Podcast Summary

Podcast: B2B Agility with Greg Kihlström™: MarTech, E-Commerce, & Customer Success
Host: Greg Kihlstrom
Guest: Alan Mosca, Co-founder and CTO at nPlan
Episode: #69 – How AI is Transforming Project Management
Date: November 11, 2025

Episode Overview

This episode explores how artificial intelligence (AI) is fundamentally transforming project management, particularly in industries known for complex, large-scale projects, such as construction. Host Greg Kihlstrom interviews Alan Mosca, co-founder and CTO of nPlan, to discuss concrete examples, debunk misconceptions, and provide leadership insights for B2B organizations considering the adoption of AI for project management and risk mitigation.

Key Topics & Insights

1. Alan Mosca's Background and nPlan's Mission

• Alan Mosca, with a background as a quant in finance and a PhD in machine learning theory, co-founded nPlan to address complex risk and planning problems in the construction industry (01:20).
• nPlan was established as an AI-first company before the generative AI boom, leveraging machine learning to predict and manage project risks.

2. Real-World AI Impact: The Transpennine Route Upgrade (TRU) Case Study

• Project Complexity: The TRU is a $12-15 billion, decade-long railway upgrade in England, done without shutting down active lines (03:14).
• Reporting Transformation: Prior to nPlan's involvement, preparing a required project report took six weeks for a four-week cycle, causing data delays of up to ten weeks (04:15).
  • "By the time you're reading about a potential problem, it might have actually already happened." – Alan Mosca (04:07)
• After implementing AI-driven automation and forecasting, reporting was reduced to two weeks, freeing up the team for higher-value tasks (05:34).
  • “Now... they're free and can actually do their job. Because the reporting is not even their job. It is something that they have to do on top.” – Alan Mosca (05:34)
• Risk Mitigation: AI improved readiness for crucial project moments (e.g., "track possession" periods) where delays would incur fines of £35,000/minute, potentially saving the project costs in the eight to nine digit range (06:30).

3. Beyond Efficiency: True Value of AI in Project Management

• AI’s core benefit isn’t just automation, but the ability to explore vastly more scenarios in project planning and risk assessment (08:17).
  • “Organizations that spend billions of dollars, 50 hours a month is not registering on any.” – Alan Mosca (09:11)
• This computational scale enables organizations to proactively manage risks and make more informed decisions, rather than focus solely on incremental time savings.

4. Common Misconceptions About AI Adoption

• LLMs ≠ All of AI: Many assume AI in project management simply means using tools like ChatGPT, but real-world applications require custom machine learning algorithms, generative models, and scenario forecasting (09:44).
  • “We're still very anchored on AI equals LLM right now, rather than like, what are the things that you can really do?” – Alan Mosca (10:25)
• Overcoming Biases: Demos, extended pilots (at least six months), and real use cases are necessary to overcome initial skepticism, especially in complex, slow-moving industries (11:10).
  • “Any pilot less than six months, we're just not going to get to that point where our customers see a return within the pilot.” – Alan Mosca (12:26)

5. Data Readiness Challenges

• Data Organization Varies Widely: Some organizations have well-structured, centralized data repositories; others may have key information “on Dave’s laptop” from years past (15:44).
  • “So you have like those two extremes. And so in one case it's very easy, obviously, in the other case not so much, but there’ll always be something.” – Alan Mosca (16:04)
• Fine-tuning Models: nPlan fine-tunes its AI models using an organization’s historical project schedules to adapt to their unique processes and improve forecasting accuracy (17:20).

6. Leadership and Organizational Readiness for AI

• Leadership Must Be Hungry for Improvement: Successful AI adoption requires leadership that actively seeks organizational improvement and supports innovation (19:01).
  • “Leadership needs to be hungry for opportunities to improve their organization. And that's usually the spark that ignites everything else.” – Alan Mosca (19:01)
• Risk Aversion as a Barrier: Highly risk-averse sectors (e.g., nuclear, defense) require robust security and compliance, and sometimes leadership resistance can block innovation (19:01).

