Just as the industrial age was heralded by a new type of industrial firm, so too the age of artificial intelligence is defined by the emergence of a new kind of company, says Marco Iansiti, Harvard Business School professor and co-director of the school’s Digital Initiative.
In the recently released book, “Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World,” he and co-author Karim R. Lakhani paint a picture of the digital firms that dominate this disruptive era, marked by both outsized risks and rewards. AI enables the massive, scale, scope, and learning potential that opens up a wealth of new opportunities for the digital enterprise, Iansiti says, but the possible downsides – from privacy concerns to algorithmic bias to wealth inequality – are equally enormous.
That’s why the age of AI demands a new kind of leadership, Iansiti says. Some time-honored assumptions simply no longer apply.
AI age puts new demands on leaders
“Traditionally, leaders have primarily focused on their own organizations and their various stakeholders, from stockholders to employees. Challenges were usually confined to industries and geographical boundaries,” Iansiti explains. “With our incredibly connected digital economy, leaders of digital firms need to understand the impact of their immensely scalable firms and the consequences of their actions for the large communities they are now shaping and influencing.”
For example, a decision that Facebook makes can impact billions of people. That necessitates raising the bar on the knowledge required to make good business decisions. “The breadth of consequences of leaders’ decisions is much greater,” Iansiti says. “Leaders should take note and develop the capabilities and outlook necessary to make wise choices.”
[ With all the AI hype, which trends really matter? Read also: 10 AI trends to watch in 2020. ]
Iansiti points to the importance of what he calls the leadership of collective wisdom. “It’s about companies taking more of a collective perspective when making decisions,” he explains. Ant Financial, for example, has close to 1.4 billion customers. “The impact is just unbelievable. That means that when making managerial decisions, a perspective on the entire ecosystem is essential,” Iansiti says. “The collective will define the sustainability of Ant’s business model and beyond. That means we need to embrace a different perspective when making decisions.”
Unfortunately, argue Iansiti and Lakhani in the book, for all the additional data organizations now have access to, there is a dearth of managerial wisdom. When algorithms are poised to take over more tasks and guide more decisions, wisdom means anticipating unintended outcomes. “Many of us were excited by the innovation that would be unleashed by opening up the Facebook platform. Very few of us were wise enough to understand the negative potential impact,” Iansiti says. “That was early, but now there is no excuse. We understand the potential negative impact of a digital firm and we must take the consequences of our decisions into wiser account.”
Ethical issues, from cybersecurity to algorithm transparency and clarity, are of particular concern for CIOs. “In each of these categories, ethical philosophy, managerial actions, and engineering details are intimately connected,” Iansiti says. “Think of defining and implementing a remedy to algorithmic bias. Even the very definition of what bias is is often in debate, let alone the engineering details of improving our systems to remove bias. CIOs are responsible for all of this.”
[ Ferret out bias: Read AI bias: 9 questions leaders should ask. ]
4 immediate opportunities for leaders in the AI era
In the book, Iansiti and Lakhani outline four areas of immediate opportunity that AI presents for today’s leaders to focus on as a start:
Transformation. “We don’t want a world that is limited to companies started in the last ten years,” Iansiti says. “More traditional organizations have much to contribute but they need to invest in changing their core.”
Entrepreneurship. AI offers the opportunity to explore seemingly infinite use cases never possible before to solve not just longstanding problems but concerns that digital scale and scope have created, like privacy or algorithmic bias.
Regulation. Iansiti argues for more regulatory innovation. “Traditional institutions need to focus much more on this class of problems and develop more sophistication – in areas ranging from philosophy to economics and from engineering to analytics – to develop effective and enforceable regulations,” he says.
Community. There is value in rallying the rest of us to become more engaged in how AI is applied to our lives. “How do you track and stand up to Trillion dollar companies? A few regulators are not enough,” says Iansiti. “We need billions of people connected together.
[ Read also: How big data and AI work together. ]
5 priorities for IT leaders in the AI era
Iansiti offers five pieces of advice for IT leaders charged with both capitalizing on and managing the risks of AI-enabled change:
1. Understand and actively anticipate the transformation of your economic and social environment. “Don’t be caught unawares,” he says. “There is no longer an excuse.”
2. Invest in operating model transformation. This is the necessary foundation for change, Iansiti notes. “Even modest investment has business benefits. Don’t wait to get started.”
3. Drive business model innovation. “Rethink your strategic options,” says Iansiti. “Even if you are an older firm, there are virtually limitless opportunities for new value creation and capture.”
4. Design ethical solutions from the ground up. This applies to both front-end and back-end AI-enabled transformation. “Take responsibility beyond growth and efficiency,” Iansiti warns. “Understand the potential downside and take a collective perspective.”
5. Take a collective view. “Support a multi-platform economy, understand regulatory options, and prepare for social impact,” Iansiti advises. “We are at the inflection point of a dramatic period of transformation. Let’s all work on this to make sure we land in a good place.”
[ Want a quick-scan primer on 10 key artificial intelligence terms for IT and business leaders? Get our Cheat sheet: AI glossary. ]
