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Jocelyn

Sexton

VP, Growth Marketing

Growth Acceleration Partners

Jocelyn Sexton is Vice President of Marketing at Growth Acceleration Partners (GAP) and a B2B technology marketing executive with more than 20 years of experience building high-performing marketing organizations that drive measurable business growth. She specializes in transforming marketing into a commercial growth engine through AI-enabled teams, data-driven demand generation and full-funnel revenue strategies. Throughout her career, Jocelyn has led global marketing organizations for high-growth technology companies and Fortune 500 brands, including Emerson and Dover. Her expertise spans AI, SaaS, enterprise software and industrial technology, with a focus on aligning brand, demand generation and sales to accelerate pipeline and revenue. She has also led marketing integration for multiple acquisitions and is passionate about helping organizations adopt AI to improve productivity, decision making and marketing performance. Jocelyn earned her MBA from The University of Texas at Austin and has been recognized as one of Austin's Top 50 Women Leaders.

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26 August 2026 13:30 - 14:30

Roundtable | From AI pilots to autonomous engineering: What it takes to put agentic systems into production

Let’s discuss the PoC-to-Production Engineering Gap. AI leaders are under pressure to move beyond prompt-driven tools, generative chat interfaces and proofs of concept, but most agentic initiatives stall before reaching production. Today, we aim to talk about what is actually working in production and where autonomous workflows struggle to deliver tangible value and fall short of fully replacing human execution. We know success requires reliable orchestration, AI-ready data, robust evaluation frameworks, cost controls, governance, and engineering teams that can balance applying expert and institutional judgment with the automation capabilities of AI. So let’s discuss the orchestration layers and guardrails required to manage access controls and permissions for autonomous software pipelines without choking innovation. And let’s see how y'all are building the practical operating models needed to scale AI from experimentation to measurable business impact.