MIT Research Reveals Industries' Gen AI Priorities

Published on
10/01/2024 02:26 PM
mit research

Real-time analytics and secure sharing are priorities in every industry to truly unleash the power of data. Sixty-four percent of CIOs say the ability to securely share live data and AI assets across platforms is “very important.”

That's according to a new report by MIT Technology Review Insights, which explores the breakthroughs in data intelligence that will enable CIOs to reach their data and generative AI priorities across seven industries, namely retail and consumer packaged goods, healthcare and life sciences, manufacturing, financial services, telecommunications, media and entertainment, and the public sector.

'Bringing breakthrough data intelligence to industries', produced in partnership with Databricks, reveals that executives see promise in technology-agnostic data sharing across an industry ecosystem in support of AI models and core operations that will drive more accurate, relevant, and profitable outcomes.

To further enable innovation in EMEA, "the region must prioritise enabling real-time analytics", as just 67% of CIOs are confident they are capitalising on this compared with 79% in North America and 73% in APJ. 

Further insights show all industries aim to unify their data and AI governance models to both protect and enable innovation: 60% of CIOs say a single built-in governance model for data and AI is “very important,” suggesting that many organisations struggle with a fragmented or siloed data architecture.

In EMEA, just 56% of CIOs agree with this sentiment., Considering the diverse and unique needs of various countries across EMEA, the region risks falling behind in the global trend of system consolidation and unified governance - essential for efficient scaling. To tackle this, every industry will have to achieve this unified governance in the context of its own unique systems of record, data pipelines, and requirements for security and compliance.

Industry-specific requirements will drive the prioritisation and pace by which generative AI use cases are adopted. Supply chain optimisation is the highest-value generative AI use case in manufacturing. At the same time, it is real-time data analysis and insights for the public sector, personalisation and customer experience for M&E, and quality control for telecommunications.

C-level executives across every industry in EMEA and indeed globally understand that data and AI must underpin everything an organisation does. This means building solid data foundations and democratising data across an organisation so that generative AI can start to drive tangible business outcomes.

Samuel Bonamigo, SVP and GM, EMEA at Databricks 

Generative AI adoption will not be one-size-fits-all, with each industry taking its own path. Still, in every case, value creation will depend on access to data and AI across roles within the organisation.

Preserving data and AI flexibility by leveraging multicloud and open source is critical for managing risks and accelerating innovation. Sixty-three percent of CIOs believe that leveraging multiple cloud providers is at least somewhat important, while 70% feel the same about open source standards and technology. Given the fast-moving AI landscape and uncertain regulatory environment, executives firmly believe in the value of strategic flexibility. 

EMEA is ahead of the rest of the world when it comes to embracing a new platform that enables the adoption of emerging technologies. 68% of CIOs in EMEA consider having a platform that enables the adoption of emerging technologies in the next two years “very important”, led by Israel 80%, Netherlands 73%, and Germany 70%.

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The report, “Bringing breakthrough data intelligence to industries,” is produced in partnership with Databricks, the data and AI company, and is based on a global survey of 600 CIOs, CTOs, CDOs, and technology leaders for large enterprises and public-sector organisations and features in-depth interviews with C-level executives.

Among the organisations represented are AT&T, AXA, Condé Nast, Databricks, Dell Technologies, General Motors, Morgan Stanley, Regeneron Genetic Center, the United States Postal Service, and Walmart.

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