• Well over half of executives expect AI use to be widespread or critical in business functions by 2025. From mostly limited AI use across the enterprise today, the surveyed executives plan a major expansion of use cases in all core functions in the next three years. More than half expect AI use to be widespread or critical in their IT, finance, product development, marketing, sales, and other functions by 2025. Some 94% of those surveyed say they are already using AI in their line of business today.

• 72% of C-level respondents stress that problems with data management will jeopardize future AI achievement. The majority of surveyed companies will invest in unifying their data platform for analytics and AI in the next three years to bolster AI adoption. Over two-thirds of respondents (68%)—and nearly all leaders (99%)—say this is crucial to the success of their enterprise data strategy.

• 78% of surveyed executives say scaling AI successfully is top priority for data strategy. The surveyed companies’ data and AI strategies are closely interlinked. Over three-quarters (78%) of the executives surveyed say that scaling AI and machine learning use cases to create business value is the top priority for their enterprise data strategy over the next three years.

• AI investment will be strongest in financial services. Of the 14 industries in the survey, AI leaders were most numerous among retail/consumer goods and automotive/manufacturing companies. However, companies in financial services are expected to see the highest investment growth in data management and infrastructure.

• Executives see multi-cloud and open standards as integral to AI progress. Most of the survey respondents (72%) appreciate the flexibility that a multi-cloud approach provides for AI development. CIOs interviewed for the study emphasize the importance of open architecture standards in supporting multi-cloud, and the importance of both in progressing AI development.

“Data issues are more likely than not to be the reason if companies fail to achieve their AI goals, according to more than two-thirds of the technology executives we surveyed,” says Francesca Fanshawe, editor of the report. “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.”
 
“These insights from global CIOs are consistent with what we hear in the field. AI-ready data is no longer a nice-to-have — it is critical to solve real-world problems and drive business outcomes," says Chris D'Agostino, Global Field CTO at Databricks. "An open and unified platform like the Databricks Lakehouse enables organizations to put their data into action and we are committed to ongoing innovations that will empower business leaders to deploy and scale mission-critical AI projects successfully."