Enterprises Looking to AI for Smarter IT Management

Enterprises are turning to AI-powered software platforms to make IT management more intelligent and ensure their systems and technology meet business needs for efficiency, lowers costs and innovation, according to new research from global AI-centered technology research and advisory firm Information Services Group (ISG).

The ISG Buyers Guides™ for IT Management, produced by ISG Software Research, find AI plays a growing role in comprehensive software frameworks for IT observability, operations management and FinOps. The need for IT management software is growing, the research says, as enterprises transition to more agile and cloud-centric architectures. AI-powered software is also helping enterprises manage and optimize the delivery, performance and responsiveness of IT services.

"IT leaders need effective operations and service management more than ever for resilience and long-term success," said Jeff Orr, Research Director for IT, ISG Software Research. "Enterprises are adopting multiple tools and platforms to support ongoing IT innovation while controlling costs."

Economic pressures, heightened cybersecurity risks and the growing need to support hybrid and remote workers have intensified the need for software that helps manage and operate IT systems and services. CIOs and IT leaders often cite these trends when building a business case for new investments in this area, ISG says.

Enterprises are strategically integrating AIOps, which uses machine learning to automate IT processes, and holistic observability practices, which help companies understand the state of IT systems through their outputs, the reports say. Together, these approaches enable real-time monitoring of application performance and infrastructure health, and provide the ability to predict and mitigate potential issues, allowing companies deliver high-quality IT services with less manual intervention. Through 2026, ISG expects 40% of enterprises to fund AIOps strategies to streamline operations and optimize resources.

AI is enabling IT teams to generate insights from vast amounts of data, the reports say. By 2027, ISG expects software providers to release GenAI-driven tools for processes such as incident management, resource allocation and performance forecasting. GenAI is also changing IT service management, introducing features such as automatic command-line generation to help teams handle service requests.

In the future, agentic AI will enable intelligent workflows with semi-autonomous actions and decisions to manage incidents in real time, ISG says. Self-healing mechanisms driven by agentic AI may be able to resolve issues automatically, allowing IT teams to focus on strategic initiatives. However, the reports say, enterprises need to be aware of unique challenges involving governance, compliance, business risk and other aspects of these emerging technologies.

As companies move more data and workloads to the cloud, FinOps is becoming a critical tool for managing costs and finances. FinOps strategies foster collaboration among finance, IT and business teams to share responsibility for managing costs and resource consumption. ISG expects one in five enterprises to invest in coordinated FinOps efforts by IT and finance departments through 2026.

"CIO and IT leaders are looking to unify the management of their IT environments and technology services through software made more intelligent with AI," said Mark Smith, chief software analyst and partner, ISG Software Research. "For the first time, our portfolio of IT management software research introduces a unified framework for evaluating software providers and products operating in this space."

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Enterprises Looking to AI for Smarter IT Management

Enterprises are turning to AI-powered software platforms to make IT management more intelligent and ensure their systems and technology meet business needs for efficiency, lowers costs and innovation, according to new research from global AI-centered technology research and advisory firm Information Services Group (ISG).

The ISG Buyers Guides™ for IT Management, produced by ISG Software Research, find AI plays a growing role in comprehensive software frameworks for IT observability, operations management and FinOps. The need for IT management software is growing, the research says, as enterprises transition to more agile and cloud-centric architectures. AI-powered software is also helping enterprises manage and optimize the delivery, performance and responsiveness of IT services.

"IT leaders need effective operations and service management more than ever for resilience and long-term success," said Jeff Orr, Research Director for IT, ISG Software Research. "Enterprises are adopting multiple tools and platforms to support ongoing IT innovation while controlling costs."

Economic pressures, heightened cybersecurity risks and the growing need to support hybrid and remote workers have intensified the need for software that helps manage and operate IT systems and services. CIOs and IT leaders often cite these trends when building a business case for new investments in this area, ISG says.

Enterprises are strategically integrating AIOps, which uses machine learning to automate IT processes, and holistic observability practices, which help companies understand the state of IT systems through their outputs, the reports say. Together, these approaches enable real-time monitoring of application performance and infrastructure health, and provide the ability to predict and mitigate potential issues, allowing companies deliver high-quality IT services with less manual intervention. Through 2026, ISG expects 40% of enterprises to fund AIOps strategies to streamline operations and optimize resources.

AI is enabling IT teams to generate insights from vast amounts of data, the reports say. By 2027, ISG expects software providers to release GenAI-driven tools for processes such as incident management, resource allocation and performance forecasting. GenAI is also changing IT service management, introducing features such as automatic command-line generation to help teams handle service requests.

In the future, agentic AI will enable intelligent workflows with semi-autonomous actions and decisions to manage incidents in real time, ISG says. Self-healing mechanisms driven by agentic AI may be able to resolve issues automatically, allowing IT teams to focus on strategic initiatives. However, the reports say, enterprises need to be aware of unique challenges involving governance, compliance, business risk and other aspects of these emerging technologies.

As companies move more data and workloads to the cloud, FinOps is becoming a critical tool for managing costs and finances. FinOps strategies foster collaboration among finance, IT and business teams to share responsibility for managing costs and resource consumption. ISG expects one in five enterprises to invest in coordinated FinOps efforts by IT and finance departments through 2026.

"CIO and IT leaders are looking to unify the management of their IT environments and technology services through software made more intelligent with AI," said Mark Smith, chief software analyst and partner, ISG Software Research. "For the first time, our portfolio of IT management software research introduces a unified framework for evaluating software providers and products operating in this space."

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Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

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As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

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