From AI Products to Enterprise Transformation to Industry Impact.
Three lenses on the same question — how AI actually creates value: as a builder, inside the enterprise, and across the wider ecosystem.
Three lenses on the same question — how AI actually creates value: as a builder, inside the enterprise, and across the wider ecosystem.
I believe the future of AI must be viewed through three complementary lenses: the builder who creates technology, the enterprise leader who scales it responsibly, and the ecosystem thinker who understands its broader economic and societal impact.
I'm Laks Alagappan, an Executive MBA graduate from Bayes Business School, London, holder of the Data Strategy for Leaders credential from Imperial College Business School, and a member of the Forbes Technology Council.
With over 25 years of experience leading large-scale technology transformation programmes across global financial institutions, I specialise in enterprise AI, software engineering, and business-led technology transformation.
Alongside my corporate leadership experience, I have designed and built several AI-powered platforms and products, including Skillopedia and others listed below. These initiatives have given me hands-on experience in applying AI to solve real-world business challenges, from enterprise productivity and knowledge management to workflow automation and intelligent decision-making.
I also write about technology, and innovation ecosystems. One of my recent articles, “26 Years On: When Ecosystems Don't Just Support Growth—They Compound It”, explores the importance of professional ecosystems, mentorship, and lifelong learning in driving long-term impact.
My thought leadership focuses on the practical application of AI within large enterprises, particularly where technology, governance, engineering, and organisational transformation intersect.
Topics I'm Exploring for Future Articles
→ How Will the CIO Organisation Transform in the Age of AI?
→ Governing Agentic AI in Banking: From Model Risk to Digital Workforce Governance
→ The Agent Management Function in the CIO Organization
→ Beyond Bronze, Silver And Gold: Is Your Data Ready For AI Agents?
→ From Data Pipelines To Decision Pipelines: Rethinking The Enterprise Data Platform
→ Can Your Data Platform Explain An AI Agent's Decision?
Where my writing and speaking have shown up beyond my own site.
In my September 2026 byline for Forbes Technology Council, I argue that most organisations measure software engineering productivity wrong — fixating on narrow coding metrics like lines generated or commit speed while ignoring requirements, testing, security, and deployment. AI can accelerate code generation, but it amplifies existing engineering discipline rather than replacing it; the metric that matters isn't how fast developers write code, it's how much faster and more reliably the whole engineering system delivers real business outcomes.
I'm a member of the Forbes Technology Council, an invite-only community for senior technology executives, and contributed to their August 2026 Expert Panel on the higher-level skills software engineers need in the AI era — on why the differentiator is shifting to systems thinking: defining the right problems, designing resilient architectures, governing AI agents, and connecting technology to business outcomes.
Profiled alongside my career transition from engineering into strategic technology leadership since my 2015 Executive MBA and the Bayes Alumni Forum talk below — including why human oversight remains critical to AI adoption and what's really holding enterprise programmes back.
Writing is where I spend most of my time, but the ideas started somewhere — here's where I've taken them to a room.
A candid discussion with 20+ mid-to-senior leaders from banking, insurance, consulting, technology, real estate, startups, and academia — exploring where organisations really are in their AI journey, and what separates successful AI programmes from endless pilots.
Key themes covered
I speak from experience because I build. A growing portfolio of agentic platforms at the intersection of AI, data, compliance, and human potential — mapped in full in Atlas below.
An index of the full agentic portfolio — 30 platforms across six business divisions (Capital Markets & Investment Banking, Retail Banking, Insurance, Compliance & Financial Crime, Technology & Data, and Support Functions), with an interactive map of how it all fits into the wider financial-services ecosystem.
A mentor–learner marketplace connecting people with mentors across 300+ specialisations. The same belief that powers the technology work: people before platforms.
The same belief that shapes the writing and the ventures — people before platforms — carries into mentoring.
Migrant Leaders — recognising work mentoring career changers into technology.
Ongoing mentor for career changers and women in technology navigating the move into leadership.
Moving Ahead — sponsoring the next generation of diverse talent in technology and finance.
I write regularly on enterprise AI, agentic systems, and where the technology is actually delivering value. If something I've written resonates — or you want to talk collaboration, a speaking opportunity, or just compare notes — I'd like to hear from you.