AI agents are transforming managed service operations—and clients’ businesses

AI agents are transforming how managed service providers (MSPs) deliver IT support to their customers. But it’s also transforming their clients’ businesses. As MSPs introduce greater automation to IT processes, they pass on the benefits to their clients: cost reduction, improved operational efficiency, and the opportunity for businesses to become more strategic, competitive, and innovative.

Using agentic AI, MSPs can move from reactive troubleshooting to proactive and predictive IT support. And in fact, 71% of organizations are actively exploring AI-driven IT service management solutions to enhance efficiency, reduce ticket volumes, and improve service delivery, according to “The state of AI in ITSM, 2024 and beyond” by the Service Desk Institute.

“Forward-thinking MSPs use automation as a foundational strategy to redefine their operations, deliver exceptional value, and differentiate themselves in a crowded market,” noted the article “Staying ahead of the curve: 7 ways automation keeps your MSP competitive.”

What are AI agents?

“Agentic AI” refers to AI systems that are designed to act autonomously and that take initiative to achieve a goal—with minimal human intervention. In the realm of IT, agentic AI can automate myriad tasks, including help desk ticketing, system monitoring, and incident resolution (see Table 1). With agentic AI, MSPs can create massive efficiencies for customers, avert system downtime, shore up cybersecurity vulnerabilities, and enable strategic innovation.

In manufacturing, AI agents can predict equipment failure or dynamically adjust production plans and inventory levels to match market needs. In banking. In community banking, ,AI agents can significantly reduce the time taken to complete a loan approval complete tasks, from days to mere minutes. And in law firms, AI agents can assist with tasks like drafting legal documents, conducting legal research, and analyzing contracts.

The AI agent market is poised to grow. According to a study by Boston Consulting Group, the AI agents market is projected to grow at a 45% compound annual growth rate through 2030. This growth is fueled by the need for real-time service delivery and proactive problem solving. These AI agents are evolving from simple reactive tools into proactive systems that plan, make decisions, and adjust as situations change.

How MSPs use AI agents to raise the bar for businesses

Industry observers say that MSPs have to get onboard with agentic AI to improve their own processes and those of their customers. In 2023, more than 60% of MSPs and enterprises shared a desire to adopt AIOps (or AI for IT operations).

“In an AI-driven business landscape, inaction is a strategic disadvantage for MSPs—and their customers– surrendering market share to competitors that effectively use automation to deliver efficiency and proactive services to clients,” noted Dr. Brian Luckey, Integris’ chief information officer. “A next-gen MSP doesn’t just manage devices or technology. It shifts to a modern, cutting-edge, and holistic MSP model that focuses on managing clients’ entire digital estate—powered by AI.”

AI agents can be effective partly because of how they use “unstructured data”—that is, data that lacks a pre-defined data model or schema—making it difficult to organize and analyze. As a result, companies typically use only about 10% of their data because it is so difficult to work with. But AI agents make it possible to access and act on the remaining 90%, much of which is unstructured or previously inaccessible. This leads to better and more efficient decision making as well as improved use of an organization’s business information.

AI agents also reduce human error by automating repetitive tasks, analyzing patterns to predict mistakes, and providing real-time guidance to prevent errors before they occur, resulting in up to 85% reduction in operational mistakes.

Smaller businesses are now recognizing the value of agentic AI in IT. In fact, according to Salesforce data, 78% of small and midsize businesses (SMBs) using or planning to use AI view it as a game-changer. What’s more, with agents handling high-volume and repetitive work, 85% say it can help scale operations and improve margins in ways that used to be out of reach for smaller organizations.  

Key areas where MSPs are using AI agents

According to PwC’s “AI agent survey,” organizations are already generating return on AI agents in a variety of areas: 66% say they have experienced “measurable value” in productivity, 57% in cost savings, and 55% in faster decision making.

Infrastructure monitoring and remediation. With automated monitoring, AI agents can continuously monitor server metrics such as CPU and memory usage, identifying anomalies and potential issues in real time. With human-monitored systems , it could take 24 to 48 hours to detect, diagnose, approve, and allocate infrastructure resources to address this issue, noted Luckey.

By contrast, an AI agent can automatically identify the issue, communicate with a customer, and either allocate resources or reboot the server As Luckey noted, the process is completely automated. Rather than responding to equipment failures, predictive maintenance with agentic AI identifies anomalies, equipment wear patterns, and environmental variables leading to subsequent possible breakdowns. 

According to IBM, predictive monitoring/maintenance reduced unexpected downtime in a manufacturing facility, creating a 5%-15% increase in equipment effectiveness.

Device monitoring and alerts. Endpoint device management and monitoring are business processes that greatly benefit from automation. Device monitoring is a continuous cycle that needs to be observed and optimized as operations scale and new information becomes available, all of which lends to automation. As workforces become more distributed, and as bring-your-own-device (BYOD) policies become pervasive, device monitoring tasks proliferate.

As remote work, cloud services, and BYOD policies become standard in various industries such as legal, AI helps organizations keep everything under control without IT having to lock everything down. 

