Intuition automated: what do you need to do next?

Depending on a firm’s core competency, managers need to decide what AI strategy to pursue

PUBLISHED : Friday, 04 March, 2016, 10:01am
UPDATED : Friday, 04 March, 2016, 10:00am

Get ready for Man vs Machine round two this month. After Google’s self-learning algorithm AlphaGo, beat European champion Fan Hui by 5-0 at the game go, the world’s top player, Lee Se-dol, will now take on the computer.

An ancient Chinese board game, go is played on a 19-by-19 grid with black and white stones. It was long thought machines would never be able to win a game. Unlike the Western game of chess, where each move affords a maximum of 40 options, go entails up to 200 choices. The possibility of different outcomes quickly compounds to a bewildering range of 10170 – more than the total number of atoms in the entire observable universe. Most interesting is AlphaGo’s ability to autonomously improve performance and simulate what cognitive psychologists regard as human intuition.

Most interesting is AlphaGo’s ability to autonomously improve performance and simulate what cognitive psychologists regard as human intuition

Whether Lee will win this month is irrelevant; the fact that AlphaGo exists is a testament to the future of artificial intelligence (AI). Similarly, IBM’s Watson, hailed to be the first computer capable of understanding natural human language, has shown us just how AI can go beyond games and trivia. By devouring millions of pages of medical journals and patient data, Watson provides recommendations – from blood tests to the clinical trials available – to physicians. A cancer doctor, for example, only needs to describe the disease symptoms to Watson in plain English before getting a diagnostic suggestion.

The prospect of knowing people’s next desires and to deploy ever-smarter bots, a super Siri, or any automated messages, as a cheap alternative to customer service, is enough to tip any Fortune 500 company to leverage ever more AI. Still, not everyone is Google and IBM. Depending on a firm’s core competency, managers need to decide what AI strategy to pursue. Here are the three most pivotal questions.

1) Am I technology inventor, service provider, infrastructure builder, or product orchestrator?

We don’t need to reinvent the wheel. Facing the onslaught of AI, firms don’t need to (and shouldn’t) all compete with Google and IBM as a technology inventor. A company can specialise as a service provider that helps other clients to utilise third-party technologies better, by integrating them into a packaged solution for immediate deployment (e.g. a technology consultancy). Closely related to that is an infrastructure builder who owns and manages the physical infrastructure that facilitates better information and service exchanges (e.g. a telecoms carrier). And a product orchestrator must decide how to stitch all components together and deliver the ultimate offerings to end users in the marketplace (e.g. an equipment maker that mass-produce driverless tractors).

2) What new core capabilities must I develop?

Depending on the dominant role a company chooses to play, different kinds of capabilities revolving AI should be emphasised. A product orchestrator, for example, may choose not to build its own AI software; but it still needs to learn how to evaluate the prospect of competing software before committing to an overall product design. Equally important is the ability to ally with leading AI experts in order to stay “in the know”.

3) How do I make money?

There are two fundamental ways that AI can prosper and enterprise: adding value and lowering cost. On the revenue side, managers need to consider how AI can strengthen and protect existing offerings, or how AI might enable the company to enter new areas when the core business is in decline. On the cost side, AI may implicate an enormous redundancy of the current workforce. Either way, the existing business model may require a major overhaul. When facing these strategic choices, determining what not to do is just as critical as what to do next.

AlphaGo and Watson, in one sense, are mere early indicators of what the future may hold, with new possibilities beyond the realm of a human mind. As said by Mary Kay Ash, there are three types of people in this world: those who make things happen, those who watch things happen and those who wonder what happened. Let us not become the last.

Howard Yu is professor of strategic management and innovation at IMD in Lausanne