As the unstoppable push to accelerate the adoption of AI continues, five data trends (and some risks) may dominate the year

In 2025 AI will handle a significant portion of data tasks such as classification, validation, and enrichment, according to Cody David, GenAI Managing Solution Architect, Syniti.

By reducing the effort required to manage data, the use of AI can empower organizations to deliver faster, more effective solutions while enhancing employee productivity and productivity. 

Here are David’s five fresh predictions for the AI data management scene in the year ahead:

Other key findings include:

  • The rise of intelligent agents

    In recent developments, AI agents have begun to work collaboratively, automating tasks and processes that were once manual and time-consuming. These agents are not isolated performers; they are part of a broader ecosystem that enhances advanced reasoning capabilities. By collaborating, AI agents can solve complex problems that single-shot large language model methods struggle with.

  • More advanced reasoning and self-improvement capabilities

    On the horizon is the ability of AI systems to improve autonomously. Unlike static model solutions, self-improving datasets and models will learn from real-world integrations, refining their outputs and adapting to evolving business needs. Advanced reasoning and self-improvement capabilities will also reduce the need for constant human intervention and accelerate the deployment of AI solutions. As these systems become more intelligent, businesses will gain tools that not only solve current problems but also anticipate and address future challenges.

  • More AI-assisted data generation and management

    This year, AI-powered solutions will enable organizations to automate the creation, deployment, and maintenance of quality content, significantly reducing the effort required from human experts. This will include:

    • Automated content generation: AI will handle more quality content creation, allowing humans to focus on curation and final approvals.
    • Accelerated project delivery: By minimizing the manual workload, AI will help organizations implement data quality and migration solutions faster.
    • Platform integration: Seamless AI integration with enterprise platforms will ensure better tool utilization, delivering maximum value to customers. This approach not only saves time but also allows subject matter experts to focus on higher-level strategic tasks while maintaining high-quality data standards.
  • Transforming daily data interaction

    In 2025, there will be a significant shift in how businesses use AI to interact with data daily. The key is reducing the burden on corporate users and subject matter experts who currently spend extensive hours on testing, requirements gathering, and data validation. By automating routine tasks and providing AI-driven insights, organizations can enhance productivity and make data-driven decisions more efficiently. This will allow experts to focus on innovation and strategy to drive success. Organizations not leveraging these capabilities will fall behind in 2025.

  • Pioneering AI in data: a vision

    As the above predictions set the stage for a new era in data management, addressing challenges such as AI bias and hallucinations will be paramount in 2025. Organizations that embrace responsible AI will be better positioned to leverage data as a strategic asset, driving efficiency and gaining a competitive edge in the long term.

These predictions and trends present an opportunity to organizations to harness AI for strategic advantage to provide data solutions to gain an edge over competitors that are reluctant to exploit technology.