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Sergio
Morales Esquivel
Head of Autonomous Engineering & AI Solutions
Growth Acceleration Partners
Sergio is Head of Autonomous Engineering & AI Solutions, where he leads the design and delivery of AI, data science, and engineering solutions for complex enterprise environments. With a background in software engineering and a Master’s degree in Computer Science, Sergio specializes in building scalable data platforms, intelligent systems, and high-performance engineering pipelines that connect technical innovation with business impact. At GAP, he oversees multidisciplinary teams working across data engineering, AI implementation, and autonomous systems, while contributing to the company’s Data Analytics Center of Excellence. His work includes mentoring engineering talent, supporting recruitment initiatives, and helping organizations stay aligned with advancements in AI and data technologies. Sergio brings expertise spanning backend architecture, cloud computing, distributed systems, embedded software, low-latency streaming, geolocation technologies, and large-scale data infrastructure. He works across diverse technology stacks with experience in Python, Scala, R, AWS, Spark, and modern analytics frameworks. He also lectures within the Data Analytics postgraduate program at Cenfotec University, helping develop the next generation of AI professionals.
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04 June 2026 14:30 - 15:30
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. In this executive roundtable, peers will share what is actually working in production and where autonomous workflows struggle to deliver tangible value and fall short of fully replacing human execution. 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. We will discuss the orchestration layers and guardrails required to manage access controls and permissions for autonomous software pipelines without choking innovation. Join us to discuss how leaders can build the practical operating model needed to scale AI from experimentation to measurable business impact.