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Pragnya
Paramita
Director, Global Product Marketing - BTP AI
SAP
Pragnya is Director of Global Product Marketing for BTP AI at SAP, where she was the first AI product marketing hire on the team, building SAP's enterprise AI go-to-market from the ground up for a portfolio spanning Fortune 500 enterprises and a global developer community. She leads a pod of product marketers across SAP's Cloud, Enterprise, and Ecosystem pillars, owns budget, and has built the GTM frameworks now used across the organization. Her work spans developing a unified portfolio narrative for a multi-product enterprise AI platform, shaping positioning for SAP's open AI ecosystem (including how Model Context Protocol integrations with agentic developer tools and workflow automation partners extend enterprise governance beyond the platform itself), and arming the global sales org with competitive battlecards to compete against hyperscaler bundles from AWS, Google Cloud, and Azure. She's also driven joint go-to-market motions with ecosystem partners and led demand generation programs behind some of the platform's highest-performing webinars to date.
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21 January 2027 13:45 - 14:30
Three lightning talks on where AI is helping PMM, and where it's quitely destroying it
Three product marketers working in genuinely different conditions, a listed enterprise, a fast scale-up, and a business that can't touch customer data without a compliance sign off, each take the stage alone for ten minutes. No shared script, no panel smoothing their answers over. Each one says exactly what they tried with AI, what actually worked, and what they quietly shut down. Then all three come back up together for fifteen minutes of open Q&A, so the room can press them on it directly. Attendees walk away with: - A concrete AI use case each speaker killed after rolling it out, and the real reason it didn't survive contact with their team - What genuinely moved a number their leadership cares about, not what looked good in a vendor demo - How company size and regulatory exposure change which AI bets are worth making first, so attendees can size their own next move against a peer in a similar spot