Investors should pay more attention to AI firms’ corporate governance
Such companies are often young and founder-led
FOR decades, stockbroking research has been dominated by financial assessment, whereby analysts scrutinise revenue growth, earnings trends, balance sheets and valuation multiples before arriving at a recommendation.
Yet, one of the most important determinants of long-term shareholder value often receives only passing attention: corporate governance.
This has long been a blind spot in investment analysis. It could become significantly more problematic as artificial intelligence companies occupy a larger share of public markets, especially since many AI plays lack decent track records of financial performance.
True, such firms can be highly innovative and create enormous value.
But a company can report impressive revenue growth and strong earnings momentum while hiding governance weaknesses beneath the surface, such as concentrated voting rights, dominant founders, limited board independence and substandard internal controls.
In these instances, questions such as whether independent directors are genuinely autonomous, whether executive remuneration is aligned with shareholder interests, whether disclosures are timely and meaningful, and whether boards possess the right expertise take on greater significance.
Consider that history suggests governance failures can destroy shareholder value far more quickly than deteriorating financial performance.
Enron, infamously, went from a company trading at 55 times its earnings to a bankrupt one in a few months, partly because of governance breakdown.
Consider also that many AI companies are relatively young, founder-led businesses operating in rapidly evolving markets. Their valuations are often based less on current profitability than on hugely inflated future expectations.
The rise of AI also introduces an additional layer of complexity because investors are no longer simply evaluating products and services.
Instead, they must also assess issues such as data sovereignty, cybersecurity, intellectual property rights, model integrity, regulatory compliance and ethical safeguards. These are governance matters as much as they are operational ones.
Investors are therefore being asked to place a substantial degree of trust in management teams and boards – a confidence which may prove wholly unfounded.
When problems eventually emerge, investors often discover that the warning signs were present all along, but were largely ignored because the focus was on financial metrics.
Financial models no longer sufficient
Ironically, the growing use of AI within the investment industry, much espoused for increasing efficiency, could make the problem worse.
True, the technology is becoming highly effective at analysing financial statements, identifying trends and generating research summaries.
But assessment of governance standards requires judgment, scepticism and human experience, and hence may receive less attention rather than more.
If anything, a stronger governance lens is needed in this milieu, because investors need to understand not only how quickly a company is growing, but also how responsibly it is being managed.
This has implications for Singapore’s efforts to deepen and broaden its equity market. Initiatives such as the Equities Market Development Programme aim to expand research coverage and attract investor interest.
As AI transforms industries and reshapes capital markets, the best analysts may not be those who build the most sophisticated financial models, but those who ask the most important governance questions. That is a lesson the domestic financial institutions needs to absorb.
Analysis, not just of numbers but also governance standards, is not always easy. But it could help differentiate genuinely well-run companies from those that merely sell a compelling growth story.
