It Pays To Break Artificial Intelligence Out Of The Lab, Study Confirms – Forbes

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Yes, artificial intelligence (AI) is proving itself to be a worthwhile tool in the business arena at least in focused, preliminary projects. Intelligent chatbots are a classic example. Now its a question of how quickly it can be expanded to deliver on a wider basis across the business to automate decisions around inventory or investments, for example.

Theres progress on this front, as shown in McKinseys latest survey of 2,360 executives, which shows a nearly 25 percent year-over-year increase in the use of AI in various business processes and there has been a sizable jump in companies spreading AI across multiple processes.

A majority of executives in companies that have adopted AI report that it has increased revenues in areas where it is used, and 44 percent say it has reduced costs, the surveys authors, Arif Cam, Michael Chui, and Bryce Hall, all with McKinsey, state.

The results also show that a small share of companies the authors call them AI high performers are attaining outsize business results from AI. Close to two in three companies, 63 percent, report revenue increases from AI adoption in the business units. Respondents from high performers are nearly three times likelier than their lagging counterparts to report revenue gains of more than 10 percent, the survey shows.

The leading AI use cases include marketing and sales, product and service development, and supply-chain management. In marketing and sales, respondents most often report revenue increases from AI use in pricing, prediction of likelihood to buy, and customer-service analytics, the surveys authors report. 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.

What are these high performers doing differently? Strategy is a key area. For example, 72 percent of respondents from AI high performers say their companies AI strategy aligns with their corporate strategy, compared with 29 percent of respondents from other companies. Similarly, 65 percent from the high performers report having a clear data strategy that supports and enables AI, compared with 20 percent from other companies. Also, the application of standardized tools to be used across the enterprise is more likely to be seen at high performers.

Adoption of Strategic AI Approaches:

Retraining workers is also a key differentiator, the survey shows. One-third of high performers, 33%, indicate the majority of their workforce has received AI-related training over the past year, compared to five percent of lagging organizations. Over the next three years, 42% of high performers intend to extend such training to most of their workers, versus only 17% of their lagging counterparts.

For AI to take hold, the McKinsey authors urge ramping up workforce retraining. Even the AI high performers have work to do in several key areas, the surveys authors point out. Only 36 percent of respondents from these companies say their frontline employees use AI insights in real time for daily decision making. A minority, 42 percent, report they systematically track a comprehensive set of well-defined key performance indicators for AI. Likewise, only 35 percent of respondents from AI high performers report having an active continuous learning program on AI for employees.

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It Pays To Break Artificial Intelligence Out Of The Lab, Study Confirms - Forbes