As generative AI captured imaginations and investment dollars in recent years, the conversation quickly turned to the data that underpins it. Data and AI will continue to redefine business in 2025, but in increasingly practical ways. AI is reshaping data infrastructure, creating a demand for data literacy, and challenging business culture and governance practices to keep up.
To compile the top trends that will impact the data industry in 2025, we tapped into our network of partners and top industry leaders, practitioners, and thinkers. We hope you’ll find their insights informative, useful, and inspiring.
Here’s to a successful 2025!
Table of Contents:
- From data pipelines to massive knowledge pipelines
- Multiple engines, unified storage
- Stronger data solutions through consolidation
- A healthy industry reset
- AI agents make up for industry amnesia
- Balancing AI ambitions with energy grid demands
- Widespread adoption of AI assistants
- Data lakes as the foundation for AI
- Beyond the hype: AI deployments at scale
- Closing gap between IT and business
- Problem-solving pragmatism over data dogmas
- AI-powered, next-level customer engagement
- Automation of Automation
- From data gravity to platform gravity
- New insights from unstructured data
- Iceberg and open table formats surge
- AI-enhanced data engineering efficiency and workflows
- Rapid value from query-enabled LLMs
- Semi-structured data upends existing data management practices
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“Enterprises will increasingly leverage user-friendly data integration tools to centralize data from various operational data stores to create a corpus for AI training.”
“It’s never been a sexy domain, but is this the year that data governance finally becomes cool? There’s such a need for data trust at this moment that it might be.”
“I think 2025 is going to be a deeply destabilizing year for everyone’s sense of comfort with technology. All of us in this industry are going to have to grapple with the fact that our jobs are changing. By 2026, I think everyone else will have to as well.”
“The implementation and adoption of AI as an assistant is one of the most important trends for 2025. Right now AI is in an era similar to what the internet was in the early ’90s—on the upswing and gaining popularity. If AI is implemented and adopted well, it will complement professional and personal lives alike.”
“We need to get back to the most pragmatic pieces of how we’re solving problems, with tangible numbers and value, not lofty goals and narrow-minded approaches. No hype, just real problem-solving—that’s how you get actual wins.”
“People want trust. Building something reliable and actionable that you have confidence in means providing transparency for all users. Visibility into the model allows you to integrate AI more easily down the road because the trust is there. Users have confidence in what you’re delivering.”
“In order to tap into the game-changing combination of semi-structured and structured data, business teams and data teams must collaborate to imagine the art of the possible in formulating analytics use cases. Instead of asking, ‘What transactional data do we have?’, flip the thinking to ‘If we really want to know our customers, patients, and employees, we need to see this type of data.’”
“People are coming to the realization that building an AI solution is very easy, but building an AI solution that actually adds value is much more difficult.”
“I believe many tools will get AI-powered improvements or better workflows, which won’t seem groundbreaking right away, but would be a very good production-grade use of AI and maybe unlock some improvements that were not possible before.”
“AI will transform how brands personalize and automate every step of the customer journey. Marketers will move past manual A/B testing and static targeting, embracing ML-driven experiences that continuously learn and adapt for each user.”
“What I’d love to see more in 2025 is organizations embrace process just as much as they do technology. Simple operational changes, such as determining who owns data quality for what domain, or establishing strong SLAs for data reliability that map back to business objectives, could reap huge benefits for the overall health of an organization’s data and AI estate.”
“I anticipate that in the coming year, a lot of vendors in the data space will get folded into larger companies. The good news is, this will actually benefit the larger industry. Too much VC funding has led to too many options in the market, which can be overwhelming to buyers. Consolidation in each specific category will provide customers with fewer solutions that do more things.”
“To drive the next outcome, businesses shouldn’t reduce data teams, they should spread them across the entire business to create a more decentralized, data-focused approach.”
