.

Practical Applications for Project Leaders

Throughout our conversation, Professor Maltzman shared numerous practical applications of AI for project leaders, demonstrating how these tools can enhance rather than replace human capabilities.

One particularly powerful example was using AI to create multiple versions of quizzes with the same difficulty level. "I plugged one of my quizzes in, I gave it my lecture notes in a firewall situation, and I said, can you create a similar quiz with the same mix of fill in the blanks, multiple choice and short essay questions? And the output was astoundingly good," he shared. The AI didn't just rearrange existing questions but created entirely new ones that maintained the appropriate difficulty level.

This same capability extends to project planning: "Just translate that to project managers, it could create a project plan. And we've tested it for that too. It can do a very good job of creating a project plan."

James expanded on this idea, noting that "most of the processes within project management, it's got a use case for in terms of whether it's a project plan or whether it's some kind of schedule review." The multimodal capabilities of modern AI models make them increasingly valuable across the project lifecycle.

Another creative application is creating an AI "board of advisors" composed of personas whose judgment you trust. As James described it, "I want Warren Buffett as my financial advisor. I want Steve Jobs as my tech advisor, but I don't want him to give me any advice about how to raise a family." You can even include "your older self" on this virtual board. While the AI is drawing on publicly available information about these individuals, it provides a unique way to gain diverse perspectives on complex decisions.

The Future of Project Management

Looking toward the future, Professor Maltzman offered valuable insights on how project management will evolve alongside AI. A recurring theme from his interactions at PMI conferences was the need for project managers to become "more human" as AI handles more technical tasks.

"How do we survive as project managers that can do scheduling and planning? Where do we, how do we help?" These questions reflect the anxiety many professionals feel. The answer, according to Professor Maltzman, lies in the uniquely human capabilities that AI lacks: "We add the aspect of, okay, this vendor or this particular installer for this vendor works in this way, has had a bad week. It's the expertise and experience that humans have that AI does not have."

While AI has data, it lacks the contextual understanding and interpersonal awareness that experienced project managers bring to complex situations. "It doesn't know that Karen and Kim don't get along or that they just had some kind of conflict last week," Professor Maltzman noted. These human dynamics remain critical to project success, regardless of technological advancement.

For project leaders considering AI adoption, Professor Maltzman warned against haphazard implementation without proper guidance: "The single biggest risk to a leader who is kind of really excited about AI and just starts to use it haphazardly without any guidance." This approach can lead to security breaches, loss of intellectual property, ethical issues, and poor decision-making.

Instead, he advocates for thoughtful integration with appropriate guardrails—not the 300+ pages of the PMI draft standard, but enough structure to ensure responsible use. As he put it, leaders need to "understand it" rather than treating it as magical or infallible.

Conclusion: The Human-AI Partnership

Our conversation with Professor Rich Maltzman revealed a nuanced vision of AI in project management—neither a threat that will replace human project managers nor a magical solution to all challenges. Instead, it's a powerful tool that, when used thoughtfully in collaboration with human expertise, can create outcomes greater than either could achieve alone.

The laser metaphor perfectly captures this vision: humans and AI in constant dialogue, reflecting ideas back and forth until they emerge as a focused, coherent beam capable of cutting through the most complex project challenges. This requires understanding AI's capabilities and limitations, providing appropriate guidance without excessive restrictions, and recognising the enduring value of human judgment and empathy.

As project management continues to evolve in the age of AI, those who master this collaborative approach—treating AI as a conversation partner rather than a search engine, using it to enhance rather than replace human capabilities, and maintaining appropriate guardrails—will be best positioned to lead successful projects and teams.

Connect with Professor Rich Maltzman on LinkedIn to follow his insights on AI and project management. His book "AI-Powered Leadership" (co-authored with Vijay Kanabar, David Silverman, and Laura Donaghey) is available through Pearson. And as always, subscribe to the Project Flux newsletter for weekly updates on how AI is transforming the future of projects.