In the hot seat: Are CEOs ready to decide who ‘owns’ AI?

The recent rise of artificial intelligence (AI), particularly Generative AI (GenAI), and the explosion in excitement around its potential is transforming boardroom discussions and reshaping business investment strategies across industries. So, do we need a Chief AI Officer?

As AI technologies demonstrate their potential to drive efficiency, innovation, and competitive advantage, corporate boards are increasingly recognizing the strategic importance of integrating AI into their decision-making processes. This shift is evident as companies allocate more resources to AI initiatives, aiming to harness data analytics, machine learning, and automation to optimize operations and enhance customer experiences.

What marks GenAI out as different to technological revolutions of the past is that it is universal – across all business functions, reshaping how companies operate, how they organise across People, Processes, and Platforms, what they do, and how they do it.

But the technology is emerging, and the entire world is working to figure out how to leverage it for growth, whilst mitigating the risks. And in this context, it is a fair question to ask whether there should be, short term at least, a specific focus on AI at board level, and if so, should it be a specific seat?

An open question: Do we need a Chief AI Officer?

What is also important to note is the people on the Boards, across industries and geographies, ​start from differing levels of technological understanding. And with a business transformation that itself is so technical, where even the technologists themselves are struggling to explain how it works, what will this mean for organisational governance, for accountability, for executive control, and for decision making?  Should AI have a specific place on the board; A Chief AI officer? Or given its universality, how should companies proceed?

The situation at the moment: CEOs need to decide, but they start from different bases

Whilst it is true that the skills of an experienced CEO can travel across sectors and geographies, it is also true that sector knowledge remains one of the most important qualifiers of success.

Proprietary research undertaken by Portera shows that the background of CEOs varies by sector. It is somewhat unsurprising to see that in Engineering or Technology companies, CEOs are more likely to come from a technical or Engineering background. Contrast this with Consumer Goods, or Telco, where CEOs are far less likely – almost unlikely – to have a scientific or technical background.

Research undertaken by Portera Research Lab shows that the likelihood of CEOs to come from a technology or science background (shown in red above) varies significantly across sectors. Most common in Auto and Tech firms, but almost absent in Telcom and CPG sectors.

It’s a given that the role of CEO is to surround oneself with expert and talented people, but AI and Corporate Governance presents a unique challenge, and one that will sit with the CEO to decide – what is the appropriate governance, and where does accountability sit?

The problem with autonomy, and the pressure on the CEO

We are already at a point where machine learning, deep learning, and generative AI technologies are performing actions that humans can’t fully explain. As AI advances, and AI works with AI to drive innovation and new services/outcomes, we will be increasingly met with situations where outcomes are derived autonomously. It will train itself more effectively, make better predictions and recommendations. And take better actions.

When this works well, it is the much trumpeted ‘efficiency’, ‘innovation’, and ‘advancement’ that AI promises. But Corporate Governance isn’t required for the ‘happy path’, it is there to plan for and manage the ’unhappy path’. What happens when things go wrong? What if – in spite of the best risk analysis, safety checks, and procedures in place – the actions taken don’t align with the operations, with safe processes, with the company policies, with ethics or values? Even the 1-in-a-million event… where the organisation didn’t even know if the risk existed in the first place. Who is accountable? How do we administer responsibility when things go wrong?

Imagine two situations. The first is the obvious, dare I say it “AI” example: A warehouse worker is hospitalised by a rogue autonomous vehicle being coordinated by an autonomous inventory management system responding autonomously to a surge in orders… which are probably placed automatically… I mean autonomously… by domestic IOT devices. Indeed, it is an ice cream manufacturer and it is warm outside. The systems failed, an injury occurred (autonomously), but the company is liable.

But what about the unforeseeable result of autonomous AI, like the current class action against UnitedHealthcare and its “nH Predict” AI algorithm, or Amazon’s Recruitment algorithm potentially favouring men over women for technical jobs? When we don’t know what we don’t know, how is accountability to be administered, and how does the CEO apportion responsibility (so that the buck doesn’t stop with them)?

AI Governance and the key decision for CEOs

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The answer is not quick and easy, and can’t be written in this article, but it is about Governance. Our consultants are actively working with legal firms, and corporations, to shape a global organisation and governance model across people, processes, and platforms. It is holistic in its domain definition to cover the entire technology, data, and operations landscape, and yet specific enough to drive responsibility and accountability throughout the organisation.

It is also true that the answer varies between businesses, and across sectors. Businesses that have data and technology at their core are simply better organised as a starting point to integrate AI into their standard operating procedures. Consumer goods and Telecoms businesses have further to go.

The time is ticking, with 40% of companies having operational AI, and 40% in pilot phases at the time of writing. And the adoption of AI will grow further, becoming a dominant means of undertaking business operations – be that in the marketing team or on the factory floor.

Arguments for and against businesses creating a board position focused on AI:

Circling back on the core question in this discussion… do companies need a Board level AI owner?

The below is what ChatGPT has to say on the matter – a typically comprehensive and broad, balanced set of pros and cons.

