PHILADELPHIA, PA — A new report from Qlik® reveals that while nearly every large enterprise has committed budget toward Agentic AI, most organizations remain years away from deploying it at scale. The Qlik 2025 Agentic AI Study, conducted by Enterprise Technology Research (ETR), highlights a striking gap between ambition and execution, with data quality, integration, and governance emerging as the primary roadblocks.
The study found that 97% of enterprises have allocated funding for Agentic AI initiatives. Of those, 39% plan to invest $1 million or more, and a third intend to devote 10–25% of their total AI budgets. Despite that commitment, only 18% have fully deployed the technology, and nearly half expect it will take three to five years to scale.
“Enterprises are not short on ambition or funding. What’s missing are the data and analytics foundations that let agents work across the business with reliability and control,” said James Fisher, Chief Strategy Officer at Qlik. “If you want Agentic AI to move the needle in 2026, invest first in trusted pipelines, interoperability, and a practical ROI framework your board believes.”
The findings suggest that Agentic AI—AI systems capable of independent reasoning, planning, and task execution—is transitioning from pilot projects to structured operational plans. However, the research indicates that data infrastructure remains the choke point, ranking ahead of model performance or algorithmic sophistication. Integration challenges, workforce skills, and governance concerns also continue to slow adoption.
Among respondents, 69% reported having a formal AI strategy, up from 37% in 2024, but only 19% have established a clear ROI framework. That lack of performance measurement, Qlik said, is turning attention from whether to deploy AI to whether it delivers tangible business results.
Cybersecurity, reliability, and legal exposure ranked among the top deployment risks, followed by explainability and auditability—critical issues for risk management and regulatory compliance.
Early adopters are finding traction in IT operations and software development, where the benefits are easier to measure through automation, telemetry, and cost savings. The study found these domains to be the most common initial use cases, signaling a practical focus on operational efficiency before broader enterprise adoption.
“As spend shifts from experimentation to line items, the constraints are classic enterprise ones: data quality, integration, governance, and talent,” said Erik Bradley, Chief Strategist at ETR. “Our data shows broad intent, but only a minority are ready to scale. The next year will be about turning tightly scoped use cases in IT ops and software engineering into durable, measured production.”
Qlik’s report positions 2026 as a “build year” for most organizations, as enterprises focus on strengthening data foundations and aligning governance structures before pushing Agentic AI into mainstream operations.
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