The AI Twin of
IAN CHENG
Turning AI into measurable business outcomes.
Ask Artificial Ian about AI strategy, transformation and leadership. He has learned from The AI Executive Briefing and speaks in Ian's real voice.

Artificial Ian
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- 20 yearsturning emerging technology into business results
- 3 continentsAsia, Europe and North America
- 17 issuesof The AI Executive Briefing
- 90+ languagesspoken by the AI Twin
Bio
Two decades of turning technology into results.

Ian Cheng has spent two decades turning emerging technology into business results. He began his career as an engineer, working on computer vision systems and process engineering for high-precision semiconductor packaging. In 2007, inspired by the launch of the first iPhone, he founded g-Dadi, one of the earliest mobile apps for hailing a taxi.
What followed was a career across five industries and three continents, much of it spent building new sources of growth. At Dun & Bradstreet, he led a US$14 million acquisition in China and its post-merger integration, extending the business from credit risk into digital marketing. At Avery Dennison, the company was pursuing an ambition to grow revenue from US$6 billion to US$9 billion in three years, and he shaped its Asia growth strategy to match. He led seven M&A and strategic investment deals totalling around US$1 billion, including a co-investment alongside Cambridge Innovation Capital and Arm. Through his regional emerging-technology portfolio, he also brought in projects with Amazon, on the technology behind its first cashier-less store, and with Coca-Cola, on its "Share a Coke" campaign. As General Manager at LF Beauty, part of Li & Fung, he held full P&L responsibility for a US$800 million business of 2,300 people, and later led its separation as a standalone company ahead of its sale to private equity firm Hony Capital. At K11, he built a digital ecosystem connecting luxury retail, hospitality and lifestyle businesses.
Today, Cheng leads AI and automation at Jaguar Land Rover, working alongside senior leadership and the C-suite. He has orchestrated the digital capabilities behind a subscription EV charging ecosystem spanning 1.1 million charge points across the UK, Europe and North America, a cornerstone of the company's non-vehicle services strategy.
"AI takes repetitive tasks away, not jobs," he says. It is the conviction behind his view that business transformation must come before AI transformation.
Under the professional moniker Artificial Ian, he publishes The AI Executive Briefing for senior leaders and speaks at international forums hosted by the University of Cambridge, the Financial Times, The Economist and the Hong Kong Trade Development Council. Born in Hong Kong and based in London, he has lived and worked across mainland China, Singapore, Malaysia, Thailand, Japan and the United States, and speaks English, Mandarin and Cantonese. Cheng holds an MBA with Distinction in Corporate Strategy and Finance from London Business School and The University of Hong Kong, and completed executive education at Harvard University in business analytics and big data. Outside work, he is an avid reader and a wine collector.

Engagements
At international and executive forums, Ian Cheng turns two decades of transformation into practical insight, and exchanges it with the leaders shaping what comes next.
University of Cambridge · Financial Times · The Economist · World Finance Forum · Pay360 · Digital Marketing World Forum · TechEx Europe · Hong Kong Trade Development Council
Perspectives
People own the result.
AI can recommend, predict and act, but accountability never transfers. Human-in-the-loop means a named owner for every outcome, with the authority to override.
Data-driven decision making.
Agentic AI turns connected data into decisions at speed. Autonomous agents handle the routine calls, so leaders focus on the choices only people should make.
From Pilot to P&L.
Choose pilots by strategy, not curiosity. Back them with resources, executive support and clear guardrails, so every pilot serves a business purpose and is built to scale.
(Build · Test · Learn)100
Encourage innovation, accept calculated risk and move in short build-test-learn cycles. Agile teams learn faster than perfect plans.
Featured moments

The Economist · AI for CFOs · 2026From Cost-Cutting to Organisational Change 
Financial Times · Future of AI · 2025Integrating AI into the organisation 
HKSAR Government & HKTDC · 2016Building an efficient, data-driven supply chain platform
Signature perspective
When intelligence is abundant, judgement becomes the advantage.
As AI reaches every company, the winners will be the leaders who decide with purpose, execute at speed and bring their people with them.
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