To mark the launch, we’re publishing Agentic AI Essentials, a four-part series to help organizations navigate the reality of agentic AI adoption. Across the series, we’ll look at the questions that matter most: what’s real versus hype, how to avoid adoption pitfalls, how to measure ROI, and how roles will evolve once agents are onboarded. Here’s a sneak peek at what’s in store.

Demystifying the Agentic AI Hype Cycle

Every wave of new technology sparks a frenzy of excitement, and agentic AI is no exception. Vendors are racing to position themselves as “agentic-ready,” while customers search for ways to solve deeply rooted challenges like technical debt and staff shortages. The result is a fog of hype that makes it difficult to see what’s truly valuable.

In the first article of our series, we’ll establish what makes agentic AI distinct. We’ll look at “tool-calling” and examine how these systems can turn intelligence into action. We’ll also explore the human fears, pressures, and ambitions that fuel the noise around agentic systems. By untangling this web of narratives, IT decision-makers can take the first step toward making sound decisions about adoption.

Avoiding Pitfalls While Integrating Agentic AI

The next question is practical: How do you introduce agentic AI into your environment effectively? Too often, organizations start with the technology rather than the problem, asking, “Where can we use agentic AI?” instead of “What problem are we trying to solve?” This can lead to misplaced priorities, inflated costs, and projects that stall before they can deliver real value.

Our second article highlights:

  • Unclear objectives: Without defined outcomes, projects risk being driven by hype rather than business needs
  • Operational costs: Unlike traditional software, agents operate in an open “action space,” which can spiral into inefficiency without strict guardrails
  • Legacy integration: Many on-premises systems simply lack the GPU-intensive infrastructure needed to support agents, forcing costly upgrades or cloud migrations
  • Financial resilience: Larger organizations can absorb the bumps of early adoption, but SMBs need a measured, phased approach to avoid being burned

For smaller and mid-sized businesses, I propose a four-stage path to successful adoption: Introduce, expand, integrate, and evolve.

Measuring Agent ROI

Even with careful adoption, one question remains: once you’ve introduced an agent, how do you know it’s delivering value? Our third article lays out a process for capturing ongoing feedback to optimize the effectiveness of your new system.

Feedback loops come in two forms:

  • Explicit feedback (thumbs-up, thumbs-down, ratings). Useful, but limited
  • Implicit feedback (did the ticket stay closed? Did the alert resolution hold?). Often more powerful, because actions have visible consequences

Establishing criteria up front is vital. A reopened ticket, for example, signals failure; a sustained resolution signals success. In more complex scenarios—like an agent creating a dashboard during an incident—effectiveness can be measured by whether the output aligns with intent. Offline testing with “golden datasets” helps refine accuracy before deployment, while continuous monitoring ensures the system stays reliable in production.

Bookmark the SolarWinds Blog for a deep dive into the mechanisms that establish trust in agentic systems.

Rethinking Human Roles in the Agentic Era

How will an IT pro’s day-to-day experience shift in response to agentic AI? Soon, with agentic support, instead of hopping between a dozen dashboards, an IT pro might simply receive a message: “Service health is bad.” From there, they can ask, “Why?” The agent does the investigative grunt work, surfacing the root cause in plain language.

The role of the professional shifts from sifting through data to validating insights and guiding the next steps. Dashboards may not disappear, but they could shift from being the centerpiece of daily work to more of an oversight tool, showing outcomes like time saved or reporting on the accuracy of agent decisions.

If that happens, the IT pro’s role is likely to change as well. Instead of losing hours on manual investigation, professionals will spend more time guiding and validating agents' work—moving from repetitive tasks to higher-value oversight and orchestration.

Read the piece for a comprehensive look at agentic AI’s short, medium, and long-term implications for IT practitioners.

Building the Future on Solid Ground

Agentic AI promises to implement a lasting shift in how IT organizations operate and how professionals spend their time. By grounding our understanding in accurate information and applying these tools with purpose, we can unlock the revolutionary potential of agentic AI in our own environments.

The sooner we take thoughtful steps forward, the sooner we can harness its power to create more resilient systems, stronger teams, and a future where technology truly works alongside us.

Forward-Looking Statements

This article contains forward-looking statements regarding future product plans and development efforts. SolarWinds considers various features and functionality prior to any final generally available release. Information in this article regarding future features and functionality is not and should not be interpreted as a commitment from SolarWinds that it will deliver any specific feature or functionality in the future or, if it delivers such feature or functionality, any time frame when that feature or functionality will be delivered.

All information is based upon current product interests, and product plans and priorities can change at any time. SolarWinds undertakes no obligation to update any forward-looking statements regarding future product plans and development efforts if product plans or priorities change.

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