Enterprise IT Leaders are at the forefront of AI transformation. Companies are invested heavily in technology and are responsible for their implementation. They are tasked with delivering innovation at speed, reducing costs, increasing productivity and generating business growth.
But the pressure is increasing and the problems are increasing. July Report, title by MIT Gen AI divide: AI status in Business2025revealed that 95% of organizations are seeing zero returns despite corporate investments of $3-4 billion in generated AI.
The problem isn't the lack of technology or IT talent. It seems to be the approach adopted by companies. The report found that 80% were researching or piloting Genai tools such as ChatGpt and Copilot, and nearly 40% were reporting their deployment. However, these tools are designed to increase individual productivity rather than profit and loss performance.
As a result, generic AI tools are used as add-ons to projects and processes and do not drive the meaningful strategic and structural changes needed to provide returns. This is bad news for enterprise IT leaders who are tasked with increasingly cleverly strengthening what employees can achieve without increasing or decreasing their employees. To do this, leaders need to reset their enterprise IT economics by using AI to create value rather than cost.
Enterprise Grade Agent AI
AI agents can provide solutions. Agents are software systems that use AI to autonomously execute tasks, reasons, plans and learning to achieve goals on behalf of users.
Ali Siddiqui is the president of BMC Helix, providing out-of-the-box AI agents for core IT functions, allowing businesses to create custom agents to suit their unique needs.
He says agents can help enterprise IT leaders deliver laser-centric AI projects that solve specific business problems, increase productivity and gain ROI.
“The massive shift that is especially needed within it is to provide a measurable business impact,” he says. “In particular within enterprise software, these supercharged AI agents allow CIOs to automate full business functions. Agents can do autonomous work with little or no human intervention. This reduces the stress on human employees and allows them to focus on innovation and strategic work.”
The need to move from popular AI tools such as CHATGPT to enterprise-grade AI agents is clear. However, the MIT report revealed that most custom or vendor sales systems have been denied. Though 60% of organizations evaluated the potential of these tools, only 20% reached the pilot stage, with only 5% of production. Fragile workflows, lack of contextual learning with existing day-to-day operations, and false alignment were cited as major issues.
Building and Scaling AI Agents
However, those affiliated with external providers enjoy twice the success rate of internal builds. Siddiqui says the starting point for IT leaders is to identify profitable use cases and build agents using the platform. “Internally, IT leaders need to get executive sponsorships, so they need to choose the right starting point,” says Siddiqui. “This means identifying a single, clear business feature and use cases that can be automated and delivered ROI. From there, you can expand your use cases. If you choose a provider that specializes in that feature, you will have access to a fleet of agents outside the box that are ready.”
IT teams are often overwhelmed by time-consuming routine tasks that can be easily automated using a fleet of BMC Helix's GPT-driven AI agents. Autonomous Incident Response Agents can automatically detect, triage, and resolve common IT issues, such as server downtime and configuration drift. Service teams can also use agents to increase productivity by resolving frequent queries such as password resets and access requests.
Security is another area that teams can deal with. Agents can be built to identify potential costly risks and increase resilience. By identifying vulnerabilities, recommending solutions, and simplifying root cause analysis, agents can reduce the number of change-related incidents. Completion of complex tasks such as analyzing organizational knowledge is also enhanced by using agents to remove silos and extracting insights from multiple departments to improve human decision-making.
Human-centered strategies
But if a fleet of AI agents can perform much of the human work, what does this mean for the IT team's future career prospects? This is a question that Siddiqui regularly faces. Here, education and communication are important to ensure change in derisk for IT leaders and to gain buy-in. Not only from the CFO, but also from the workforce facing a new future, not just from the colleagues.
“Leaders need to work with stakeholders to clarify their use cases and how agents will enhance their work,” says Siddiqui. “First, agents are released by focusing on projects that actually show how they will affect the final line. Second, one of the biggest opportunities is to reduce non-head count spending, such as LLM and capacity costs.
Hundreds of companies are already embracing the power of BMC Helix's AI agents. One of the company's biggest clients handles approximately HR 3 million cases per year. However, autonomous AI agents have enabled client teams to access an instant summary of cases (small but repetitive tasks). Similarly, employees at this customer's support desk can use an agent called Helix GPT Service Collaborator to get a quick answer to questions about cases. Support Professional Agent Support is multiplying productivity by providing actionable insights and providing advice for faster incident resolution. Overall, Helix GPT saved customers $2.9 million a year.
Agents also help businesses predict the future. A Network Operations Center (NOC) is a command center that monitors, manages, and maintains networks, servers, applications, and other critical IT infrastructure. Much of their time is spent dealing with incident management. However, agents can predict most issues long before they impact the customer experience, helping IT leaders improve customer satisfaction and retention. This allows you to scale your performance and provide a measurable ROI for AI.
For more information about Agent AI scaling, visit BMC Software
Enterprise IT Leaders are at the forefront of AI transformation. Companies are invested heavily in technology and are responsible for their implementation. They are tasked with delivering innovation at speed, reducing costs, increasing productivity and generating business growth.
But the pressure is increasing and the problems are increasing. July Report, title by MIT Gen AI divide: AI status in Business2025revealed that 95% of organizations are seeing zero returns despite corporate investments of $3-4 billion in generated AI.
The problem isn't the lack of technology or IT talent. It seems to be the approach adopted by companies. The report found that 80% were researching or piloting Genai tools such as ChatGpt and Copilot, and nearly 40% were reporting their deployment. However, these tools are designed to increase individual productivity rather than profit and loss performance.
