Enterprise ITOps leaders are realizing that legacy incident management processes are collapsing under the weight of today’s sprawling, hybrid-cloud enterprise environments. Monitoring and observability tools generate a relentless flood of alerts across cloud platforms, infrastructure, applications, and services. The signals are there, the volume of noise makes it harder than ever to identify what’s urgent. And when your teams can’t tell the two apart quickly, incidents escalate, SLAs slip, and the cost of running IT operations quietly balloons.
That’s the challenge BigPanda and ServiceNow set out to solve together, and why we’re excited to share a new e-book we created jointly with ServiceNow that highlights how enterprises can shift from reactive firefighting to intelligent, agentic IT operations.
Agentic IT operations offers a solution by transforming manual and reactive ITSM processes into intelligent, autonomous systems. These systems can adapt to changing environments, learn from experience, and collaborate with humans to respond to incidents at machine speed. With intelligent, automated workflows, enterprises can achieve faster mean time to resolution (MTTR), lower operational overhead, and increased team productivity.
Why IT Teams are stuck in reactive mode, and how agentic ITOps breaks the cycle
Here’s a number that should worry every IT leader: only 25% of alerts are actionable. The rest is noise that your teams have to manually comb through, eating up hours of engineering time and slowing incident response.
More than 50% of mean time to resolution (MTTR) is wasted waiting for information, not resolving the issue. This isn’t because your teams lack talent. It’s because they lack clarity. Every handoff resets understanding, fragmented context slows triage, and low-quality tickets keep skilled engineers stuck in low-value work instead of focusing on what drives the business forward.
The conventional answer has been to add more tools, headcount, and processes. But adding those layers simply scales effort, not outcomes. The result is an operating model that reacts to what has already happened rather than anticipating what’s coming.
Agentic ITOps facilitates a different approach. Rather than passively surfacing data, agentic ITOps interprets signals, identifies relationships between events, and surfaces what matters most, even when the underlying data is imperfect, incomplete, or siloed.
How BigPanda and ServiceNow reduce alert noise by up to 99% accelerate incident resolution
“With the help of BigPanda, we reduced incidents by 69% and significantly improved IT operational efficiency.”
Samy Senthivel, Director of Observability Services, Autodesk
As part of our partnership with ServiceNow, BigPanda has developed a certified ServiceNow application that transforms high-volume alert streams into actionable, context-rich incidents directly within ServiceNow. By integrating BigPanda with their ServiceNow deployment, enterprises can dramatically reduce alert noise and accelerate incident resolution.
BigPanda correlates thousands of raw alerts into a single, context-rich incident, enriched with probable root cause, topology data, and ownership before it ever reaches ServiceNow. That means teams open a ticket and immediately know what’s happening, why, and who should own it. No more manual triage, bridge calls to determine whether two alerts are the same incident, or manual guesswork.
The results speak for themselves:
- 99% reduction in alert noise
- 50% fewer incident tickets
- 30–50% faster MTTR
- 43% ticket reduction
- ~15,000 hours of manual work saved
- Up to 74% reduction in bridge calls
For Autodesk, integrating BigPanda with ServiceNow reduced incidents by 69% and improved MTTR by 85% across a monitoring environment that generates 100,000 monthly application alerts across 25 fragmented tools. That’s not a marginal improvement, it’s a fundamentally different way of operating.
This value can be unlocked immediately. Historically, waiting for ideal data conditions is one of the biggest barriers to implementing AI in IT operations. With agentic ITOps powered by BigPanda, enterprises don’t need a perfect CMDB or fully mature ITOM practice to start seeing value.
BigPanda is built to work with the real-world complexity that enterprises already manage, including Incomplete CI mappings, outdated relationships, missing ownership data. By automatically surfacing configuration items in live alerts, BigPanda actually improves CMDB data quality over time.
“Whether an organization is early in its ITOM journey or operating a mature NOC, they can start seeing improvements in MTTR within weeks, without needing to re-architect their existing environment,” said Tom Mezl, Chief Revenue Officer at BigPanda.
Together, BigPanda and ServiceNow are redefining how complex enterprises run their IT operations. By combining signal processing with a proven workflow backbone, this bridges the gap between overwhelming data and effective action.
By shifting to agentic-supported operations, systems not only detect issues but also actively shape how they are understood and resolved. The results are a shift to proactive incident management, increased operational capacity, and enhanced efficiency.
The median ROI for organizations using BigPanda and ServiceNow together is 430%, with median annual benefits of $2.85 million and a payback period of under one year.
Learn more about transforming your operations with BigPanda and ServiceNow
We’ve only scratched the surface here. The full e-book, Agentic IT Operations, Built for Action, goes deeper on how enterprises can turn ServiceNow and BigPanda into an effective engine for intelligent IT operations. Read the e-book to learn how to get started with agentic IT operations today, without waiting for perfect data.
Five key takeaways from this article:
Alert volume isn’t the problem, actionability is. Enterprises generate more observability data than ever, but only 25% of alerts are actionable. Agentic AI solves for clarity, not just coverage.
BigPanda and ServiceNow are complementary by design. BigPanda operates upstream of ServiceNow to correlate, enrich, and filter signals before they become tickets. This turns ServiceNow into an active operational backbone for intelligent incident response.
You don’t need perfect data to start. One of the most persistent myths in enterprise IT is that CMDB and observability data must be fully mature before automation can add value. BigPanda works within real-world data gaps and improves data quality over time as part of normal operations.
ServiceNow customers that integrate BigPanda are seeing ROI quickly. Customers see median returns of 430%, with payback in under a year. The go-live timeline of approximately six months means organizations can begin realizing value before the end of a single fiscal year.
The real goal is expanded operational capacity, not just faster tickets. Speed of resolution matters, but the larger opportunity is freeing skilled engineers from reactive, low-value work. BigPanda and ServiceNow together shift IT operations from a cost center reacting to incidents to a proactive function that protects and enables the business.
