Hong Kong AI adoption tests governance readiness

Organisations scaling autonomous systems face growing pressure to strengthen accountability, workforce oversight, and data governance.

Hong Kong organisations are moving quickly to adopt artificial intelligence, but governance and workforce readiness risk lagging as systems take on more autonomous decision-making.

Stanley Sum, Partner for Technology Consulting at KPMG Advisory (Hong Kong) Limited and one of the judges for the Hong Kong Business Technology Excellence Awards 2026, said companies need to rethink how work is organised as AI moves beyond assisting employees towards executing tasks.

“The biggest shift isn't technical, but it's cultural and operational,” Sum said.

Employees will increasingly need to orchestrate workflows and critically assess AI outputs rather than focus on repetitive tasks. Sum said this requires continuous learning, stronger domain judgement, and confidence to challenge AI recommendations instead of accepting them automatically.

Accountability also becomes more important as autonomous systems make decisions. Sum said responsibility should remain with business and product owners supported by technology leadership.

“Autonomy changes how decisions are made, but business leaders always own the outcome,” he said.

Organisations therefore need clear operating boundaries, human oversight, fail-safe mechanisms and escalation paths before allowing AI systems greater autonomy.

Data quality presents another challenge, but Sum said it should be viewed as part of a wider governance problem rather than the sole barrier to scaling AI.

Different teams can adopt AI at different speeds, creating fragmented systems, inconsistent standards and unauthorised tool use. Companies consequently need stronger data permissions and governance alongside reliable information that can provide models with real-time context.

“Without this foundation, you are not scaling the intelligence, but you are scaling errors potentially faster,” Sum said.

For executives, Sum argued that AI should therefore be treated as a business transformation rather than a technology project, requiring attention to governance, workforce management and organisational processes across the enterprise.