AI: Exploiting uncertainty, redefine organizational governance
We live in "an era of mass extinction". According to tech-entrepreneur Thomas Siebel, close to half the companies in existence today are likely to disappear within ten years. Generative AI offerings such as ChatGPT4 will only accelerate that trend. Boards are now challenged to re-evaluate their purpose, relevance, and capabilities to survive in the age of AI.
Historically, every leap in technology has eventually challenged organizational designs. Current trends are tech-empowering frontline workers(öffnet im neuen Fenster) to self-organize(öffnet im neuen Fenster), thereby creating more flattened and distributed organizational structures. However, given the impending AI-fueled transformation, the majority of knowledge jobs at the frontlines are likely to be either automated or disappear altogether within the next 10-15 years. In the absence of deep AI understanding to supervise, manage, and complement AI technologies, no knowledge worker will survive. The CEO and the board of directors are equally challenged.
We tend to assume that innovation and transformation are all about CEO leadership when it is increasingly a matter of organizational governance(öffnet im neuen Fenster). Management cannot do it alone. To take an extreme example, Google's executives were so flummoxed by ChatGPT's threat to its $150 billion search business that they called back the company's founders. Directors must now work with owners and executives to re-define corporate governance for the AI age.
What Boards can do
As AI decouples prediction from judgment, human judgment is becoming more important(öffnet im neuen Fenster), and companies will need to enhance the "smarter human, smarter machine interface" by decentralizing decision-making power towards the frontlines. The board must redefine its fiduciary duties accordingly, and Vijay Govindarajan's Three Box Solution(öffnet im neuen Fenster) – preservation, destruction, and growth – may pave the way.
(1) Preservation - Integrate AI expertise at the board level. The board's traditional supervising and advising responsibilities must now encompass ethical, regulatory, and safety reviews of algorithms. As algorithms become more powerful and potentially harmful, boards must enhance their expertise in this area, perhaps through an AI-dedicated board committee with access to specialist knowledge outside the firm. Overall, we should anticipate more government regulations in this area, expanding the board's compliance mandate. Currently, boards are ill-equipped to meet this challenge, often lacking cognitive diversity and critical reflection capabilities in these emerging areas.
(2) Destruction - Eliminate structures and conventions that bury uncertainty. Organizational frameworks such as rule catalogues, hierarchical decision-making, best practices and perhaps CEO dominance, for instance, may have been sensible in earlier decades. However, they could now foster inertia and prevent the organization from embracing the uncertainty companies need to thrive. Uncertainty is the fuel to optimize prediction models. The faster prediction models can be tested and improved under uncertainty, the better their predictions, making a firm's future less uncertain. Uncertainty thus becomes the source of collaborative advantage. Indeed, embracing uncertainty requires dismantling a mindset resistant to uncertainty that still prevails both in the boardroom and among corporate leaders.
(3) Growth - Mobilize for extensive upskilling with fluid top-down/bottom-up connectivity. First, boards can promote AI-driven up-skilling(öffnet im neuen Fenster) across the entire organization, without waiting for the CEO to act. This can be achieved, in part, by advocating for dedicated HR staff to conduct training and raise awareness regarding the threats and opportunities AI presents to individual tasks and jobs across the firm. Second, as AI is only as good as the underlying data is relevant, boards must assess business models and strategies to optimize access to quality data. Business model innovation will now also serve the purpose of acquiring new and pertinent data.
Third, the board must insist that management articulates and communicates strategy with an eye to prediction models to generatively minimize errors through action-based (and increasingly machine-generated) feedback loops. The AI-driven company requires leaders to develop a new language to empower frontliners with AI, learn to think probabilistically, and embrace bottom-up data to challenge predictions. In fact, boards must assess a CEO's AI readiness and judgment by the person's active enthusiasm for being proven wrong to generatively improve prediction models.
Promising Areas
As of yet, only a few boards have started considering and working on these dimensions, and we have no examples yet that can be comprehensively profiled. One promising practice that may impact all three dimensions is the use of so-called shadow boards. Young, talented high-potentials below the senior level hold meetings with and without the regular board, using the same agenda as well as defining future agendas.
Shadow boards, as analyzed by IMD's Jennifer Jordan(öffnet im neuen Fenster), prove helpful for companies like Prada, Gucci and Accor Hotels. Not only does the board gain insight into the perspective of younger employees, who often know more about emerging areas and trends than their elders, but the practice can also identify opportunities and threats early on, making them available for building better prediction models. More importantly, shadow boards can now serve as a powerful tool closer to the frontlines for mobilizing AI upskilling, reviewing future data strategies, and cultivating language and thinking in terms of prediction models to better harness the predictive learning power of AI.
The greater the opportunity for systemic impact, the more significant the board's role is to ensure a holistic approach and continuity beyond the CEO. In the U.S., for example, several advanced hospitals such as Mayo and Cleveland Clinic are discovering that task-specific AI empowerment in radiology analytics, for example, has repercussions far beyond the radiology department, affecting their entire value chain.
Singapore's DBS, for example, invested heavily in AI and has already transitioned from laggard to Southeast Asia's leading bank. It now employs more data scientists than bankers. Its Group-CEO, Piyush Gupta, has strong roots in technology. However, as as crucial as a tech-savvy CEO is becoming, it remains uncertain how DBS' AI-fueled reinvention will continue and accelerate beyond Gupta without a board taking the steps outlined above.
The Challenge with Boards
Why aren't boards further along in this? Do boards themselves genuinely want to step up? Do CEOs have any interest in boards stepping up? These are pertinent questions, and the answers will vary individually and by company. The more senior and broadly active the directors, the more likely they are to rely on generic compliance formulas and best practices to assess management.
Despite all the talk about the "revolt in the boardroom," directors have collectively -perhaps not individually- become estranged from innovation. In their inaction, they have inadvertently reinforced the CEO's dominance and potentially fostered inertia. On the CEO front, truly great leaders want a board that can make their performance stronger and more sustainable. However, CEOs have no time and attention left to upskill the board.
The future of AI governance(öffnet im neuen Fenster) is holistic. Fundamentally, it entails a cultural shift that cannot be left to executive leadership alone. It begins with owners and the board. Private equity-sponsored governance models(öffnet im neuen Fenster) and, to some extent, family-controlled businesses turned the board into a productive force long time ago. However, the publicly listed corporation seems more vulnerable than ever, and its eclipse(öffnet im neuen Fenster) is more real today. Companies will need directors that go beyond their fiduciary duty of oversight and are empowered and skilled to actively and holistically support the AI-driven transformation.
Dr. Daniel Bijan Khezri is Chairman of KCRI (Khezri Capital Research International) AG (Switzerland), a governance and investment partner; owner and CEO of Marquard Group (Switzerland); and advisor to leading family offices. He is the book author of 'Governing Continuous Transformation: Re-framing the Strategy-Governance Discussion' (Springer, 2022).
Prof. Dr. Oliver Gassmann is Chairman of the Institute of Technology Management and of the Global Center for Entrepreneurship and Innovation at the University of St. Gallen. He is one of the most cited innovation scholars, author of The Business Model Navigator, and serves on several boards.