Arguments for:

1. Strategic Integration: An AI-focused board member can help integrate AI into the core strategy of the company, ensuring that AI technologies are leveraged to enhance business operations and create new revenue streams​
2. Innovation and Competitiveness: AI can drive significant innovation across various sectors. A dedicated AI position can keep the company at the forefront of technological advancements, ensuring it remains competitive in an increasingly AI-driven market​
3. Risk Management and Ethical Oversight: AI comes with numerous ethical and legal challenges, such as bias in algorithms and data privacy concerns. An AI expert on the board can help navigate these issues, ensuring responsible and ethical use of AI technologies​
4. Enhanced Decision-Making: AI can provide advanced analytics and insights, improving decision-making processes. A board member with AI expertise can facilitate the adoption of AI tools that enhance business intelligence and operational efficiency​
5. Regulatory Compliance: With increasing regulations surrounding AI, having an AI expert on the board can help ensure that the company stays compliant with current laws and anticipates future regulatory changes​
6. Enhanced Supply Chain Efficiency: AI can significantly improve supply chain operations by predicting demand, optimizing inventory, and reducing waste. A dedicated AI expert can drive these efficiencies, ensuring cost savings and better resource management​
7. Personalized Consumer Engagement: AI enables more personalized marketing and consumer engagement through data analysis and machine learning. A board member focused on AI can spearhead initiatives that leverage consumer data to create tailored marketing strategies, improving customer satisfaction and loyalty​
8. Product Innovation: AI can analyze market trends and consumer preferences to inform new product development. An AI-focused board member can help identify opportunities for innovation, ensuring that the company stays ahead of market trends and consumer demands​
9. Quality Control: AI technologies such as computer vision and predictive analytics can enhance quality control processes, reducing defects and ensuring product consistency. A board position focused on AI can oversee the implementation of these technologies, improving overall product quality​
10. Competitive Advantage: As the CPG industry becomes increasingly competitive, leveraging AI can provide a significant edge. A dedicated AI board member can ensure the company remains at the forefront of technological advancements, differentiating it from competitors​

And against…

1. Resource Constraints: Allocating resources to create a new board position might be challenging, especially for smaller companies. It may divert resources from other critical areas of the business​
2. Integration Difficulties: Embedding AI into existing processes and culture can be complex. A top-down approach driven by a board member might face resistance and practical implementation challenges​
3. Overemphasis on AI: A dedicated AI board position might lead to an overemphasis on AI at the expense of other important business areas. It’s essential to balance AI initiatives with other strategic priorities​
4. Evolving Technology: The rapid evolution of AI technology can make it difficult for a single board member to stay current with all developments. This can lead to outdated strategies and misaligned AI initiatives​
5. Overlap and Redundancy: AI initiatives can often be integrated within existing roles and departments. Creating a separate board position may lead to redundancy and overlap with the responsibilities of other executives and departments
6. High Implementation Costs: Implementing AI solutions can be expensive, requiring substantial investment in technology and talent. Smaller CPG companies might find it challenging to justify these costs, especially if the return on investment is uncertain​
7. Cultural Resistance: Integrating AI into traditional CPG operations might face resistance from employees accustomed to legacy systems. A top-down approach driven by a board member could exacerbate this resistance, making it difficult to achieve buy-in across the organization​
8. Data Privacy Concerns: Using AI to analyze consumer data raises privacy and ethical issues. A board position focused on AI must navigate these concerns carefully, balancing innovation with compliance and ethical considerations​
9. Risk of Over-reliance: Over-reliance on AI might lead to undervaluing human judgment and creativity. In the CPG industry, where consumer preferences and market trends can be highly nuanced, a balanced approach that integrates AI with human insights is essential​
10. Evolving Technology: AI technology is rapidly evolving, and keeping up with the latest developments can be challenging. A single board member might struggle to stay current, leading to strategies that quickly become outdated​

Portera’s assessment

ChatGPT provides useful context. But what’s the answer? Whilst being broadly right, we can still be precisely wrong.

In previous periods of transformation where a new technology or innovation came to the fore, there is precedent for having ‘Chiefs’ of that thing. We have Chief Data Officers, Chief Digital Officers (and last time I checked, data tends to be digital or at least it overlaps), and Chief Information Officers (who use data and digital channels) etc etc. The point here is that with ownership comes focus and accountability.

AI needs focus and attention. It needs the entire Board to become experts in AI within their disciplines. But lessons of corporate governance and accountability need to be learned; here specifically I am referring to the ongoing issue in many organisations over the lack of Data ownerships within the organisation (many people in many organisations all think they ‘own’ the data). This problem still persists, and the same ‘arms race’ to bring the best AI innovation will inevitably lead to confusion and risk in organisations, and that will land at the CEOs desk.

One person needs to have the mission and empowerment to drive successful adoption of AI across the organisation.  And they need to be on the Board. On the day-to-day implementation, it is likely the COO will be responsible for the AI workforce in their own territory, similarly across the other functions too e.g. CHRO, CMO etc, but having an AI board member who brings together these departmental agendas, drives the data and performance story, chairs AI Board meetings, and answers AI-related questions on the spot is an important immediate need, and one that should be filled.

Maybe this won’t be the case in 10 years’ time… but then again, we still have Chief Digital Officers, so I won’t be holding my breath.