Artificial intelligence expected to have a bigger role in board decision-making.

    On paper, Artificial Intelligence (AI) and governance look like opposing ends of a spectrum. AI uses technology to make decisions mostly about routine tasks. Governance is an art that relies on people who use experience and instinct to make complex decisions.

    No computer could fully replace a director; no boardroom could be automated. But the intersection of AI and governance will be much larger – and sooner – than widely realised. Top boards will use AI not to replace directors, but as a tool to augment director decision making.

    Executive teams are increasingly harnessing the power of big data and AI to analyse large data-sets, so it makes sense that boards follow suit.

    Less considered is how directors can use AI within the boardroom to process larger data-sets, test management assumptions, run more scenarios around capital-allocation decisions and gain greater insight into real-time organisation culture.

    For now, boards of large organisations are more concerned about the impact of big data, automation and AI on their organisation and its industry rather than the boardroom itself. Forward-looking directors want to understand how AI could create opportunities and risks in their industry and disrupt the organisation.

    Less considered is how directors can use AI within the boardroom to process larger data-sets, test management assumptions, run more scenarios around capital-allocation decisions and gain greater insight into real-time organisation culture.

    The idea is not as far-fetched as it seems. AI is already influencing governance at the edges: machine-learning programs used to recruit directors; algorithms used in board decisions; and boards using big data in strategic decisions, for example.

    It’s early days, but as technology disrupts more industries, as the speed of global business increases, and as organisations become larger and more complex, human boards could struggle to keep up. Incorporating big data and AI into the boardroom, to supplement rather than replace human decisions, could redefine the nature of governance and aspects of corporate law.

    Director/CEO recruitment and AI

    Governance applications of AI are potentially widespread. Ohio State University researchers have examined whether algorithms can be used to select directors of publicly traded companies. A summary of their research was published by the Harvard Law School Forum on Corporate Governance and Financial Regulation in April.

    The researchers evaluated whether a machine-learning algorithm could forecast if an individual will succeed as a director; alternative approaches to forecast director performance using algorithms; and why directors who are counter to shareholder interest are chosen.

    Using publicly available data on firm, board and director characteristics, the researchers claimed their algorithm could accurately predict the success of individual directors. As well as those directors who were likely to be unpopular with shareholders.

    Unsurprisingly, the algorithm found that directors who are not old friends of management and come from different backgrounds are likelier to better monitor management – a point not lost on institutional investors who have argued for greater boardroom diversity.

    As director-selection algorithms become more advanced, and more data on directors is available, it’s possible that boards could use machine-learning tools in director-selection processes. A Chair who identifies a director for nomination could run that selection through an algorithm to identify if there is a large discrepancy between the human and computer view.

    The same technology, by extension, could be applied to CEO recruitment. Machine-learning programs scouring millions of executives worldwide and filtering it to a short-list of, say, five candidates who are the likeliest to succeed in the CEO role.

    Again, the technology is not replacing the human-compiled list or the interview process, but is another tool to test CEO recruitment – the board’s most important task. In time, such algorithms could extend to executive and board succession planning.

    ‘Robo’ directors

    Robotic directors are another consideration. Hong Kong venture-capital firm Deep Knowledge Ventures in 2014 appointed the world’s first robo director as a “board member with observer status”. The algorithm, named Vital, is analysing trends in life-science companies to predict successful investments.

    According to Deep Knowledge Ventures, Vital was appointed because of its ability to “automate due diligence and use historical data-sets to uncover trends that are not immediately obvious to humans surveying top-line data”. The potential to use AI in capital-allocation decisions made by boards, and to run more scenarios on different decisions, is enormous.

    More boards could introduce a robo director (presumably without requiring a shareholder vote) in coming years as other governance algorithms are created and back-testing shows they are a valuable addition for boards. Having a robo director working 24/7, in addition to part-time non-executive directors, could vastly expand board resources and monitoring.

    Risk management

    Boards could also use AI in risk-management oversight. Global accounting firms are investing in AI to automate routine functions in audit and other services and harness the power of data mining. It’s possible that algorithms could be used to continually monitor firm risk from the board’s perspective, providing real-time insight into current or future risk.

    As directors read hundreds of pages of board packs to understand organisation risk, algorithms could process millions of data points around identified or unidentified risks.

    In time, boards could spend more time assessing the algorithm’s risk-management advice rather than trying to identify risks from source material, which will become harder as the complexity and velocity of global business increases.


    Organisation culture and values are another potential AI governance application. High-performing boards monitor organisation-culture surveys and meet senior or front-line staff and suppliers to gauge firm temperature. Algorithms could analyse digitised communication within the organisation to gauge employee sentiment in real time.

    Just as global investment banks use algorithms to analyse CEO language in company announcements, so too could firms use technology to analyse employee language – in aggregated terms – to better understand the organisation’s values, ethics and culture.

    It’s possible that algorithms could predict Environmental, Social and Governance (ESG) issues within the firm through communication analysis. For example, whether an increase in employee turnover is likely because of deteriorating organisation sentiment. Or whether the risk of organisation fraud is rising because of inappropriate communication.

    Technology, of course, will never replace director instinct in gauging organisation culture, but boards need all the help they can get in understanding the organisation’s human capital and culture – factors that are continually shown to differentiate high- and low-performing organisations.

    Corporate reputation

    Governance AI could extend to corporation-reputation monitoring. As directors read analyst, industry and media reports to know what is said about the organisation, AI could analyse millions of comments about the firm in social media and elsewhere. Boards could use the technology to assess the organisation’s reputation in real time against against rivals.

    AI, of course, will pose many challenges for boards when it arrives in full force. Legal framework procedures would have to change to accommodate advice if robo directors are given equal voting rights with human directors.

    AI in the boardroom also challenges shareholder voting rights and numerous other policies and procedures based on the appointment of human directors. Then there’s the issue of boardroom composition and whether enough organisations have directors who understand AI and can embrace it. Directors with a strong background in data science – and the skill to govern across multiple aspects of business – are in short supply.

    The biggest challenge will be the balance between human and robo directors. If AI is shown to make better governance decisions over time than human directors, it’s possible that robo directors could have a bigger say. That might mean slightly fewer human directors and more governance robots that make decisions free of emotion, 24/7, and for a fraction of the price.

    Granted, it’s science fiction for now. But AI, data analytics and machine learning could knock on the boardroom door faster than the governance community expects.

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