Terence Kok
Enterprise AI Strategist · Author · Keynote Speaker
Registered Management Consultant (RMC) · ISO/IEC 42001:2023 Lead Auditor

Biography
Terence Kok is an enterprise AI strategist with twenty-five years leading AI and digital transformation programmes across Asia and the Middle East. He has designed and deployed AI systems for national smart city initiatives, critical infrastructure projects, and enterprise operations at scale, including a retrieval-augmented generation platform serving more than 6,000 engineers with zero security incidents. His practice spans the full deployment lifecycle: from readiness assessment and governance design through to production optimisation and ROI measurement.
His work centres on three disciplines most AI implementations neglect. First, structured impact assessment before deployment begins, so ROI claims are defensible rather than aspirational. Second, AI governance that maintains accountability as systems scale: oversight, escalation paths, and audit trails. Third, an optimised deployment methodology that closes the gap between pilot success and production performance, drawn from the Eight-Dimension AI Readiness Assessment in his book AI at Scale: From Pilot to Production (2026).
Terence introduced the Return on Employee (RoE) framework as a counterweight to narrow cost-reduction AI business cases, quantifying the productive capacity gained per person instead: hours reclaimed, decision quality, and cognitive bandwidth returned to higher-value work. He has applied RoE across mid-market transformation engagements, government capability-building programmes, and international development contexts, including the UN ESCAP AI for Developing Countries Forum.
Speaking Topics
AI Readiness Diagnostics
The five-dimension framework for assessing whether an organisation is positioned to deploy AI productively.
Governing Agentic AI Systems
How to design oversight structures that maintain accountability when AI acts without human approval for every step.
Measuring AI ROI
Two measurement layers, model performance and business outcome, and what to measure in the first ninety days. Includes the Return on Employee (RoE) framework for workforce-aligned impact reporting.
AI Governance for Non-Technical Leaders
The four governance questions every decision-maker must answer before deploying AI, translated from IMDA and NIST frameworks into plain language.
Return on Employee: Rethinking AI Investment
Why AI business cases built on cost reduction fail to sustain leadership support, and how the RoE model measures AI performance through workforce capacity amplification, improved decision quality, and cognitive bandwidth returned to higher-value work.
Selected Engagements
Conversational AI Innovation Summit
InteracTech Asia
9th Chief Digital & Data Officer Asia Summit
CDO Vision Singapore
AI for Developing Countries Forum (UN ESCAP)
FutureCIO Conference
C-Engage Convention
3rd Salalah Engineering Forum
IMDA Digital Transformation Industry Day
