Home Bots & Business ‘Democratizing data and AI are number one challenges for generative AI’

‘Democratizing data and AI are number one challenges for generative AI’

by Pieter Werner

A new report by MIT Technology Review Insights 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.

The current landscape of data management and AI integration in various industries underscores the importance of real-time analytics and secure data sharing. According to recent statistics, 64% of Chief Information Officers (CIOs) highlight the significance of securely sharing live data and AI assets across different platforms.

This trend is evident across numerous industries, where there’s a growing interest in technology-agnostic data sharing to support AI models and core operations. Such practices are believed to enhance the accuracy and profitability of outcomes. However, there’s a disparity in confidence among regions in capitalizing on real-time analytics, with EMEA (67%) lagging behind North America (79%) and Asia-Pacific Japan (APJ) (73%).

Another critical aspect is the unification of data and AI governance models. About 60% of CIOs consider a single, integrated governance model for data and AI as crucial. This need stems from the challenges posed by fragmented or siloed data architectures. In the EMEA region, 56% of CIOs resonate with this view. The region faces unique challenges due to the diverse needs of its countries, potentially impacting its pace in adopting unified governance models, which are essential for efficient scaling.

Industry-specific requirements significantly influence the adoption and application of generative AI. For instance, in manufacturing, supply chain optimization is seen as the most valuable application of generative AI. Other sectors like the public sector, media and entertainment (M&E), and telecommunications focus on different aspects such as real-time data analysis, customer experience personalization, and quality control, respectively. While the adoption of generative AI is not uniform across industries, its success largely depends on access to data and AI across organizational roles.

Regarding technology infrastructure, 63% of CIOs consider leveraging multicloud environments somewhat to very important, and 70% hold a similar view about open source standards and technologies. This approach is driven by the need to manage risks and foster innovation in a rapidly evolving AI landscape and uncertain regulatory environment.

In terms of embracing platforms that enable the adoption of emerging technologies, the EMEA region appears to be leading globally. Sixty-eight percent of CIOs in EMEA deem such platforms as very important for the next two years. Israel (80%), the Netherlands (73%), and Germany (70%) are at the forefront of this trend. This indicates a proactive approach in the region towards integrating emerging technologies into their operational frameworks.

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