7. Empowering Teams for Change

• The workforce typically splits between AI skeptics (“AI will take my job”) and early adopters; the key is to give innovators space to experiment and support their ideas (22:39).
  • “Just let them come up with innovation ideas, try some experiments... good stuff will come out of it... You need to nurture them.” – Alan Mosca (23:48)
• Mandatory training or top-down imposition can stifle enthusiasm; instead, encourage organic growth of skills and interest.

8. Staying Agile as a Leader

• Alan recommends fostering a learning environment via research teams, regular events (like nPlan’s “AI Day”), and pushing the boundaries with stretch goals (24:10).
  • “We have had from day zero what a lot of people now call an ambidextrous organization.” – Alan Mosca (24:10)
• Staying updated in the AI space is challenging due to the overwhelming pace of new research and product development—be deliberate about what to focus on to avoid burnout (25:52).

Notable Quotes

• On reporting improvements and freeing up team time:

  “Now... they're free and can actually do their job. Because the reporting is not even their job. It is something that they have to do on top.” – Alan Mosca (05:34)

• On AI’s real impact:

  “If I'm taking a forecasting procedure that used to take six months and I can do it in 10 minutes... what does that mean? Well, it means that I can do hundreds of them every day... and that's how you create the value.” – Alan Mosca (08:17)

• On misconceptions of AI:

  “The biggest misconception that I find now is that everybody just thinks that when you mention AI, you actually mean ChatGPT...” – Alan Mosca (09:44)

• On leadership and culture:

  “Leadership needs to be hungry for opportunities to improve their organization. And that's usually the spark that ignites everything else.” – Alan Mosca (19:01)

• On managing AI change at mid-levels:

  “Just let them come up with innovation ideas, try some experiments, let them sometimes make some mistakes... good stuff will come out of it... You need to nurture them. That's the only thing that needs to happen.” – Alan Mosca (23:48)

Timestamps for Key Segments

• [01:20] Alan Mosca’s background & vision for nPlan
• [03:14] Concrete example: AI in the Transpennine Route Upgrade
• [05:34] Reporting transformation and team impact
• [06:30] AI’s role in risk mitigation and cost savings
• [08:17] The true value of AI: scaling scenario planning
• [09:44] Biggest misconceptions about AI in project management
• [11:10] How to engage skeptics and win buy-in for AI projects
• [15:44] Data readiness and organizational challenges
• [17:20] Fine-tuning AI models for client-specific accuracy
• [19:01] Leadership traits for successful AI adoption
• [22:39] Nurturing innovation within project teams
• [24:10] Alan’s agile routines and advice for staying adaptable
• [25:52] Dealing with information overload in the AI world

Memorable Moments

• The TRU project’s paradox: “Every four weeks the project team at TRU would produce a report... Making that report took them six weeks.” (04:05)
• AI’s role in avoiding “eight to nine digit” fines by accurately forecasting risks before they materialize (07:13).
• Alan’s approach to nurturing innovation: “All that leadership needs to do is give those people space... That’s the only thing that needs to happen.” (23:48)
• nPlan’s playful “NERD” research team and regular “AI Day” events to fuel creativity and adaptability (24:10).

Takeaways for Listeners

• For Executives: Focus on creating a culture where innovation is welcomed and hungry, and recognize that AI offers far more than incremental speed—it enables whole new ways of approaching complexity and risk.
• For Project Leaders: Don’t fear AI as a job-replacer; embrace it as a tool to elevate your strategic impact.
• For Data Managers: Data readiness is a journey; get organized now to reap AI’s future benefits.
• For Innovators: Seek out environments where experimentation is encouraged, and use AI to proactively shape rather than just react to project outcomes.

Full episode and more show notes available at:
www.b2bagility.com