Expert Perspective | AI & Rewards | Recent Developments

In this Expert Perspective, Michael Piker discusses how AI is transforming work and why Total Rewards (TR) is a critical lever for successful AI adoption. As roles are redefined, HR and TR must rethink how they reward performance, learning, and productivity. The session combines recent AI developments with practical frameworks and examples to help organizations move from experimentation to impact.

Key focus areas:
- Transforming TR to Lead AI Adoption: AI is already augmenting most work. What does this mean for roles, skills, and reward models in practice.
- AI Reward Tools: Use Cases and Platforms. Practical AI applications and technologies supporting reward, performance, and pay decisions.
- From TR Specialists to Strategic Advisors: How TR leaders evolve into strategic advisors shaping talent strategy and business outcomes in AI driven settings

Artificial Intelligence is no longer a future capability—it is actively reshaping how work is performed and how value is created inside organizations. This session highlighted that while AI tools are rapidly embedded in daily workflows, many reward frameworks, job architectures, and governance models lagging reality, creating risks around fairness, trust, and adoption. The discussion reframed AI not as a technology challenge, but as a workforce and rewards design challenge, with Total Rewards positioned as a critical lever.

A recurring message was that what organizations reward ultimately shapes behaviour. If AI-enabled learning, experimentation, and higher-quality outcomes are not recognized through pay, incentives, and career signals, employees receive mixed messages. Total Rewards, therefore, plays a decisive role in whether AI becomes a true value creator or a missed opportunity.

Key takeaways:

• Total Rewards is a strategic enabler of AI adoption
  Reward systems send powerful signals. When AI-enabled contribution is not reflected in rewards, adoption slows and trust erodes. Aligning rewards with AI-driven value creation is essential for sustainable transformation.
• AI is redefining work faster than reward frameworks evolve
  Roles are expanding in scope and abstraction due to AI, while job structures remain static. This gap creates hidden inequities and misalignment between contribution and reward.
• Skill-based rewards require outcome focus, not tool focus
  The most valuable AI-related capabilities are often non-technical—judgment, problem framing, and orchestration. Rewarding tool usage alone risks missing real value creation.
• AI should inform reward decisions, not replace human judgment
  AI can enhance insight and consistency, but accountability for pay and performance decisions must remain human to safeguard fairness, transparency, and trust.

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