While it may seem your team is not using your new AI tools, they may be leveraging AI in ways you have not anticipated, often outside the systems you have implemented. In this episode of Predictable B2B Success, host Vinay Koshy interviews Tom Gersic, whose experience includes SaaS adoption at Salesforce, large-scale AI deployments in global banks, and, as founder of ux.ai, developing advanced sales tools.

Tom Gersic discusses his experience with “Lightning Adoption,” a major initiative that reported directly to Marc Benioff. He examines the shortcomings of traditional adoption strategies, the limitations of customer logo-based targets, and misconceptions about executive sponsorship. Drawing on extensive experience, he provides a candid perspective on why superior products do not always gain traction and why initial enthusiasm for new technology often fades before its value is realized.

This episode offers valuable insights for founders preparing for board meetings and revenue leaders seeking to measure the true value of AI. Listen to learn what truly drives and hinders adoption in the current AI landscape.

Some topics we explore in this episode include:

• Product Adoption Strategies: Focus on user workflows, not just product features, to drive real adoption.
• Monthly Active Users (MAU) as Key Metric: Moving from vanity metrics to MAU for measuring true engagement.
• User Experience and Performance Issues: How usability and perceived speed barriers affect adoption.
• Executive Sponsorship: The critical impact of hands-on leadership on rollout success.
• Hype Cycle and Disillusionment: Persevering through the “trough of disillusionment” when initial excitement fades.
• Enthusiasm vs. Sustained Adoption: Why excitement isn’t enough for long-term, meaningful use.
• Shadow AI Use and Governance: Risks of unapproved AI tool use and the enabling role of strong governance.
• Embedding AI in Workflows: The imperative to deeply integrate AI into daily business processes.
• Measuring Productivity and Value: Aligning metrics to true business outcomes instead of surface-level activity.
• AI in Regulated Industries: Unique challenges and lessons from deploying AI in sectors like finance and insurance.