Preparing an organization’s data for AI presents a new set of challenges and opportunities. This survey report from MIT Technology Review Insights examines whether companies are equipped with the right data foundations to leverage generative AI, and delves into the hurdles of establishing the necessary data infrastructure for this technology. The report is based on insights gathered from a survey of 300 C-suite executives and senior technology leaders, as well as in-depth interviews with four industry experts.
The key findings of the report include:
Data integration emerges as the primary focus for AI readiness. According to the survey, 82% of C-suite and other senior executives agree that scaling AI or generative AI use cases to drive business value is a top priority. The biggest challenge in achieving AI readiness, as identified by survey respondents, is data integration and pipelines (45%). When asked about the difficulties in data integration, respondents highlighted managing data volume, transitioning data from on-premises to the cloud, enabling real-time access, and handling data changes.
Executives are honing in on data management challenges and seeking sustainable solutions. 83% of survey respondents acknowledge that their organization has identified multiple data sources that need to be integrated to support AI initiatives. While data-driven technologies in the past led to data integration and aggregation efforts, these were often tailored to specific use cases. Now, companies are seeking scalable and use-case agnostic solutions, with 82% prioritizing strategies that will remain effective regardless of changes in data strategy and partnerships.
Data governance and security emerge as major concerns for regulated industries. Data governance and security issues rank as the second most common challenge in data readiness (cited by 44% of respondents). Those in highly regulated sectors are two to three times more likely to highlight data governance and security as a concern, with chief data officers (CDOs) emphasizing this challenge twice as often as their C-suite counterparts. Experts emphasize the importance of addressing data governance and security from the outset of any AI strategy to ensure proper data utilization and access.
This content was created by Insights, the custom content division of MIT Technology Review. It was not authored by MIT Technology Review’s editorial team.
Download the full report.
