What if the biggest missed opportunity in marketing isn’t what you send but what you shouldn’t send at all? In this episode of The Array by Jacquard, Toby and Jasper sit down with George Khachatryan, Head of AI Decisioning at Braze, to explore how reinforcement learning and AI agents are transforming marketing from static, segment-based campaigns into dynamic systems that make real-time, one-to-one decisions for every customer. They break down why traditional A/B testing is fundamentally limited, how AI decisioning continuously balances exploration and exploitation to maximize outcomes, and why true personalization requires more than just the “right message, right time, right channel.” The conversation dives into the importance of knowing when not to engage, the tension between short-term performance and long-term brand identity, and the three key bottlenecks - content generation, data integration, and experimentation, that prevent most organizations from realizing AI’s full potential. This episode also reframes the marketer’s role in an AI-first world: from executing campaigns to managing intelligent agents, setting guardrails, and making strategic trade-offs that data alone can’t solve. For teams looking to move beyond manual segmentation and unlock meaningful ROI from AI, this conversation provides a clear, practical framework for the future of marketing. What You’ll Learn: Why most marketing teams are bottlenecked by content, data, or experimentation and how to identify your weakest link How reinforcement learning outperforms traditional A/B testing by minimizing wasted opportunity during experimentation Why “right message, right time, right channel” is incomplete without knowing when not to send anything How AI decisioning enables continuous, real-time personalization at the individual level - not just segments The hidden trade-off between short-term conversions and long-term brand equity and how to manage it with guardrails How combining content generation AI with decisioning AI creates exponential personalization at scale Why marketers are evolving from campaign operators to “AI agent managers” How autonomous systems balance exploration and exploitation to solve the cold-start problem What it takes to move from static creative libraries to infinite, personalized customer experiences George Khachatryan is the Head of AI Decisioning at Braze, a pioneering platform in AI-driven lifecycle marketing. He specializes in applying reinforcement learning and AI agents to optimize customer engagement at scale, enabling brands to move beyond manual segmentation and rule-based systems toward fully autonomous, one-to-one decisioning. Under his leadership, AI decisioning platforms have helped enterprises dramatically improve campaign performance across use cases like cross-sell, retention, and winback by making real-time, individualized marketing decisions. George is at the forefront of redefining how marketers leverage AI - not just for automation, but for continuous learning, experimentation, and strategic growth. If you enjoyed this episode, make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube Podcasts.
