Companies new to the space can learn a great deal from early adopters who have invested billions into AI and are now beginning to reap a range of benefits.
Here is a brief excerpt from an article written by Jacques Bughin, Eric Hazan, Sree Ramaswamy, Michael Chui, Tera Allas, Peter Dahlström, Nicolaus Henke, and Monica Trench for the McKinsey Quarterly, published by McKinsey & Company. To read the complete article, check out other resources, learn more about the firm, obtain subscription information, and register to receive email alerts, please click here.
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After decades of extravagant promises and frustrating disappointments, artificial intelligence (AI) is finally starting to deliver real-life benefits to early-adopting companies. Retailers on the digital frontier rely on AI-powered robots to run their warehouses—and even to automatically order stock when inventory runs low. Utilities use AI to forecast electricity demand. Automakers harness the technology in self-driving cars.
A confluence of developments is driving this new wave of AI development. Computer power is growing, algorithms and AI models are becoming more sophisticated, and, perhaps most important of all, the world is generating once-unimaginable volumes of the fuel that powers AI—data. Billions of gigabytes every day, collected by networked devices ranging from web browsers to turbine sensors.
The entrepreneurial activity unleashed by these developments drew three times as much investment in 2016—between $26 billion and $39 billion—as it did three years earlier. Most of the investment in AI consists of internal R&D spending by large, cash-rich digital-native companies like Amazon, Baidu, and Google.
For all of that investment, much of the AI adoption outside of the tech sector is at an early, experimental stage. Few firms have deployed it at scale. In a McKinsey Global Institute discussion paper, Artificial intelligence: The next digital frontier?, which includes a survey of more than 3,000 AI-aware companies around the world, we find early AI adopters tend to be closer to the digital frontier, are among the larger firms within sectors, deploy AI across the technology groups, use AI in the most core part of the value chain, adopt AI to increase revenue as well as reduce costs, and have the full support of the executive leadership. Companies that have not yet adopted AI technology at scale or in a core part of their business are unsure of a business case for AI or of the returns they can expect on an AI investment.
However, early evidence suggests that there is a business case to be made, and that AI can deliver real value to companies willing to use it across operations and within their core functions. In our survey, early AI adopters that combine strong digital capability with proactive strategies have higher profit margins and expect the performance gap with other firms to widen in the next three years.
This adoption pattern is widening a gap between digitized early adopters and others. Sectors at the top of MGI’s Industry Digitization Index, such as high tech and telecoms or financial services, are also leading AI adopters and have the most ambitious AI investment plans. These leaders use multiple technologies across multiple functions or deploy AI at the core of their business. Automakers, for example, use AI to improve their operations as well as develop self-driving vehicles, while financial-services companies use it in customer-experience functions. As these firms expand AI adoption and acquire more data, laggards will find it harder to catch up.
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Here is a direct link to the complete article.
Jacques Bughin is a director of the McKinsey Global Institute, Michael Chui is an MGI partner, and Tera Allas is an MGI visiting fellow; Eric Hazan is a senior partner in the Paris office; Sree Ramaswamy is a partner in the Washington, DC, office; Peter Dahlström and Nicolaus Henke are senior partners in the London office, where Monica Trench is a consultant.