Summary
This document is a guide that outlines key data management trends expected to shape strategies in 2026. It identifies nine significant trends, including the importance of AI-ready data, ethical AI, multi-cloud flexibility, and converged data management platforms. Each trend is accompanied by specific challenges organizations may face and actionable strategies for execution. For instance, it emphasizes the need to audit data readiness and treat legacy migrations as strategic cleanups. It also discusses the challenges of AI bias and compliance risks, recommending audits of AI models and the implementation of explainability tools. The guide highlights the necessity of addressing tool sprawl and governance gaps while advocating for self-service data solutions that include guardrails to mitigate risks. Overall, the document stresses that success in data management will require prioritizing execution over mere innovation, urging leaders to focus on practical applications that deliver measurable value.
