By Stuart Kerr, Technology Correspondent
Published: 24 July 2025
Last Updated: 24 July 2025
Contact: [email protected] | Twitter: @LiveAIWire
Author Bio: About Stuart Kerr
When an AI named "Mika" was appointed CEO of a Chinese gaming company in 2024, many dismissed it as a publicity stunt. But a year later, shareholders are listening more closely. With decisions made faster, supply chains optimised by algorithm, and employee feedback analysed in real-time, Mika isn’t the only synthetic boss quietly reshaping corporate governance. Welcome to the age of the algorithmic CEO.
Beyond the Boardroom Hype
AI has long supported back-end business operations — from accounting systems to customer analytics — but the latest evolution brings it to the top of the organisational chart. This isn’t about replacing leadership charisma with code; it’s about embedding pattern recognition, risk modelling, and data-driven objectivity into roles once defined by instinct and politics.
In some sectors, this shift is already visible. In HR, AI is transforming recruitment and retention strategy — as explored in The Last Recruiter. In finance, Code Capital details how algorithmic thinking now guides entire portfolio strategies. Bringing those same systems into executive decision-making feels like a natural — albeit controversial — progression.
When Bots Make the Call
One of the earliest known AI executives was appointed by Hong Kong–based venture fund Deep Knowledge Ventures in 2014. Their algorithm, named VITAL, had a voting seat on the board. A decade later, firms are experimenting with letting AI weigh in on product-market fit, marketing strategy, and even acquisitions.
Harvard Business Review notes that AI systems today often monitor KPI dashboards in real-time and flag leadership teams when strategic pivots are needed — long before quarterly reports would suggest the same. Meanwhile, Cooley PubCo outlines how AI is being used to assess board effectiveness, track compliance risk, and evaluate ESG strategies against investor sentiment.
But it’s not all progress and profit. A Lawfare analysis cautions that when governance becomes hybrid — with humans deferring key calls to opaque systems — accountability can evaporate.
The Risks of Executive Automation
There’s a difference between AI being consulted and AI commanding. The former makes sense in a data-rich world. The latter introduces issues of responsibility, transparency, and moral agency.
What happens when a CEO-AI recommends mass layoffs or closes a factory to boost quarterly margins? Is it just doing what it was trained to optimise? Who answers to displaced workers or regional governments?
This philosophical tension was explored in The AI Identity Crisis, where human agency becomes subordinate to models optimising shareholder value. The problem isn’t just that machines make decisions — it’s that their rationale may be inaccessible to those affected by them.
The Case for Hybrid Leadership
AI’s strengths in data synthesis, forecasting, and neutrality are clear. But executive leadership also requires emotional intelligence, vision, and the ability to handle nuance. As noted in the OECD’s report on Corporate Governance and AI, AI should serve as an advisor — not a replacement.
Boards must now draft clear policies around AI-assisted decisions, including limits on automated authority, human override thresholds, and audit trails for transparency. The Deloitte PDF on AI Governance provides a playbook for boards trying to navigate these uncharted waters.
Ultimately, the most successful companies may not be those with the smartest software — but those with leaders wise enough to know when not to listen to it.
About the Author
Stuart Kerr is the Technology Correspondent for LiveAIWire. He writes about artificial intelligence, ethics, and how technology is reshaping everyday life. Read more