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On this subject, here is an article about AI: Most companies report measurable benefits from AI where it has been deployed; however, much work remains to scale impact, manage risks, and retrain the workforce. A group of high performers shows the way.
Most respondents are seeing returns from AI
In this year’s survey, we asked respondents about 33 AI use cases across eight business functions, including how adoption of AI for each of these activities has affected revenue and cost in the business units where AI is used. The results suggest that AI is delivering meaningful value to companies.
Aggregating across all of the use cases, 63 percent of respondents report revenue increases from AI adoption in the business units where their companies use AI, with respondents from high performers nearly three times likelier than those from other companies to report revenue gains of more than 10 percent. Respondents are most likely to report revenue growth from AI use cases in marketing and sales, product and service development, and supply-chain management (Exhibit 1). In marketing and sales, respondents most often report revenue increases from AI use in pricing, prediction of likelihood to buy, and customer-service analytics. In product and service development, revenue-producing use cases include the creation of new AI-based products and new AI-based enhancements. And in supply-chain management, respondents often cite sales and demand forecasting and spend analytics as use cases that generate revenue.
Overall, 44 percent of respondents report cost savings from AI adoption in the business units where it’s deployed, with respondents from high performers more than four times likelier than others to say AI adoption has decreased business units’ costs by at least 10 percent, on average. The two functions in which the largest shares of respondents report cost decreases in individual AI use cases are manufacturing and supply-chain management. In manufacturing, responses suggest some of the most significant savings come from optimizing yield, energy, and throughput. In supply-chain management, respondents are most likely to report savings from spend analytics and logistics-network optimization.
AI adoption is increasing in nearly all industries, but capabilities vary
As in last year’s survey, we asked respondents about their companies’ use of nine AI capabilities.5 Fifty-eight percent of respondents report that their organizations have embedded at least one AI capability into a process or product in at least one function or business unit, up from 47 percent in 2018—a sign that AI adoption in general is becoming more mainstream. What’s more, responses show an increase in the share of companies using AI in products or processes across multiple business units and functions: 30 percent of this year’s respondents report doing so, compared with 21 percent in the previous survey. While this seems to indicate that more companies are beginning to scale AI, high performers are much further along in these efforts, averaging 11 reported AI use cases across the organization versus about three among other companies.
By sector, the results indicate increases in AI adoption in nearly every industry in the past year. Retail has seen the largest increase, with 60 percent of respondents saying their companies have embedded at least one AI capability in one or more functions or business units, a 35-percentage-point increase from 2018.
The results show companies applying AI capabilities that help them perform the functions that create value in their industries. For example, respondents from consumer-packaged-goods companies are more likely to report using physical robotics—which can aid in assembly tasks—than most other types of capabilities. And telecom respondents report their companies using virtual agents—which can be used in customer-service applications—more than other capabilities (Exhibit 2). High-performing companies, however, are far more likely to adopt AI in business functions that this survey and past research link to greater value creation more broadly. For example, more than 80 percent of respondents from high performers say they have adopted AI in marketing and sales, compared with only one-quarter from those of other companies that use AI.
On a regional level, the survey shows significant increases in adoption levels in developed Asia–Pacific,6 Europe, Latin America, and North America. In Asia–Pacific and Latin America, the shares of respondents who say their companies have embedded AI across multiple functions or business units have nearly doubled since the previous survey. However, the increases put all of these regions, as well as China, at similar aggregate reported levels of adoption, suggesting that while there is considerable variation at the level of individual companies, the adoption of AI is a global phenomenon.7
The results indicate that the pace of adoption will likely continue in the near term, with 74 percent of respondents whose companies have adopted or plan to adopt AI saying their organizations will increase their AI investment in the next three years. More than half of these respondents expect an increase of 10 percent or more. But the survey results indicate that AI high performers plan to invest more, with nearly 30 percent of respondents from these companies saying their organizations will increase investment in AI by 50 percent or more in the next three years, compared with just 9 percent of others who say the same.
AI high performers tend to engage in value-capturing practices
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