Just as artificial intelligence is helping doctors make better diagnoses and deliver better care, it is also poised to bring valuable insights to corporate leaders—if they’ll let it.
At first blush, the idea of artificial intelligence (AI) in the boardroom may seem far-fetched. After all, board decisions are exactly the opposite of what conventional wisdom says can be automated. Judgment, shrewdness, and acumen acquired over decades of hard-won experience are required for the kinds of complicated matters boards wrestle with. But AI is already filtering into use in some extremely nuanced, complicated, and important decision processes.
Consider health care. Physicians, like executives and board members, spend years developing their expertise. They evaluate existing conditions and deploy treatments in response, while monitoring the well-being of those under their care.
Today’s medical professionals are wisely allowing AI to augment their decision-making. Intelligent systems are enabling doctors to make better diagnoses and deliver more individualized treatments. These systems combine mapping of the human genome and vast amounts of clinical data with machine learning and data science. They assess individual profiles, analyze research, find patterns across patient populations, and prioritize courses of action. The early results of intelligent systems in health care are impressive, and they will grow even more so over time. In a recent study, physicians who incorporated machine-learning algorithms in their diagnoses of metastatic breast cancer reduced their error rates by 85%. Indeed, by understanding how AI is transforming health care, we can also imagine the future of how corporate directors and CEOs will use AI to inform their decisions.
Complex Decisions Demand Intelligent Systems
Part of what’s driving the use of AI in health care is the fact that the cost of bad decisions is high. That’s the same in business, too: Consider that 50% of the Fortune 500 companies are forecasted to fall off the list within a decade, and that failure rates are high for new product launches, mergers and acquisitions, and even attempts at digital transformation. Responsibility for these failures falls on the shoulders of executives and board members, who concede that they’re struggling: A 2015 McKinsey study found that only 16% of board directors said they fully understood how the dynamics of their industries were changing and how technological advancement would alter the trajectories of their company and industry. The truth is that business has become too complex and is moving too rapidly for boards and CEOs to make good decisions without intelligent systems.
We believe that the solution to this complexity will be to incorporate AI in the practice of corporate governance and strategy. This is not about automating leadership and governance, but rather augmenting board intelligence using AI. Artificial intelligence for both strategic decision-making (capital allocation) and operating decision-making will come to be an essential competitive advantage, just like electricity was in the industrial revolution or enterprise resource planning software (ERP) was in the information age.
For example, AI could be used to improve strategic decision-making by tracking capital allocation patterns and highlighting concerns—such as when the company is decreasing spending on research and development while most competitors are increasing investment—and reviewing and processing press releases to identify potential new competitors moving into key product markets and then suggesting investments to protect market share. AI could be used to improve operational decision-making by analyzing internal communication to assess employee morale and predicting churn, and by identifying subtle changes in customer preference or demographics that may have product or strategy implications.
The Medical Model: Advances That Have Enabled AI in Health Care
What will it take for boards to get on board with AI supplements? If we go back to the health care analogy, there have been three technological advances that have been essential for the application of AI in the medical field:
- The first advance is an enormous body of data. From the mapping of the human genome to the accumulation and organization of databases of clinical research and diagnoses, the medical world is now awash in vast, valuable new sources of information.
- The second advance is the ability to quantify an individual. Improvements in mobile technology, sensors, and connectivity now generate extraordinarily detailed insights into an individual’s health.
- The third advance is the technology itself. Today’s AI techniques can assimilate massive amounts of data and discern relevant patterns and insights—allowing the application of the world of health care data to an individual’s particular health care situation. These techniques include advanced analytics, machine learning, and natural language processing.
As a result of the deployment of intelligent systems in health care, doctors can now map a patient’s data, including what they eat, how much they exercise, and what’s in their genetics; cross-reference that material against a large body of research to make a diagnosis; access the latest research on pharmaceuticals and other treatments; consult machine-learning algorithms that assess alternative courses of action; and create treatment recommendations personalized to the patient.
Three Steps Companies Can Take to Bring AI Into the Boardroom
A similar course will be required to achieve the same results in business. Although not a direct parallel to health care, companies have their own components—people, assets, history—which could be called the corporate genome. In order to effectively build an AI system to improve corporate decision-making, organizations will need to develop a usable genome model by taking three steps:
- Create a body of data by mapping the corporate genome of many companies and combine this data with their economic outcomes;
- Develop a method for quantifying an individual company in order to assess its competitiveness and trajectory through comparison with the larger database; and
- Use AI to recommend a course of action to improve the organization’s performance—such as changes to capital allocation.
Just as physicians use patient data to create individualized medical solutions, emerging intelligent systems will help boards and CEOs know more precisely what strategy and investments will provide exponential growth and value in an increasingly competitive marketplace. Boards and executives with the right competencies and mental models will have a real leg up in figuring out how to best utilize this new information. While technology is growing exponentially, leaders and boards are only changing incrementally, leaving many legacy organizations further and further behind.
It’s time for leaders to courageously admit that, despite all their years of experience, AI belongs in the boardroom.
Barry Libert is CEO of OpenMatters, a machine learning company, and a senior fellow at Wharton’s SEI Center. He tweets @barrylibert. Mark Bonchek is CEO of Shift Thinking and a faculty member at Singularity University. He tweets @markbonchek. Megan Beck is CIO at OpenMatters and a research fellow at Wharton’s SEI Center. She tweets @TheMeganBeck.
Originally appeared on MIT Sloan Management Review. Reproduced with permission from the author.