In the film Margin Call, the Jeremy Irons character outlines the crux of his job. “I’m here for one reason and one reason alone. I’m here to guess what the music might do a week, a month, a year from now. That’s it. Nothing more,” he explains.
This emphasis on strategy and big-picture thinking epitomises the modern view of leadership. This perhaps helps to explain the findings from a Germany study from a few years ago, which found that executives often eschew data when making decisions, preferring instead to rely on their instincts. After all, as Irons explains, that’s what they’re in the big job for.
AI age
If big data wasn’t able to penetrate senior decision-making, is AI faring any better? One study, from INSEAD, explored the use of AI to aid strategic decision-making. The researchers examined how strategies are formed in the private equity industry, where decisions are often extremely complex (and indeed, not dissimilar to those made by Irons’ character in Margin Call).
They found that after analysing around 60,000 deals, a clear pattern emerged, with deals often involving a co-investor that had clear expertise in so-called “add-on deals”, which are when the private equity firm acquires a company and then merges it with one already in its portfolio.
They also found that co-investors are often new participants in the pool of partners and are not among those who usually participate in leveraged buyouts. The researchers believe that new partners would be required to pursue add-on deals, which would make PE firms with a lot of existing partners slower to adopt add-on deals.
They argue that AI can be successfully deployed to help us not only think up new strategies but also think of those strategies in a new light.
The structure of decisions
Another study, from Wharton, explores how AI can impact the way in which decisions are made. The researchers examine the so-called “flattening”, whereby organisations strip out layers of middle management, and ponder how AI impacts the structure of decision-making within organisations that have gone through this process.
The study found that when firms are decentralised, AI is often used for tasks that can be defined as fairly stable. It’s deployed in a way that aims to improve operational efficiency and financial performance, while managers focus their energy on things like innovation.
By contrast, in more centralised firms, the use of AI tends to focus on less certain tasks, such as new product development. The aim in this instance is to reduce the firm’s reliance on middle managers and provide executives with more control.
The researchers found that as the level of automation increases, organisations tend to move towards a more centralised form of decision-making, which therefore diminishes the role of middle managers. This has a knock-on effect on things like innovation, where decentralised firms have an advantage due to their greater agility.
What’s more, the introduction of AI also runs the risk of reducing communication and decision-making precisely because it reduces the key role middle managers play in supporting the executive team in both formulating and administering strategic decisions.
Lack of flexibility
Research from Harvard Business School should also give executives pause for thought before they implement AI in the strategic process. The research focused on the kind of split-second decisions we all make throughout the day that humans are exceptionally good at. These tasks help us to orient ourselves before we get started and pivot whenever the circumstances dictate. It’s something that humans are good at, but technology isn’t.
If nothing else, Irons’ character was responding to a rapidly unfolding situation and had to make a decision extremely quickly. This is something the researchers believe humans remain far better than AI at doing. Instead, AI struggles to navigate evolving situations because it lacks both a degree of self-awareness and an understanding of its own capabilities.
So, while AI is finding its way into a growing number of use cases in organisations across the land, it’s perhaps reasonable to suggest that its role in the boardroom should be limited at least until it proves itself more capable at dealing with the kind of unexpected events that so often drive strategic decision-making. The Harvard researchers believe its beholden on managers to fully appreciate when using AI might provide valuable assistance and when its likely to lead them astray.
“In any sort of changing environment setting—like shifting between different workflows, providing personalized care to a wide range of patients with various problems, or the example of an automated vehicle having to respond to changing environments—this is where humans are going to shine more than automation systems,” they conclude. “If you more deeply understand why your AI systems are limited, you are probably better equipped to know when and how to deploy them in practice.”
