Successful businesspeople celebrating with the cup in hands.
Much has been written recently about the impact that AI will have on global organizations — companies, governments, non-profits – and how organizations must prepare to manage these responsibilities. Artificial Intelligence is arriving rapidly, and organizations will be forced to adapt, whether they choose to or not. Mustafa Suleyman, author of The Coming Wave argues, “Within the next few years, AI will become as ubiquitous as the Internet”. JP Morgan’s Jamie Dimon calls AI “critical to our company’s future success” and adds that AI will eventually “be used in almost every job” at JP Morgan. Like it or not, the arrival of AI is inevitable, and organizations must find a pathway to adoption that fits their mission, capabilities, and culture.
As an advisor on data and AI to leading global organization for 30+ years, it is clear to me that successful adoption of AI will depend on a few critical factors. First, great AI will depend upon great data. Mustafa Suleyman notes, “Eighteen million gigabytes of data are added to the global sum every single minute of every day”. Those organizations that establish a strong data foundation will be best positioned to leverage the benefits of AI. Second, organizations must be honest about the cultural challenges that they face, including their willingness and readiness to undertake transformational efforts that will alter processes and require new skill sets. Finally, organizations must be realistic about past experience and learn from previous efforts to build data, analytics, and AI leadership functions.
History can teach us. Organizations need to recognize and appreciate their mixed record in building the data foundation and culture that is a prerequisite for maximizing organizational success. One long running survey of leading global organizations has shown that progress on data, analytics, and AI has come slowly for most. Even as organizations have embraced the arrival of Generative AI within the past year, half of organizations still report that they are not competing on data and analytics, not managing data as an asset, have not created a data-driven organization, and have not established a data, analytics, and AI culture. Further, more than three quarters of organizations continue to cite cultural obstacles as the greatest barrier to data, analytics, and AI success.
Past efforts to establish data leadership roles and responsibilities have met with mixed results. Although a few organizations had dabbled with the Chief Data Officer (CDO) role prior to 2008-2009, it was largely in response to the financial crisis of this period that the role was formally established. By 2012, only 12% of leading companies reported had established the CDO role within their organizations, and it was not until 2017 that this number surpassed 50%. Over time, responsibilities of the role expanded within many organizations to include analytics and AI. Although 83% of leading organizations now report having a Chief Data and Analytics Officer (CDAO), nearly half say that the role is still not successful and well-established, and continues to be characterized by a brief, uncertain tenure, with 6% saying that the role has been an outright failure.
With nearly two-thirds of leading organizations now reporting that Generative AI has the potential to be the most transformative technology in a generation, many organizations are reassessing whether there is a need for a separate and distinct AI leadership function. Although 61% of organizations report that Generative AI falls within the responsibilities of the CDAO, and 79% argue that it should be situated there, recent stories suggest that 11% of organizations have gone ahead and created a new role — the Chief Artificial Intelligence Officer (CAIO); 21% of organizations report that they are actively recruiting for the CAIO position. The New York Times published a recent lead story, Hottest Job in Corporate America? The Executive in Charge of AI. Boston Consulting Group (BCG) has weighed in with their perspective in a thought-piece entitled, Every C-Suite Member Is Now a Chief AI Officer. MarketWatch has added a further perspective in their story, Chief AI officer: A necessity for companies or an expensive impediment? We are at a critical juncture.
Global organizations are confronted with a potentially once-in-a-generation challenge, one with great opportunity as well as equivalent risks. Will organizations realize exponential productivity gains, elevate knowledge workers from mundane tasks, and improve customer satisfaction, or be hampered by threats of misinformation, ethical bias, and job displacement? What kind of data and AI executive leadership will be required to seize upon the opportunities, navigate the challenges, risks, and threats, implement the prerequisite safeguards and guardrails, and deliver transformational value to their organizations? I offer 3 suggestions.
First, make data and AI a business responsibility. Organizational reporting relationships continue to be a topic of ongoing debate. When the CDO/CDAO role was first established, it was mostly a defensive role focused on risk mitigation and compliance – ensuring that regulatory data reporting was accurate and complete. Over time the role evolved, with a greater focus on business outcomes such as revenue and customer growth. Success of the role and of its incumbents increasingly depended upon strong integration into organizational and business processes, strong partnership and collaboration with organizational and business leaders, and delivery of quantifiably measurable results. As the CDO/CDAO role has evolved, it has increasingly moved from being seen as primarily a technology and infrastructure role reporting to the Chief Information Officer (CIO), to a critical business role reporting to the CEO or COO, a pattern that has worked well for many of the most successful organizations.
Second, educate corporate boards on the opportunities and risks associated with AI. It has been noted that while over 95 percent of board members believe in the need for AI, just 28% of companies have made realistic progress. Further, there have been reports of misperceptions and misunderstanding by board members of their understanding of AI, its implications, and inherent risks. Organizations owe it to themselves to ensure that data and AI executive leaders are on the agenda to present regularly at board meetings — to educate the board, track progress, and highlight ongoing risks. It should be appreciated that AI continues to evolve at an accelerated pace and in this respect, we are all learning together. Board members, organizational leadership and data and AI leadership are in the same boat, where patience, commitment, and adaptability will be necessary to achieve the best outcome.
Third, plan for an AI future. Should organizations establish a Chief AI Officer role or situate AI responsibilities under the Chief Data Officer? It is likely too early to tell, and what works for one organization may not function best for another. What is less subject to debate is that for organizations to succeed in an AI future, they need to establish strong data and AI leadership quickly, in whatever form works best for that organization. The great news for data and AI leaders is that the demand for their skills and expertise will only increase. Although half of organizations continue to struggle, half of organizations have demonstrated success in integrating data and AI capabilities into their organizational processes and operations.
Mustafa Suleyman concludes, “We are going to live in an epoch when the majority of our daily interactions are not with other people but with AIs”. Jamie Dimon echoes this sentiment in his comments. This is what technological transformations have looked like throughout human history. Transformation brings disruption, and disruption can foster resentment and resistance. This is a challenge that data and AI leaders, and the organizations that they are a part of, can expect to face. We might not look forward to, or feel prepared for, an AI future. We might not like it. We might even resist it. But, like it or not, an AI future is coming. It’s not a case of if but a case of when. The arrival and enormous transformational impact of AI is inevitable. Now more than ever, global organizations will need strong data and AI executive leadership to navigate this future. Organizations best prepare.
