• A new research program by MIT Technology Review Insights explores trends in global AI adoption and the potential for companies across industries to share data with each other in the future.
The program, The global AI agenda, is developed in association with Genesys, Philips, and NUS Business School’s Centre on AI Technology for Humankind, and includes a survey of more than 1,000 leaders as well as in-depth interviews with AI experts worldwide. The research examines the leading AI use cases by industry, brings the latest thought leadership on AI and ethics, and provides case studies of companies seeking to scale AI solutions. It will be published in a series of white papers between March and June 2020.
The first report, “The global AI agenda: Promise, reality, and the future of data sharing,” is released today. The findings are as follows:
• AI deployment is widespread but will take time to scale. AI is being deployed widely across sectors, exercising an important, though not dominant influence in business operations. Most survey respondents (60%) expect AI to be used in anywhere from 11% to 30% of their business processes in three years’ time. Financial services providers, manufacturers, and technology companies have the highest expectations of AI penetration.
• Change management and data challenges hamper efforts to scale AI. More than half of surveyed companies struggle most with the change management involved in modifying business processes to leverage AI. Nearly as difficult are data challenges—cited by 48%—such as integrating unstructured data and interfacing with open-data platforms.
• The top AI use cases today are in quality control, customer care, and cybersecurity. Some 60% of manufacturers and pharma companies are using AI to improve product quality. Nearly half of retail and consumer firms (47%) are using it in customer care. Over 50% of energy firms are leveraging AI for monitoring and diagnostics, 58% of financial services providers for fraud detection, and 52% of tech firms to strengthen cybersecurity.
• Currently nascent, data sharing can magnify the impact of AI. Two-thirds (66%) of companies are willing to share data externally to help develop new AI-enabled efficiencies, products, or even value chains. Manufacturers, consumer goods firms, retailers, and health sector organizations envision benefits to supply chain speed and visibility and reduced time to market of new products. Technology and financial services firms see gains to customer service, cybersecurity, and fraud detection, among other uses.
• Greater regulatory clarity is required for more active data sharing. Although in principle willing to share data, businesses are still cautious, and more clarity is needed in privacy regulation and industry standards, say 64% and 58% of respondents, respectively, before data sharing takes hold.
