Identifying agentic AI use cases

The ServiceNow Enterprise AI Maturity Index 2025 found that 43% of organisations worldwide are considering adopting agentic AI in the next 12 months—but just 28% are very familiar with the technology. There’s a gap between organisations investing in it and truly understanding what it can do for their business.

How can leaders close this gap and get more value from their agentic AI investments? It begins with identifying agentic AI use cases in the organisation. Here’s an approach to get you started.

Process mapping

Process maps are a way for organisations to visualise workflows and spot inefficiencies. They can be prepared using Process Mining, which employs data science to discover, analyse, and visualise what business processes look like and how they work.

A process map uncovers bottlenecks and reveals areas that can be streamlined. A clearer view of workflows can help organisations determine if AI agents can feasibly perform a task, and whether the task occurs frequently enough for automation to add value.

The most compelling use cases emerge when AI agents can be orchestrated as a team to automate processes end to end. It’s also important to consider which workflow automation tools AI agents can use to perform the task.

By identifying processes fit for automation, organisations can unlock new productivity benefits. For example, three years since integrating agentic AI into its HR department, a German life sciences company has seen a 45% increase in self-submitted requests. Nearly three-quarters (74%) of all HR requests are now handled by AI agents, and the remaining 26%—more complex or unique requests—are handled by HR professionals.

Vertical and horizontal use cases

Process mapping can reveal two types of use cases for agentic AI. Horizontal use cases affect the entire enterprise. For example, by digitising organisation-wide supply ordering with agentic AI, a global biopharmaceutical leader saved more than 30,000 hours in a year.

In contrast, vertical use cases are function-specific and can directly address the unique challenges of a particular business unit. For instance, after creating more than 600 customer service knowledge base articles with agentic AI, a digital services provider in Ireland achieved a 99% customer satisfaction.

Identifying both vertical and horizontal agentic AI use cases can help organisations achieve a balanced approach to automation. Processes should be considered on a case-by-case basis, focusing on AI agents that offer the most return on investment.

ServiceNow AI Agents are designed to execute tasks and collaborate across IT, HR, customer relationship management (CRM), and more—helping to put AI to work in every corner of the business.

Guided by employee expertise

Individuals in the business who “do the doing” can help identify the most valuable processes to enhance with agentic AI. Speak to your people about which time-consuming, repetitive tasks—known as first-line tasks—can be handed over to AI agents to free up their time.

More relevant automations can help employees reduce the amount of effort they commit to mundane and manual tasks, freeing them to focus on high-priority tasks that require complex problem-solving and decision-making—also known as second-line tasks. Moving employees from first-line to second-line tasks can help drive greater productivity.

Find out how ServiceNow can help you put AI agents to work for people.