With the eruption of AI, how do you incentivize a stagnant workforce to embrace 'continuous learning' and motivating them to learn as the workforce technology evolves?
Scott RugglesIT Project Manager| Maricopa County Department of TransportationPhoenix, Az, United States
With all of the emerging technologies, tools, and instructions coming from all angles on prompting, llms, and the proper methods when dealing with AI projects and data. How are you encouraging your workforce to have an open mindset and take their time to learn and experiment with these emerging technologies? Company-issued trainings? Policy documents? Are you incentivizing those who take time from their days to brush up on the latest trends?
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Luis BrancoCEO| Business Insight, Consultores de Gestão, LdªCarcavelos, Lisboa, Portugal
Excellent question. I'd challenge one underlying assumption: a workforce often appears "stagnant" not because people resist learning, but because the organization hasn't made learning part of the work itself. Training, incentives and policies certainly help, but they rarely compensate for operating models that reward short-term delivery while leaving little time or space for experimentation. The real challenge may be less about motivating people to learn and more about designing work so continuous learning becomes a normal part of delivering results.
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1 reply by Scott Ruggles
Jul 20, 2026 3:00 PM
Scott Ruggles
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Great call. Yes the 'learning' part of the organization is typically met with 'Where am I supposed to find the time?' and that needs to shift and all parts of the organization need to allocate. some of their time (however small) to knowing what's going on in the industry, new tools, etc. Otherwise we'll constantly be behind the curve.
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Scott RugglesIT Project Manager| Maricopa County Department of TransportationPhoenix, Az, United States
Jul 20, 2026 2:43 PM
Replying to Luis Branco
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Excellent question. I'd challenge one underlying assumption: a workforce often appears "stagnant" not because people resist learning, but because the organization hasn't made learning part of the work itself. Training, incentives and policies certainly help, but they rarely compensate for operating models that reward short-term delivery while leaving little time or space for experimentation. The real challenge may be less about motivating people to learn and more about designing work so continuous learning becomes a normal part of delivering results.
Great call. Yes the 'learning' part of the organization is typically met with 'Where am I supposed to find the time?' and that needs to shift and all parts of the organization need to allocate. some of their time (however small) to knowing what's going on in the industry, new tools, etc. Otherwise we'll constantly be behind the curve. Saving Changes...
Robert SnyderFounder & President| Innovation Elegance, LLCChicago, Il, United States
Scott, in the U.S. over the past 10-20 years, a trendy statement from H.R. departments has been that employees own their careers.
"Behind the curve" is a fundamental marketing tactic, right?
Cynicism aside, I do like a rigorous Lessons Learned template (list of 14 culture traits) that includes the culture trait of "Learning."
I recently attended the INSEAD webinar that forced me to stop and reflect on the future of organizations: Humans and Algorithms Working Together. We need to raise the organization design question and understand: What will humans do, and what will machines do? In a summary: There is no universal blueprint for human-AI collaboration. Every organization must learn what works through disciplined experimentation. -Define meaningful metrics for successful organizing -Design and run parallel experiments -Compare alternative collaboration models -Scale successful innovations enterprise-wide -We should think of technology as a teammate Key Message: treat organization design as a continuous capability – not a one-time restructuring Still, I don’t know the answer to how to redesign the organization for an AI-enabled world, but reflecting on the question, “What will humans do, and what will machines do?” could help me navigate in the right direction of experimentation. Saving Changes...
Robert SnyderFounder & President| Innovation Elegance, LLCChicago, Il, United States
I'm unsure if it qualifies as a blueprint, but a cute statement resonated with me, so I'll share. Human should delegate to technology work that qualifies as dull, dirty, dangerous, difficult, demanding, demeaning, delicate, or dear.
Very subjective, but there's some merit to it. 😊
If I literally treat technology as a teammate, I expect that AI might have authority for work and accountability for work, relieving humans of either or both. I expect to see AI with assignments on the project plan.
Just like organizations maintain scorecards for their operations, I'd love the PM profession to formulate a scorecard for project culture, but I don't see an appetite for that.
I believe there are some timeless culture traits for collaboration that serve as a blueprint: scale, infrastructure, low marginal cost, synchronization, boundaries, simplicity, transparency, low latency, and trustworthiness.
But I'm also learning I'm in the minority. What seems to be the blueprint instead is VUCA. But even in that, it's good we have clarity about important ambiguity is. 😊
Orchestration is a buzzword for AI agents, but it hasn't reached buzzword status for human collaboration. Since humans don't organize (orchestrate) themselves on their own terms, AI might orchestrate humans on its terms? Saving Changes...
Scott RugglesIT Project Manager| Maricopa County Department of TransportationPhoenix, Az, United States
Jul 20, 2026 3:09 PM
Replying to Robert Snyder
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Scott, in the U.S. over the past 10-20 years, a trendy statement from H.R. departments has been that employees own their careers.
"Behind the curve" is a fundamental marketing tactic, right?
Cynicism aside, I do like a rigorous Lessons Learned template (list of 14 culture traits) that includes the culture trait of "Learning."
That's the vertical axis, adjacent to a column to rate Red/Yellow/Green.
Although the horizontal axis, the sentences ...
I like ___________. I wish ___________. I hope ___________. I wonder ___________.
That is how I try to keep a culture of learning. Reactions and ideas welcome.
Interesting! I'll do some research on that template and see what reactions my team will have to providing some data for it. Thanks!
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1 reply by Robert Snyder
Jul 21, 2026 3:09 AM
Robert Snyder
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Certainly. I hope it's helpful. One caveat ... 3 or 4 columns ... 14 rows ... that's either 42 or 56 cells. Keep in mind it's a monthly Lessons Learned template. As few as 3-5 cells might be enough to focus on in any given month, aiming that every "wish," "hope," and "wonder" is resolved, and every month has minimal or zero duplicates from the previous month.
I sequenced the rows according to how I viewed the sense of urgency. If 14 rows is overkill, "crawl, walk, run." Start with 3 rows ... or 7 rows ... and as each trait is green and stably green, add more culture traits to scrutinize/reflect. I'll stay tuned!
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Robert SnyderFounder & President| Innovation Elegance, LLCChicago, Il, United States
Jul 21, 2026 12:06 AM
Replying to Scott Ruggles
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Interesting! I'll do some research on that template and see what reactions my team will have to providing some data for it. Thanks!
Certainly. I hope it's helpful. One caveat ... 3 or 4 columns ... 14 rows ... that's either 42 or 56 cells. Keep in mind it's a monthly Lessons Learned template. As few as 3-5 cells might be enough to focus on in any given month, aiming that every "wish," "hope," and "wonder" is resolved, and every month has minimal or zero duplicates from the previous month.
I sequenced the rows according to how I viewed the sense of urgency. If 14 rows is overkill, "crawl, walk, run." Start with 3 rows ... or 7 rows ... and as each trait is green and stably green, add more culture traits to scrutinize/reflect. I'll stay tuned!
Based on my understanding, organizations and leaders should actively encourage their teams to learn and experiment. Knowledge is the most valuable asset in the software industry and in the era of AI, continuous upskilling is essential.
Organizations should incentivize training programs that directly support project needs. Additional trainings can be recognized in performance appraisals as a positive factor in ratings, encouraging employees to continuously expand their expertise.
AI should be viewed as an assistant, not a replacement. The results generated by AI must always be verified by the individual responsible for the work, which requires a understanding of the subject matter. Without that knowledge, verification is impossible. Saving Changes...
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