In 2025, seven trends will shape the future of data and AI, offering advantages for those who see these changes not as challenges but as opportunities to innovate and excel.
AI governance will be non-negotiable
AI governance will become mainstream and will be a huge sticking point for organizations next year compared to the multiple iterations of data governance we have seen. The speed of adoption, creation of regulations, increased expectations of customers’ protection of their data balanced with capabilities of products they purchase, cost of replicating data due to AI, and the general risk landscape increased by Copilots will all contribute to AI governance adoption. This time, governance will stick and become the coveted job in 2025.
The rise of SLMs and agentic GenAI
2025 will mark exponential advancements in small language models (SLMs) and agent-driven generative AI. These models will tackle some of AI’s most persistent challenges: hallucinations, high operational costs, and poor user input quality.
By focusing on better contextual understanding, these innovations will reduce user friction and improve the reliability of AI tools. Organizations will prioritize these streamlined, cost-effective solutions over traditional, large-scale models.
A reality check for AI investments
The AI investment landscape is poised for a shift. As organizations grapple with the realization that poor data quality undermines the effectiveness of AI models like Copilots, these investments will focus on improving data accuracy and AI data management.
This recalibration in 2025 will redirect funding toward building robust data foundations, enabling a resurgence in responsible AI adoption by 2026. With improved data accuracy and usability, the next wave of AI will deliver on its initial promises with greater success.
Consumers and data awareness
The increasing ubiquity of AI in everyday life will lead to a more enlightened consumer base. With growing awareness of data privacy and more stringent regulations, consumers will better understand the value of their data.
This shift will transform how companies collect and use consumer information. Mature organizations that can balance personalization with privacy – i.e., offering tangible value for data sharing or seamless opt-out options – will lead the market. The era of consumer-driven data strategies will begin.
Industry frameworks for security and compliance
Enterprises will lean on industry frameworks to standardize their security, privacy, and data practices. These frameworks will offer a roadmap for internal alignment and serve as a defense against regulatory scrutiny. By adopting these frameworks, organizations will mitigate risks and gain the agility to navigate complex audits and inquiries.
Synthetic data’s time to shine
Synthetic data will have its day in the sun. As more and more regulatory and consumer expectations are developed, usage of synthetic data to protect sensitive data will become more mainstream. The more mature AI governance becomes, the more understanding of how to use synthetic data becomes and therefore increases synthetic data usage.
Automation reinventing data management
Automation will reinvent some data management jobs. Data Stewardship 2.0 will go from creation and collaboration to automation and validation.
Developing data glossaries with business terms, linking physical schema/tables/columns to the business terms, describing unstructured data with a business description, increasing lineage capabilities, organizing data within domains, predicting data ownership, remediation automation, and many other capabilities will drive recommended data management capabilities for data stewardship validation increasing understanding and alignment of data.
Here’s to 2025
The future of AI and data management is bright but requires thoughtful planning and strategic adaptation. Organizations that invest in AI governance prioritize data accuracy, embrace synthetic data, and leverage automation will lead the way.