A report by MIT Technology Review Insights explores opportunities for businesses to leverage data and generative AI to deliver growth.
The report, “Laying the foundation for data- and AI-led growth,” is produced in partnership with Databricks and is based on a global survey of 600 CIOs, CTOs, CDOs, and technology leaders for large public and private-sector organizations and features in-depth interviews with C-level executives.
Among the organizations represented are ADP, Condé Nast, Databricks, Dell Technologies, General Motors, Starbucks, Razorpay, Regeneron Genetics Center, and the U.S. Transportation Security Administration.
“We are at an inflection point with AI adoption and CIOs are doubling down on their investments to ensure they have the right technology and talent in place to reap the efficiencies of AI democratization,” says Naveen Zutshi, chief information officer for Databricks.
“Today’s early movers will be tomorrow’s AI winners. But to be successful, technology leaders must foster a culture where employees feel empowered to experiment with AI in a secure environment that protects data privacy. Only then will companies realize their goals of adopting and scaling AI across the organization.”
The findings are as follows:
- Executives expect AI adoption to be transformative in the short term. A majority – 81%– of survey respondents expect AI to boost efficiency in their industry by at least 25% in the next two years. One-third say the gain will be at least 50%.
- CIOs are doubling down on their investments in data and AI. Faced with new competitive pressures and an unprecedented speed of innovation, technology leaders need their data and AI assets to deliver more growth to the business than ever before. They are investing to secure this future: every organization surveyed will boost spending on modernizing data infrastructure and adopting AI during the next year, and for nearly half (46%), the budget increase will exceed 25%.
- Democratization of AI raises the stakes for governance. As business units clamor to use generative AI, executives seek governance frameworks that can provide data accuracy and integrity as well as data privacy and security. Sixty percent of respondents say a single governance model for data and AI is “very important.”
- As generative AI spreads, flexible approaches are favored. Eighty-eight percent of surveyed organizations are using generative AI, with 26% investing in and adopting it, and another 62% experimenting with it. The majority (58%) are taking a hybrid approach to developing these capabilities, using vendors’ large language models (LLMs) for some use cases and building their own models when IP ownership, privacy, security, and accuracy requirements are tighter.
- Talent and skills gaps overshadow organizations’ other data and AI challenges. When asked how their company’s data strategy needs to improve, the largest share of respondents (39%) say investing in talent and upskilling the workforce. An even larger share (72%) say it will be “very important” to encourage innovation that will help attract and retain talent.
- Lakehouse has become the data architecture of choice for the era of generative AI. Nearly three-quarters of surveyed organizations have adopted a lakehouse architecture, and almost all of the rest expect to do so in the next three years. Survey respondents say they need their data architecture to support streaming data workloads for real-time analytics (a capability deemed “very important” by 72%), easy integration of emerging technologies (66%), and sharing of live data across platforms (64%). Ninety-nine percent of lakehouse adopters say the architecture is helping them achieve their data and AI goals, and 74% say the benefits are “significant.”
“With data and AI at the forefront of innovation, our report underscores the commitment of C-suite executives to steer toward a transformative future,” says Laurel Ruma, global director of custom content for MIT Technology Review. “Strategic investments, consolidation efforts, and dedication to governance and democratization of AI are not merely choices; they are imperatives for success.”
