AI changes every field it touches in different ways. These articles are co-written with people who know one of those fields from the inside.
6 articles
With Maria Singh
Security reviews score findings one at a time and assign each to the team that owns the asset. An AI agent connects those assets by design, so three Low findings can add up to one critical path that no team owns. FIRST's CVSS guidance already says how to score chains, and OWASP's agentic guidance says how to break them. Here is how to govern the path as well as the parts.
With Dr. Christina Chua
Brokers are letting AI agents place orders, compliance teams are handing e-communications review to language models, and Project Guardian has put tokenised bonds into production. Each move raises a control question that boards in Singapore have not yet answered: who is liable when an agent trades outside its mandate, how to prove a quieter alert queue is a better one, and whether live asset data can be trusted to value a tokenised infrastructure bond.
With Maria Singh
Most organisations defer some patches and record the decision as an accepted risk. Those decisions assumed that turning a patch into a working exploit took skill and weeks. Anthropic's 2026 evaluations show a model doing it in under an hour for about $2,000 per exploit, and its September threat report describes criminals running exploit research around the clock. Here is how to rewrite the risk register.
With Chris der Kinderen
The fuel station is one of the first places in retail where AI, the connected car and new payment rails meet at scale. What changes at the pump and in the shop, where the risks sit in pricing, fraud and customer data, and what operators should do in the next twelve months.
With Dr. Christina Chua
Banks, exchanges and central banks are moving money and securities onto the same programmable rails that DeFi built. By 2031 the two systems will share settlement, collateral and market mechanisms, with regulated access on top. AI arrives at the same time as customer, attacker, target and supervisor. Here is how the integration will unfold, where AI changes the risk, and what boards and regulators should do now.
With Maria Singh
No quantum computer can break today's public-key encryption yet, but the estimates of what it would take fell twentyfold in a year, and Google now targets 2029 for its own migration. AI systems rest on the same RSA and elliptic-curve cryptography: the links that carry training data, the signatures that vouch for models and the tokens that identify agents. Here is what breaks, what does not, and what boards should do now.
Cybersecurity and AI
Vice President, The AI Collective; Founder, AISecurityLab.ai
3 articles together
Maria is a cybersecurity and AI strategy leader, Vice President of The AI Collective and founder of AISecurityLab.ai, who at T-Mobile helped cut critical vulnerabilities by 90% across more than 75,000 endpoints. Our posts together cover the security assumptions under AI programmes that are ageing fastest, from the cryptography AI systems rely on to how organisations decide which vulnerabilities to leave open.
Wealth management and institutional sales
Director, Institutional Sales, Moomoo Financial Singapore
2 articles together
Christina supports institutional sales at Moomoo Financial Singapore and has spent more than ten years in financial services across private wealth, key accounts and institutional clients. Our work together looks at how regulated finance is adopting new infrastructure, and where AI changes the risk.
Fuel retail and forecourt payments
Project Delivery Manager APAC, Vontier
1 article together
Chris leads project delivery across Asia Pacific at Vontier, whose Gilbarco Veeder-Root and Invenco businesses supply fuel dispensers and forecourt payment systems, and has delivered forecourt technology programmes worth more than US$70 million for major oil companies in Malaysia and India. Our work together looks at how payments and AI are changing the fuel station.
Most of my work sits where AI meets a board's accountability. The hard questions usually come from a specific field: a security specialist's view of what a quantum computer would break, a finance view of what settlement risk means once money moves on shared ledgers, a view from security operations of what a patch deferral assumes about the attacker. I would rather write those posts with someone who has done that work than write around the gaps myself.
Each post is written by two people.
The collaborator brings the domain. I bring the governance and board view.
The evidence standard does not change.
Every claim is checked against its primary source and graded in the Evidence & Methodology table, the same as every other post on this site.
Credit is stated plainly.
Co-authors are named in the byline and linked to their own profiles. Reviewers who improve a post after publication are thanked by name at the end of it.
I started this section because the co-written posts came out stronger than what I would have written alone. If you lead in a field that AI is changing and you have a view the rest of us should hear, write to me. The bar is the same one I hold myself to: verified sources, plain language, and something a reader can act on.
Ask Terence
Answers from his writing, with sources.
AI-written from this site's pages and can be wrong. How this works
