Dr. Elias Kairos Chen
AI Researcher · Entrepreneur · Strategic Adviser · Author
Exploring how artificial intelligence, agency and superintelligence are reshaping organisations, economies, governance and the human future.
I study intelligence, natural and artificial, and advise the leaders deciding what to do about it. My work runs from brain-inspired AI research to enterprise transformation, intelligent agency and the broader implications of superintelligence.
Boards are told how much AI their organisations use. They are rarely told what it has done to the accounts. A case for judging AI by readiness, financial outcomes and responsible delegation.
Read the essay →Present-day erosion of entry-level work and occupational identity is overlooked by debates fixated on AI extinction and abundance, and needs policy attention.
Proposes a four-layer framework (present, transition, systems, self and civilisation) for mapping AI's transformation of civilisation, and outlines the author's upcoming work.
AI is fragmenting the old labour-for-income economy into five coexisting economies, and institutions fail to see all five at once.
AI capability, institutional acknowledgment, and policy response move at different speeds, and this gap will make the transition difficult.
AI agents embedded in foundation models are gradually displacing knowledge work, calling this process agentrification and linking it to superintelligence.
My doctoral and published research is in brain-inspired artificial intelligence. Here is what that means, in plain terms.
Most AI today is loosely modelled on the brain. Brain-inspired AI goes further, borrowing how real neurons communicate, learn and adapt over time.
Why it matters for leaders: it points to AI that learns continuously from less data and uses far less energy.
Instead of passing numbers continuously, spiking networks communicate through brief electrical pulses, as biological neurons do. Timing carries information.
Why it matters: they are well suited to signals that change over time, such as sensors, speech, physiological data and markets.
Hardware and software designed around the brain's architecture, processing information where it is stored rather than shuttling it back and forth.
Why it matters: it could make capable AI run on devices at the edge, with a fraction of today's energy cost.
How many specialised AI components, agents and people combine into systems that perceive, decide and act, and where those systems fail.
Why it matters: enterprise AI is becoming a system of agents, so governing the system matters as much as any single model.
AI progress should be judged not only by what systems can do, but by the outcomes they produce and how responsibly they are governed.
Whether an organisation can capture value from AI: strategy, data, processes, people, governance and financial measurement working together.
As AI moves from answering to acting, which decisions a machine may make, recommend, or never touch, and who remains accountable.
Judging AI by what it does to revenue, operating costs, capital and risk, at its full cost, rather than by how widely it is adopted.
Oversight, testing, monitoring and the ability to intervene, so that delegated decisions remain answerable to people.
These ideas inform three applied frameworks developed through Kiros Intelligence Group. The full assessments and calculators live on kiros-intelligence.com.
Brain-inspired AI, agency and the future of intelligence.
Which lines in the accounts can AI move, at what full cost?
Agent Value Ledger ↗Results tracked against the baseline, and reported honestly.
The newsletter archive by topic, the featured essay and published research.
Essays → 02Proposed topics for keynotes, board briefings and workshops.
Speaking → 03Strategic advisory for boards and enterprises, through Kiros Intelligence Group.
Advisory →