Speaker
Abstract
In large, highly regulated enterprises like ING, adopting AI in engineering isn’t as simple as enabling a new tool — it’s a fundamental shift in how thousands of engineers design, build, and deliver software. This talk shares how ING introduced GitHub Copilot to more than 5,000 engineers, and what it truly takes to measure, scale, and sustain AI‑driven productivity across a complex, global organization.
We will walk through ING’s journey from early pilots to full‑scale rollout, highlighting measurable productivity outcomes as well as the cultural, operational, and engineering transformations required to make AI adoption stick. Moreover, we will share practical lessons learned and insights, which can be relevant to any organization navigating AI adoption at enterprise scale.
Sponsored session
QCon London 2026 is a three day conference for senior software engineers, architects and team leads. An international program committee of working engineers selects every session. Patterns and practices, not products and pitches.
Part of the track
Sponsored Solution Track IFrom the same track
Monday 16 March
10:35 Westminster (4th Fl.) Sponsored Scaling the Unknown: How monday.com Built Performance Guardrails for AI and Custom Apps Eviathar Moussaffi, Chen Salomon At monday.com, we’ve learned that performance bottlenecks are never solved—only relocated. 11:45 Westminster (4th Fl.) Sponsored From Pilot to Impact: How AI Is Transforming Large‑Scale Engineering Yaping (Luna) Luo Global Head of Developer Experience (DevEx) & System Engineering @ING In large, highly regulated enterprises like ING, adopting AI in engineering isn’t as simple as enabling a new tool — it’s a fundamental shift in how thousands of engineers design, build, and deliver software. 13:35 Mountbatten (6th Fl.) Sponsored From Prompt to Production: How Spotify Builds Internal Tools in Days with AI and Platform Engineering Stuart Clark, Mike Lewis Spotify Portal Studio + Claude — Empowering Internal Teams to Build Tooling… 14:45 Westminster (4th Fl.) Sponsored Maximising an Agentic AI Ecosystem: Trust, Control and Scale Jonathan Griffiths Field CTO @Dynatrace Agentic AI is rapidly moving beyond individual assistants toward interconnected ecosystems of agents, tools, and platforms. This shift promises step‑change improvements in productivity and autonomy—but it also introduces new challenges around trust, control, and operational scale. 15:55 Westminster (4th Fl.) Sponsored Beyond Observability: Implementing Runtime Guardrails for Production AI Agents May Walter Co-Founder and CTO @Hud Agentic engineering thrives in controlled environments but often falters in dynamic production systems. 17:05 Westminster (4th Fl.) Sponsored Context Engineering: Building the Knowledge Engine AI Agents Need Brandon Waselnuk Developer Relations @Unblocked Every AI coding tool can generate code. Very few can generate the right code for your organization — because they're missing context.