MIT Technology Review survey: IT leaders in every industry cite democratisation of data and AI top priority to achieve generative AI goals

09/01/2024
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New research from MIT Technology Review Insights explores the opportunities that data intelligence offers CIOs to achieve their AI goals. The research report, Bringing breakthrough data intelligence to industries, was produced in collaboration with data and AI company Databricks. Among other things, the research shows that almost 9 in 10 organisations are already fully embracing generative AI, but there are still challenges in making data and AI tooling available within the wider organisation.

For the survey, 600 global CIOs, CTOs, CDOs and other tech leaders working for large public and private organisations across seven sectors: retail and consumer goods, healthcare and life sciences, manufacturing, financial services, telecommunications, media and entertainment and the public sector were surveyed. In addition, several in-depth interviews were conducted with executives. Represented MIT Technology in the study include AT&T, AXA, Condé Nast, Databricks, Dell Technologies, General Motors, Morgan Stanley, Regeneron Genetic Center, the United States Postal Service and Walmart.

Key research findings:
Real-time analytics and secure data exchange are priorities in every sector. 64% of global CIOs consider secure sharing of data and AI assets in real-time and across platforms "very important". Leaders across sectors see the potential for technology-agnostic data sharing within an industry ecosystem to support AI models and core operations, for more accurate, relevant and profitable results. An even greater proportion (72%) believe the ability to stream data for real-time analytics is becoming essential to increase customer satisfaction and gain competitive advantage. The EMEA region lags slightly behind in this regard, with only 67% of CIOs convinced they are making the most of real-time analytics, compared with 79% in the Americas and 73% in APJ.
All sectors are striving to merge their data and AI governance models to facilitate innovation.
60% of CIOs say a single integrated governance model for data and AI is "very important". This implies that many organisations are struggling with a "siloed" or fragmented data architecture. In EMEA, only 56% of CIOs agree. Although that difference is currently small, in the longer term, the region risks falling behind the global trend of system consolidation and unified governance. Therefore, each sector will have to achieve this unified governance in the context of its own record systems, data pipelines and security and compliance requirements.
Sector-specific requirements determine the priority and pace of generative AI adoption.
Supply chain optimisation is the most valuable application of generative AI in the manufacturing industry. For the public sector, it is real-time data analytics, for media and entertainment it is personalisation and customer experience, and for telecommunications it is quality control. Generative AI will not be applied in the same way everywhere, and each sector has to follow its own path in this. Nevertheless, value creation in any case will depend on access to data and AI across the organisation.

Maintaining data and AI agility by using multicloud and open source is crucial for managing risk and accelerating innovation.
63% of CIOs consider multi-cloud at least "somewhat important" and 70% feel this way about open source standards and technology. Given the rapidly changing AI landscape and uncertain regulatory environment, executives firmly believe in the value of strategic agility.

EMEA is ahead of the rest of the world in adopting new platforms that facilitate emerging technologies.
68% of CIOs in the EMEA region have embraced a platform that facilitates the adoption of emerging technologies. Israel is at the forefront with 80%, followed by the Netherlands (73%) and Germany (70%).
"Global leaders now understand that data and AI should underpin all business operations. That means all employees should have access to reliable data using a solid data foundation so that everyone can generate AI insights and results," says Samuel Bonamigo, SVP and GM in EMEA at Databricks. "Investment in an infrastructure with open formats and a robust governance model is therefore becoming a critical success factor for organisations in every industry."

"Today's tech leaders speak plainly: a unified governance model for data and AI is not just a priority, but a necessity," says Laurel Ruma, global director of custom content at MIT Technology Review. "It is clear that real-time analytics, secure data sharing and technology-agnostic ecosystems will play a central role in the future of innovation across all industries."

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