Executive Technology Board
From closed-door discussion to practical frameworks
The Executive Technology Board distills anonymized, Chatham House–compliant insights from boardroom sessions into short, shareable briefings. These are built for senior leaders who need patterns, trade-offs, and next moves — not theory, hype, or vendor narratives.
Featured Insight
The Executive Technology Board Innovation Index is curated by our members, and spotlights early-stage companies shaping AI in the enterprise. This year’s list features private, AI-native startups that are gaining traction across large enterprises - we started with sourcing lists from top tier VCs and Industry Analysts; then rationalized down for focus, fit and size; and then invited members to down select the companies to include on the list. Request here.
Insights
AI and Digital Transformation in Asia
Cross-industry leaders compared AI transformation across very different starting points - from greenfield platform roll-ups to century plus-old, regulated incumbents. Despite variance in maturity, themes converged on: simplify and standardize first; keep the core thin; push differentiation to data products and AI at the edge; and treat culture as the hardest constraint. Request here.
AI & the Three Pillars of Success
This is a summary of learnings on the three pillars of success in AI in the Enterprise: AI Strategy, Enterprise Architecture and Organizational Design & Change. We also reflect on a deep dive example amongst our membership and take away key learnings from the journey. AI-generated audio summary available. Request here.
AI Agents & Agentic AI
This session underscored that agentic AI is no longer a theoretical construct but an operating reality, with enterprises deploying it across clinical trials, engineering, logistics, procurement, manufacturing, and customer engagement. Enterprises should treat agentic AI not as a technology overlay but as a driver of operating model redesign, workforce transformation, and measurable business outcomes. Priorities should be clear data governance, explainable trust frameworks, and vertical use cases that deliver demonstrable value. Request here.
Redefining Digital
As digital transformation reaches a new inflection point with the mainstreaming of predictive, generative and now agentic AI, enterprises are reassessing both their past progress as well as future direction. We’ve already invested significantly in digitizing operations, modernizing infrastructure, and experimenting with emerging technologies – and yet the journey has only really begun. The definition of “digital” is also evolving - from discrete, tech-led initiatives to embedded strategies that are inseparable from core business and growth priorities. And this redefinition of Digital now means managing significantly higher complexity, balancing incredible speed and agility with stability and leverage, integrating sustainability, ethics and responsible AI governance. Request here.
Leadership in the age of Generative AI
The conversation surrounding Generative AI has decisively shifted from “what is it?” to “how fast can we change?” While GenAI is often framed as a technological leap, its true disruption lies in how it rewrites the rules for talent, training, operating models, and leadership culture, especially in knowledge-driven industries. Leaders pointed to a generational divide: early-career employees adopt GenAI as naturally as spreadsheets, while mid-level professionals - often gatekeepers of process and institutional knowledge - remain hesitant or unsure how to apply it. This "messy middle" is now the greatest barrier to widespread adoption. Request here.
Building AI-Ready Data Platforms
The path to enterprise AI maturity runs directly through data. But building AI-ready data platforms is not a technical problem alone. It’s a multidimensional transformation that touches architecture, governance, talent, and organizational design. Early AI efforts often failed not because the models were ineffective, but because of poor data quality, fragmented ownership, and misaligned user experiences. Modernizing infrastructure without addressing foundational issues tends to accelerate inefficiencies rather than resolve them. And AI-readiness demands more than scalable tooling; it requires consistent, trusted data flowing through systems that are aligned with how the business actually operates. Request here.
Governance in the current climate
Global enterprises are now operating in a world of radical regulatory divergence, geopolitical volatility, and technological acceleration, and all happening at once. Data flows that once powered seamless globalization are now being rerouted, restricted, or reinterpreted by local law. AI, still in its early innings, is heading toward a regulatory reckoning. Meanwhile, expectations around privacy, ethics, transparency, and resilience are splintering across borders. This is no longer just about compliance. It’s about strategic posture, cultural fluency, and organizational agility. Request here.
The Evolution of Enterprise Architecture & AI in the enterprise
Enterprise architectures are undergoing significant transformation as organizations navigate geopolitical shifts, regulatory complexities, and the rapid adoption of AI. The traditional focus on efficiency and standardization is being replaced by an approach that prioritizes resilience, flexibility, and business alignment. Two major shifts are defining the evolution of enterprise technology. Reflecting on real world case study and the parallel evolution of AI in the enterprise. Request here.
Redefining Trust in the Digital Economy
In a world where technology evolves faster than policies and societal norms, trust has become both a currency and a foundation of success in the digital economy. Technology enables scale and velocity in ways previously unknown, amplifying not only opportunities, but also risks - issues once manageable on a smaller scale at pace have now become monumental in their impact. And trust is no longer a passive construct but an active, dynamic process that requires continuous alignment between technology, ethics, and human values. Request here.
Rethinking Customer Value Chains
Evolving AI, data platforms and automation technologies are creating opportunities to reimagine entire customer value chains that were originally put in place with the capabilities then available. Technology executives embarking on this journey of rethinking their customer value chains are transforming their businesses, and driving growth, efficiency, and durability in their business models. Request here.
Operating Technology
This meeting of the Executive Technology Board curated small group of Europe-based CIO/CDO/CTO members from corporations across vertical industries. The group toured one of Europe’s largest fully automated smart factories of its kind and spent time on a deep dive discussion on Operating Technology (OT). This summary of the conversation has been abstracted to a framework that may be used in defining and driving OT/IT operating model convergence, implementing AI in manufacturing, and governing for Cybersecurity in OT. Request here.
Next steps
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