Backup and disaster recovery. Data and software backups are essential for any future-proofed business. For MSPs, a DR/BC strategy presents an opportunity to offer simplified and automated backup solutions. Cloud-based backup systems that can be easily monitored, scheduled, and managed are key for next-generation backup.

When backups fail,  diagnosing the issue requires manual log analysis, a resource-intensive process that consumes significant time and directly translates into operational costs. With AI agents identifying errors, it can reduce recovery time. And when every minute of downtime costs hundreds of thousands of dollars, those time savings are critical.

Help desk transformation. AI assistance transforms how technicians approach ticket resolution. With real-time support and automated triage, teams can focus on complex issues while routine tasks are handled automatically. This leads to significant improvements in response times and service consistency.  

Intelligent ticket management. End-to-end ticket resolution automation handles routine issues without human intervention. Smart classification and routing ensure that tickets reach the right resources immediately, while built-in sentiment analysis helps prioritize urgent customer needs.

In industries such as banking, agentic AI is also having a massive impact on customer service. AI-powered systems, such as chatbots and automated workflows, ensure that customer inquiries are addressed instantly. Whether it’s resolving basic queries or directing customers to the right department, AI eliminates long customer wait times, improving the speed of service. Higher-level issues, as in other domains, are escalated to human workers.

Patch management. Patch management finds vulnerabilities in your IT systems and applications. AI agents can significantly enhance patch management by automating tasks like vulnerability scanning, patch prioritization, and even automated remediation. 

Regulatory compliance automation and fraud detection. With agentic AI streamlines reporting and monitoring, reducing costly manual interventions in various industries, including banking. Fraud detection brings massive improvements as AI monitors transactions in real time, flagging anomalies before a security breach can occur.

Research, content generation, and workflow automation. Agentic AI in law firms, for example, enables lawyers to develop contracts, briefs, and other legal documents more efficiently. One law firm has begun deploying two agentic AI-assisted contract tools that have achieved up to 92% accuracy, a higher rate than most large language model-based tools.

AI is also having a massive impact on fraud detection. HSBC bank, for example, has significantly improved its fraud detection capabilities by integrating AI into its risk management systems. As a result, it has reduced fraud false positives by 60%.

Workflow automation. Automated script generation and debugging streamline common tasks, while contextual customer replies ensure consistent communication. Alert ticket resolution can happen automatically for known issues, reducing the noise in the system and allowing teams to focus on genuine problems.

Knowledge base enhancement. According to some data, 80% of support tickets are for issues that have already been addressed in existing knowledge base. With AI-developed knowledge bases, technicians can quickly search past tickets and solutions using natural language queries, while automated knowledge base ingestion ensures that information stays current and relevant.

At Integris, for example, the  technology teams are developing a knowledge base using AI, based on previous ticket information, client guidebooks, and training documentation. When an IT incident takes place, help desk technicians can use on-demand knowledge from these various sources to resolve the problem without having to escalate the ticket to higher-level engineers. This enables junior level technicians to address issues efficiently while also enhancing junior technicians’ skills.

AI agent best practices: Start incrementally

But as industry participants have noted, automation requires real analysis and process optimization before organizations can automate workflows. Further, data inputs must be up-to-date, clean, and accurate, noted Luckey–otherwise a company’s digital estate may include automation, but on fragile foundations.

This means MSPs need to take the time to understand and analyze a company’s workflows and objectives before introducing AI agents. Processes may also need to be revamped before they can be automated.

“MSPs have a tendency to rush into the automation process, not understanding the foundational work or strategy required,” Luckey noted. “Ensuring the data in which the processes will rely on is clean, consistent, and standardized is critical for success. Automation struggles with ambiguity and thrives on predictable inputs.”

Finally, note that while AI can reduce human error and the need for human intervention, organizations should still begin incrementally and pilot AI agents in low-risk areas of the business. As one industry observer predicts in an article on the potential failures of AI agents, “The successful applications will be in areas where the tasks are highly standardized, the consequences of errors are low, and human oversight is built into the system.” As you consider how your own MSP uses automation, here are some key points to ask about—does your MSP take this approach?

• Start small and targeted. Don’t try to automate entire workflows. Identify narrow, well-defined tasks where you can easily measure success and failure.
• Maintain human oversight: Retain human monitoring of how agentic AI handles a given workflow, and always have humans in the loop for important decisions.
• Build in failure. Assume an AI agent will make some mistakes and build systems to catch and correct those mistakes quickly. This plays into starting small and iterating as flaws emerge.
• Nurture human expertise. AI agents should supplement, not replace human expertise. Maintain the ability to do critical tasks manually.

And if you’re looking for areas where MSPs might be introducing automation, check out Table 1. It depicts IT service delivery tasks that MSPs are now introducing into their own and their customers’ environments. Consider asking your MSP whether it’s automating these areas—and whether they have demonstrable results:

Table 1: How MSPs are using AI agents; Source: “From Reactive to Proactive: How AI Agents Transform MSP Service Delivery,” ZofiQ