Despite the rapid advancements in generative AI, many enterprises—including Agile organizations—struggle to scale AI initiatives beyond the proof-of-concept (PoC) phase. At OpenTable, we turned this challenge into an opportunity to embed AI strategically across our products and workforce while staying true to Agile principles. In this session, I will be pairing with my Head of Product to share our transformation journey from both an IT and business perspective—offering a holistic view of how AI adoption requires alignment across technology, strategy, and operations to succeed at scale.
AI-First Product Strategy: How we built AI-powered solutions like automated review responses and SEO-optimized content generation, ensuring cost efficiency and performance while reducing reliance on external APIs.
AI-Enabled Workforce & the ART Framework: Overcoming skepticism and fostering AI adoption within teams using ART—a framework focused on Autonomy, Removing Silos, and Tighter Feedback Loops—to create a culture where AI enhances human potential rather than replacing it.
Scaling AI Operations: Establishing repeatable, scalable processes for AI deployment, model training, security, compliance, and continuous monitoring to ensure long-term success.
Agility in AI Adoption: Applying Agile methodologies such as "Date for Date" to balance confidence in delivery with leadership expectations while navigating uncertainty in AI development.
By embracing systems thinking, we successfully transformed AI from a disconnected set of tools into a strategic enabler of agility and innovation. This session will provide actionable insights for organizations looking to leverage AI responsibly, drive human-AI collaboration, and establish AI as a core pillar of Agile transformation.
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A framework for prioritizing AI initiatives across products and processes.
Strategies for fostering AI adoption among teams, addressing cultural resistance, and unlocking creativity.
Lessons on experimenting iteratively and balancing agility with leadership expectations.
Pitfalls to avoid when transitioning to an AI-native culture.