August 25, 2026 – The hype around agentic AI is growing rapidly, but many organizations lack a consistent way to evaluate where it can deliver value. Vendors and internal teams often push for AI agents to solve problems that simple automation could handle at a lower cost and with less risk. Info-Tech Research Group’s new blueprint, Create Your Agentic AI Roadmap for Data Management, helps data leaders separate genuine agentic opportunities from routine automation and invest only where the organization is ready to deliver.
Organizations are under pressure to show results with AI, but moving too soon can be costly. Agentic AI requires stronger data governance, controls, and oversight than traditional AI. Many teams overestimate their readiness and then watch pilots stall when data quality and governance gaps appear. The firm’s blueprint helps teams identify gaps early by validating every use case candidate through three gates: fit, readiness, and complexity.
“The fastest way to waste an AI budget is to invest in agentic AI before confirming whether a use case actually needs an AI agent,” says Jason Edwards, principal research director at Info-Tech Research Group. “Teams need to make sure the data and governance foundations are ready, understand how complex the use case will be to build, and confirm that an agent is the right solution before they move forward.”
Key Challenges Data Leaders Face With Agentic AI in Data Management
Info-Tech’s research points to four common barriers:
- Agent-washing hides the truth. Vendors and teams label ordinary automation as “agentic,” which makes honest comparison nearly impossible.
- No consistent way to qualify ideas. Teams choose use cases based on excitement and demos, not with a repeatable test of fit, readiness, and complexity.
- Readiness is overestimated. Data quality and governance gaps often stay hidden until a project is funded and a pilot is already underway.
- Complexity is underestimated. The real cost, effort, and risk surface too late, and the initiative stalls.
Info-Tech's Three-Phase Framework for Prioritizing Agentic AI Use Cases
The Create Your Agentic AI Roadmap for Data Management blueprint guides teams through the following three phases:
Phase 1: Define the use cases. Teams choose their highest-priority data management domains, select and scope candidate use cases, and document them in a structured register.
Phase 2: Qualify the use cases. Teams run each candidate through agentic fit, readiness, and complexity gates to confirm whether it needs an agent, check the data and governance foundations, and analyze how hard it is to build.
Phase 3: Prioritize and act. Teams score the qualified candidates on benefit, effort, and risk, then sort them into a sequenced roadmap.
The Create Your Agentic AI Roadmap for Data Management blueprint includes an Agentic AI Scoring Kit, which runs candidates through a three-gate model, and an Agentic AI Candidate Definition Workbook, which standardizes how use cases are scoped. These tools help CIOs, data leaders, and governance teams turn a long list of competing ideas into a clear roadmap with owners, guardrails, and measurable goals that leadership can fund.
For exclusive and timely commentary from Info-Tech’s experts, including Jason Edwards, and access to the complete Create Your Agentic AI Roadmap for Data Management blueprint, please contact pr@infotech.com.
About Info-Tech Research Group
Info-Tech Research Group is the “get things done” partner for over 30,000 IT, HR, and marketing leaders worldwide. The fastest growing research and advisory firm, Info-Tech enables leaders to make well-informed decisions and transform their organizations through AI, strategic foresight, step-by-step methodologies, practical tools, industry-leading advisory, and training programs. For nearly 30 years, tens of thousands of private and public organizations have trusted Info-Tech to lead their most important initiatives through periods of change and deliver outcomes that truly matter.
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