Why CEOs and Corporate Boards Can’t Afford to Get AI Governance Wrong

Absent of any useful precedent, CEOs and corporate boards are struggling to land on the right AI governance model for the organization. Companies that continue to operate without a clear plan do so at the risk of being bypassed by those already taking confident steps forward.

CEOs and their boards have good reason to be both excited and concerned about the ways that Artificial Intelligence (AI) can transform their companies for decades to come. An annual benchmark survey conducted by one of this article’s authors found that 64.2% of business leaders believe that generative AI (GenAI) has the potential to be the most transformative technology in a generation.

The same survey found that although initial preparations are underway, progress remains at an early stage for most organizations. While 89.6% of executives reported that corporate investments in AI were increasing, just 62.9% said that the necessary safeguards and guardrails were in place for the use of Generative AI today. Further, only 50.5% said that the necessary talent was on board to ensure responsible implementation, and just 4.7% claimed that Generative AI applications had been implemented in production at scale.  

A 2024 “From Potential to Profit with GenAI” survey by Boston Consulting Group (BCG) reinforces the potential of AI, as well as the uncertainty. The survey of 1,400+ C-suite executives finds that 90% of business leaders are pursuing limited experimentation, and that, “While almost all executives now rank AI and GenAI as a top-three tech priority for 2024, 66% of leaders are ambivalent or dissatisfied with their progress on AI and GenAI — and only 6% have begun upskilling in a meaningful way.”

BCG’s newly-published “AI at Work 2024” survey reinforces the view that most organizations remain at an early stage when it comes to the establishment of AI processes and training of employees. Just 28% of respondents report that they have undergone any level of upskilling to prepare for an AI future. And while 84% of those surveyed report productivity gains and 83% reported improved speed using AI, just 36% report having integrated GenAI into their business processes.

It should not come as a surprise that adoption of transformational technologies like AI have historically played out over decades, not years. As with any technology seen to have a transformational impact, anticipation ranges from exuberance to apprehension. While 49.1% of business leaders see an opportunity to achieve exponential productivity gains, 44.3% fear the spread of misinformation or disinformation.

AI governance must be the responsibility of the entire C-Suite

So, how can business leaders establish AI governance structures to ensure innovative and safe adoption of AI within their organizations? What steps can they take today to ensure that preparations are underway, processes in place, education started, people are ready, and responsible safeguards and protections are being implemented? How do they ensure responsible adoption and integration of AI into the processes of an organization?

CEOs and boards must ask whose responsibility it is to guide the implementation of AI in the organization. Should it be concentrated under one role or one part of the organization, or should it be dispersed? How might this vary from one organization to another?

The first step in preparing for safe and successful AI adoption is establishing the necessary C-Suite governance structures. This needs to be a point of urgency, as far more advanced and powerful AI capabilities, including Artificial General Intelligence (AGI), where AI may be able to perform human cognitive tasks better than the smartest human being, loom on the horizon.

BCG published a leadership report earlier this year entitled “Every C-Suite Member Is Now a Chief AI Officer.” The report identified AI responsibilities at every level of corporate management, beginning with the Board and CEO, CIO, CDAO, including corporate risk, finance, HR, and marketing functions. 

Based upon our extensive AI and data advisory leadership experience and counsel to Fortune 1000 and Global 2000 firms worldwide, we outline here our prescription for establishing necessary AI governance:

1. Start with the Corporate Board and Chief Executive Officer (CEO)

Corporate leadership and boards must determine how best to manage the risks and opportunities presented by AI to serve its customers and to protect its stakeholders.  To begin with, they must identify where management responsibility should sit, and how these responsibilities should be structured.

BCG’s report states that from the CEO on down, there needs to be at minimum, “a basic understanding of GenAI, particularly with respect to security and privacy risks,” adding that business leaders “must have confidence that all decisions strike the right balance between risk and business benefit.”

Last year, one of us published an article, “How Should Corporate Boards Be Thinking About Generative AI?” The premise of the article was that “The emergence of generative AI presents corporate boards of directors with a present-day challenge.” Ash Gupta, the former and longtime Global President of Risk and Information Management for American Express, commented, “Catastrophic mishaps can happen if your people and processes are not adequately trained. Effective implementation will require both technical and leadership understanding.”

