With a wave of retirements about to hit workforces, companies have to be prepared to keep avenues open for experienced workers who want to adapt to AI, and to teach junior workers so they can still learn the core skills that AI now performs.

Key takeaways include:

• The day-to-day challenges this shift will bring
• What kinds of responses can HR leaders experiment with to protect and grow expertise amid rising retirements and AI reshaping on-the-job learning?
• What expertise will look like in an AI-enabled workplace
• How to frame the skills and expertise issue so people in the boardroom take action.

Subscribe to the UC Today channel for more interviews with HR experts on trends shaping the future of work.

Join Kieran Devlin from UC Today as he sits down with Chris Stapenhurst, Director of Product Management at Arctera. If you are navigating the complexities of modern compliance and data governance, this conversation highlights exactly why the "build it yourself" model is becoming obsolete.

As data volumes explode and regulations tighten ahead of 2027, the traditional on-premise data center is struggling to keep up. Chris Stapenhurst explains that AI is incredibly power-hungry - noting that large tech companies are even purchasing nuclear power stations to fuel data centers - and most firms simply cannot manage that level of hardware overhead on their own.

In this insightful discussion, Kieran and Chris break down the critical role of elasticity in the AI era. They discuss why "building for tomorrow" often leads to wasted budget on unused capacity, and how SaaS models offer a smarter alternative.

Key discussion points include:

• The Power of Elasticity: Understanding how cloud infrastructure allows organizations to "burst" up resources to meet immediate AI processing demands and shrink back down instantly, ensuring you only pay for what you use.
• Data Governance & Hygiene: How Arctera aggregates and normalizes content from disparate sources (whether on-prem or cloud) to create the clean, accessible data foundation required for accurate AI insights.
• Agility Through SaaS: The compliance advantage of a SaaS model, which delivers seamless quarterly updates to address new regulations without the costly downtime and IT resource drain associated with upgrading on-premise systems.

Next Steps:

Are your infrastructure and compliance strategies ready for the next wave of AI regulations? Visit the Arctera website to learn more about their cloud-native solutions.

AI is no longer experimental. From Microsoft Copilot to Zoom AI Companion, AI is now embedded across enterprise collaboration platforms - and leaders are under pressure to deploy it at scale.

But here’s the challenge: the pace of innovation is outstripping traditional governance models. New behaviors are emerging. AI-to-AI interactions are happening. Shadow AI is spreading. And regulators are watching closely.

In this exclusive UC Today interview, Rob Scott sits down with Devin Redmond, CEO of Theta Lake, to unpack what modern AI governance really looks like - and why moving from guardrails to scalable governance is now mission‑critical for CIOs.

In this conversation, we explore:

• Why AI has moved from pilot projects to production pressure
• The innovation paradox facing today’s CIOs
• Why blocking AI often increases enterprise risk
• What real AI governance maturity looks like#
• How to monitor human‑to‑AI and agent‑to‑agent interactions
• Why regulators are intensifying scrutiny
• What CIOs should demand from their AI vendors