Synthetic Workforce Data – A New Model for Change Management
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Synthetic Workforce Data – A New Model for Change Management
HubSpot has created a ‘workforce twin’ – an AI-powered platform that predicts how employees may react to new policies before they are introduced. By drawing on survey data, sentiment analysis and synthetic modelling, the tool equips leaders with early warnings of likely concerns and equips HR and comms teams to prepare more effective rollouts. Matthew Corritore shares lessons from developing this product, from pilot stage to adoption by senior leaders.
Why is this being discussed now?
Why is this being discussed now?
Large organisations must deliver constant change – from hybrid work to job architecture redesign – but leaders often lack foresight into employee reactions. Failed rollouts waste time, cost, and credibility. Synthetic data models offer a way to road-test policy changes safely, helping HR mitigate risks and build trust while accelerating adoption.
What will be covered in this episode?
What will be covered in this episode?
- How synthetic workforce data is created and governed responsibly.
- Applications of predictive models to anticipate employee concerns.
- Examples of policy changes shaped by simulated employee reactions.
- Designing AI tools for adoption by HR, comms and business leaders.
What will I learn by watching?
What will I learn by watching?
- Understand how synthetic data can enhance change management practice.
- Learn a framework to build, pilot and scale predictive HR tools.
- See how AI models identify risks and improve rollout planning.
- Gain practical advice on starting small and demonstrating value quickly.
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15 - 16 October 2025 · Convene West 46th Street · New York
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