CHRO participants engaged in a meaningful discussion about AI’s impact on the workforce, recognizing that human capital leaders will play a critical role in guiding this people transformation. Here are our key takeaways from the roundtable discussion.
Strategy & Framing
- AI is a people transformation, not a technology transformation. Framing AI as an IT initiative misses the point. The real opportunity lies in reimagining how work gets done, how roles are defined, and how organizations are structured. Firms treating AI purely as a cost-cutting tool risk short-term gains at the expense of longer-term organizational health.
- Governance needs to be cross-functional. AI strategy owned solely by IT tends to stall. Roughly 40% of real estate firms now have cross-functional technology committees made up of people across the organization who are experimenting and sharing ideas. HR needs a seat at that table from the start.
Organization Design
- The org structure conversation is urgent and wide open. Traditional org design aimed for 5-year shelf stability is no longer realistic. The classic pyramid is flattening: entry-level roles are evolving into more analytical mid-level work, middle management is thinning, and senior leadership becomes even more critical for judgment, relationships, and capital decisions.
- "Human in the loop" is not enough. Think "human in the lead." It is not just about where humans check AI outputs, but where humans must lead and AI supports, versus where AI leads and humans support. This reframe is a practical tool for org design conversations.
- The entry-level skills gap deserves attention. Eliminating entry-level work risks hollowing out the talent pipeline over time. Entry-level roles will likely evolve rather than disappear, requiring critical thinking and communication skills from day one, with AI handling the administrative baseline that used to define those jobs.
Change Management & Culture
- Culture, trust, and change management are the hardest parts. Resistance to technology and change stalls AI rollouts more than technology does. Employees worry about what AI means for their roles, and trust in AI outputs is still being earned. Change management needs to be baked into AI strategy from the start, not bolted on later.
- Change management belongs in HR and should be treated as a leadership competency, not a project management function. Formalizing a methodology and cascading it through the organization was cited as a key near-term priority.
- Change fatigue is real and underestimated. The pace of AI-driven change is relentless. Unlike past transformation cycles, there is no clear beginning, middle, and end. Organizations need to actively account for human sustainability as part of any AI implementation plan.
The Future of Work
- Relationships will matter more, not less. Where AI has already been deployed, it often points back toward human connection. Residents still want human contact. Investors still want trusted advisors. As AI handles more routine work, leaders and employees will have more bandwidth for relationship-building, coaching, and higher-judgment work.
- The role of the people manager is shifting, not disappearing. Managers today play a critical role in setting vision, managing prioritization, and helping employees navigate an overwhelming pace of change. Over time, AI may take on more routine supervisory tasks, raising the question of what distinctly human leadership looks like at every level.
- There is an opportunity to rethink work more broadly. Several participants raised the question of whether AI gives organizations a real opening to redesign work structures more fundamentally, including how hours are structured, how teams are organized, and whether the industrial-age model of work still makes sense.
Practical Actions & Tools
- Incentivize ideas from the bottom up. One firm launched an AI incentive policy offering bonuses for employees who surface high-impact AI use cases, creating an organization-wide innovation channel rather than relying solely on top-down direction.
- AI coaching tools are showing early promise. One participant is piloting an AI coaching tool for frontline managers at a low per-employee cost and has already seen a meaningful drop in employee relations cases.
- Use a structured framework to evaluate AI use cases. A four-part framework was shared covering whether the problem is worth solving with AI, whether AI is the right tool, whether it can be deployed responsibly, and where it should live. A fifth dimension was suggested by the group: the human sustainability factor, accounting for change fatigue and the pace of continuous iteration.