A report from MIT Technology Review Insights showed over half of the CIOs, CTOs, and chief data officers surveyed expect artificial intelligence (AI) use to be widespread or critical in their business by 2025. Ninety-four percent of those executives say they are already using AI today.

Laurel Ruma, global director of custom content for MIT Technology Review, told SDxCentral the primary challenges CIOs and other executives face as they pursue AI adoption are “addressing shortcomings in data management and infrastructure, as well as internal structural and process rigidities and talent deficits.”

“Improving processing speeds, governance, and quality of data, as well as its sufficiency for models, are the main data imperatives to ensure AI can be scaled,” she added. 

Over three-quarters (78%) of the executives surveyed say that scaling AI and machine learning (ML) use cases is the top priority for their enterprise data strategy over the next three years. Seventy-two percent of the C-level respondents said that problems with data management will jeopardize future AI achievement. 

Of the 14 industries in the survey, AI use was highest in retail/consumer goods and automotive/manufacturing. However, the report notes companies in financial services are expected to see the highest investment growth in data management and infrastructure.

Most of the executives (72%) “appreciate the flexibility that a multicloud approach provides for AI development.” Those surveyed emphasized the importance of open architecture standards in supporting multicloud, and the importance of both in progressing AI development.

Ruma said a multicloud approach enables AI teams to choose the most suitable platforms for different use cases that have specific resource requirements involving the sourcing, storage, or processing of data. 

She added a multicloud strategy and an open approach to data architecture and standards “often go hand-in-hand.”

With the MIT report titled “CIO vision 2025: Bridging the gap between BI and AI,” Ruma explained AI is the processing of massive amounts of data, but business intelligence (BI) means “analyzing and applying the insights from that data.”

She added the more employees in an organization who can configure and improve AI algorithms, the more AI-based innovations are likely to materialize. “Many CIOs are looking to data-literate employees without specialist data science training—to rise to this challenge,” she added. 

Beyond investing in people, 32% of survey respondents say that business intelligence/analytics infrastructure and tools is the most instrumental investment to generate benefits from AI.

MIT expects leader spending on data security over the next three years will rise by 101%, on data governance by 85%, on new data and AI platforms by 69%, and on existing platforms by 63%.

“So far, security and risk management have been primary areas of AI investment,” Ruma noted. She explained that although many executives cite faster product development and reduced time to market as AI-derived gains, relatively few have yet been able to point to significant top-line returns from increased revenue. 

However, Ruma expects that by 2025, net additions to revenue are expected to be the most tangible form of return gained from AI. “CIOs recognize that their organizations have thus far only scratched the surface of the efficiency, speed, innovation, and other gains that the use of AI and machine learning can generate across different functions,” she said. 

“They also recognize that the data, talent, and other foundations they are putting in place to support AI development cannot remain static.”