2. Empower the entire C-Suite leadership team

For any organization to be successful in governing AI, success will ultimately depend upon the establishment of a corporate mandate that starts with corporate leadership and the board and must be communicated and orchestrated at all levels within the organization on down.

When corporate data leaders and Chief Data and Analytics Officers (CDAO), were asked where responsibility for generative AI should reside, 79.4% responded that it should sit under the CDAO, with 74.8% seeing the role as a business function. This should not be surprising. If it was not well understood before, it should be appreciated now more than ever that successful AI depends upon successful data.

The BCG report notes that it will be “incumbent on each C-suite member to climb the GenAI learning curve in his or her area of responsibility so that top executives can manage implementation in an informed and thoughtful manner with customer trust, resilience, and safety front of mind.” The report concludes, “all C-suite members need to climb the GenAI learning curve.” These functions include risk, human resources, marketing, and finance, among other C-Suite roles.

Earlier this year, JPMorgan announced that its Chief Data and Analytics Officer, Theresa Heitsenrether, would sit on the bank’s operating committee reporting directly to CEO Jamie Dimon, “to keep up with ongoing AI investment and implementation bankwide.” This is an example of developing a clear plan for AI governance.

3. Ask whether you need a Chief AI Officer (CAIO)

A recent article in CIO Magazine found that 21% of companies were looking to add a Chief Artificial Intelligence Officer (CAIO) to their IT leadership team.  A New York Times article from earlier this year, Hottest Job in Corporate America? The Executive in Charge of AI, quoted one of the co-authors here as commenting, “Organizations want to say, ‘Yeah, we have a chief AI officer,’ because that makes them look good.”  This is not meant to minimize the role, but to say that business leaders need to think through their AI management plan and act wisely.

In recent months, industries such as the U.S. Federal Government have mandated the hiring of Chief AI Officers. Each organization must come to their own conclusions about how to optimize governance of AI in the C-Suite, but a case can be made that the sets of issues surrounding AI adoption, from minimizing risk, to establishing safeguards, to using AI to improve productivity customer service can justify establishing a new and focused role, even if that role is transitional.

What will set the winners in AI apart?

BCG’s survey concludes, “Winners invest in productivity and topline growth”, noting that, “Of the companies that expect to see cost savings from AI and GenAI in 2024, roughly half anticipate more than 10% in cost savings.” The survey continues, “Organizations that plan to invest more than $50 million in AI/GenAI next year are 1.3 times as likely as their peers to expect cost savings in 2024—and 1.5 times as likely to anticipate more than 10% in cost savings.” 

Transformational change is never easy. Each organization must ultimately make their own determination of what organizational and reporting structure best meets their needs based on factors including their industry, company culture, innovation profile, ability to manage change, and the ability of the organization to serve its customers in a responsible manner that improves the customer experience.

We are still in the very early days of the AI future — The time to act is now. CEOs and Corporate Boards can’t afford to get AI governance wrong.

About the Authors

Randy Bean is the author of Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI, and a contributor to MIT Sloan Management Review, Forbes, and Harvard Business Review.  He has been an advisor to Fortune 1000 organizations on data & AI leadership for 3+ decades.

Vlad Lukic is Managing Director and Senior Partner at Boston Consulting Group (BCG), where he is the global leader of the Technology & Digital Advantage Practice.  He has worked with leading organizations to accelerate the successful delivery of large-scale, end-to-end tech and digital transformations.

Marc Schuuring is Managing Director and Senior Partner at Boston Consulting Group (BCG), where he is the leader of the BCG Data & Digital Platform (DDP). He has over 28 years of professional experience in technology enabled strategies and transformation, and transformation of the core IT of large companies.

Lucas Quarta is Managing Director and Partner at Boston Consulting Group (BCG), focusing on data and analytics, and is a core member of the Data & Digital Platform leadership. He is co-global leader for data governance & data strategy, working with clients to shape the Chief Data & Analytics Officer agenda, and was formerly a CDO at BNP Paribas.