Agentic AI Adoption Slows at Early Stages

A new Dynatrace report indicates that about fifty percent of agentic artificial intelligence projects are still confined to proof‑of‑concept or pilot phases. This suggests many organizations are struggling to move beyond experimentation toward full‑scale implementation, despite a strong appetite for AI‑driven transformation.

Key Deployment Areas

The study identifies the primary domains where companies are experimenting with AI agents: IT operations and DevOps (approximately 72% of respondents), software engineering (around 56%), and customer support (about 51%). These areas reflect where enterprises see immediate operational benefits from autonomous agents.

Expected Return on Investment

While investment focus is on the three domains above, the highest anticipated returns are projected in IT operations and system monitoring (roughly 44% of respondents), cybersecurity (about 27%), and data processing and reporting (around 25%). This gap highlights a mismatch between where money is being spent and where the greatest financial impact is expected.

Barriers to Progress

Several obstacles are slowing the transition from pilot to production. Security, privacy, and compliance concerns are cited by more than half of the participants. Managing and monitoring AI agents at scale presents a challenge for 51% of respondents, and a shortage of skilled staff or adequate training affects 44%. Additionally, one in three organizations point to an unclear business case as a barrier.

Human Oversight Remains Central

Human involvement continues to play a critical role in AI decision‑making. Approximately 69% of agentic AI decisions are still verified by humans, and 87% of companies are building agents that require human supervision. Moreover, 23% of respondents prefer to rely solely on human‑supervised agents for critical tasks.

Future Budget Outlook

Despite the challenges, confidence in AI remains high. Seventy‑four percent of surveyed leaders expect to increase their agentic AI budgets in the coming year, indicating a commitment to overcoming current hurdles.

Recommendations for Successful Scaling

Dynatrace advises organizations to rethink traditional ROI metrics, establish clear guardrails for human‑machine collaboration, and adopt a deliberate, intent‑driven scaling approach rather than large, indiscriminate spending. By focusing on measurable outcomes and robust governance, companies can better translate AI pilots into tangible business value.

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