Answer extracted from the The Josh Bersin Company podcast — listen to the full episode below.
Which AI use cases deliver immediate impact in HR workforce operations?
Seneca Polytechnic deployed AI across five critical workforce areas: workforce planning, organizational design, job architecture, change management, and compensation analysis. Their standout approach creates personas for change management by analyzing organizational data to build archetypes, which they use as a testing ground to improve deliverables and navigate complexity.
From broad strategy to concrete change management personas
The scope of Seneca's AI deployment reveals how HR teams can think systematically about where AI adds value. Rather than piloting AI in isolation, Diana Mouhan's team embedded it across the full talent lifecycle—from planning headcount needs to designing how compensation aligns with organizational strategy.
The persona-building approach stands out because it translates abstract organizational complexity into human profiles. By analyzing data at the thematic level, the team creates archetypes that represent distinct employee segments or change readiness profiles. These personas become a testing mechanism: HR leaders can stress-test new policies, communication strategies, or process designs against each persona before rolling out to the full organization.
As discussed in this episode of the What Works podcast, this method helps teams anticipate friction and refine solutions early. It's particularly powerful during organizational change, where one-size-fits-all communication often fails. Personas reveal where different groups sit on adoption curves, what concerns matter most to each segment, and how to craft messaging that resonates.
"Trust isn't just telling people don't be afraid. Trust is actually built on acknowledging the concerns that they have and being super vulnerable in that journey with them."
Diana Mouhan — Executive Director of Transformation and Change at Seneca Polytechnic. With over a decade of expertise in organizational strategy and AI adoption, Diana has built transformation practices across Deloitte and Kearney before leading Seneca's innovation hub, where her team drives HR modernization through data-driven personas and adaptive change strategies.
The persona approach also echoes a broader insight from Seneca's journey: understanding where your team sits on the AI readiness spectrum is the foundation for any sustainable deployment. What Diana's team discovered was that readiness ranges dramatically—some staff members still needed to learn what a prompt was, while others were already experimenting with advanced use cases.
The compensation analysis and job architecture applications show that AI doesn't have to be flashy to deliver value. Market data, internal pay equity assessments, and role-based competency mapping are all areas where AI accelerates accuracy and reduces manual analysis time. These use cases often deliver faster returns than more experimental applications.
If you're mapping where AI fits in your own HR operation, Diana's full conversation covers how she prioritized which areas to tackle first and how budget constraints actually forced her team to be more creative in using existing tools.
Key takeaways
- AI delivers fastest impact when deployed across the full talent lifecycle (planning, design, compensation, change management) rather than isolated pilots.
- Persona-building using organizational data creates testable archetypes to validate HR strategies before rolling out organization-wide.
- Change management personas reveal readiness profiles and allow HR leaders to craft targeted communications for different employee segments.
- Foundational use cases like job architecture and compensation analysis often deliver steadier ROI than more experimental AI applications.
See also
What assessment approach reveals HR team readiness levels for AI adoption?
Diana's team took time to listen and understand where each person was on their AI journey—some didn't yet understand what a prompt was while others were already exploring advanced applications. This personalized assessment informed targeted training and support strategies.
What is the foundation for building trust in AI adoption within an HR team?
Diana emphasizes that trust isn't simply telling people not to be afraid of AI. Instead, it requires acknowledging team members' concerns vulnerably and walking the AI journey together, validating concerns while demonstrating value.
How can an HR organization continue transformation when technology funding disappears unexpectedly?
Rather than pausing the transformation until funding returns with indefinite timing, Diana's team at Seneca Polytechnic redesigned the transformation itself, shifting from "what technology do we need" to "how do we optimize the tools we already have."