For many manufacturers, aftermarket services increasingly account for a significant share of profits, sometimes exceeding those from product sales. These services can provide more predictable cash flow and a valuable competitive edge. And now, agentic artificial intelligence (AI) offers a range of cost-effective ways to enhance them.

Behemoth manufacturers like Bosch and Siemens have already implemented agentic AI, but it's not just for large manufacturers. Here's what you need to know.

A critical piece of the puzzle

Successful manufacturers understand that a sales transaction is only the beginning of a customer relationship. Aftermarket services, such as remote monitoring and diagnostics, maintenance and repairs, and other types of post-sale services, can help customers reduce downtime and, in turn, increase their satisfaction and loyalty. Notably, it's been estimated that the operating margin for aftermarket services is 2.5 times the margin for new equipment sales.

In the past, aftermarket services have often been reactive — such as sending a technician when a customer reports a problem. But agentic AI is empowering manufacturers to take a more proactive approach, with substantial benefits for both them and their customers.

The agentic AI advantage

The term "agentic AI" generally refers to an autonomous AI system that acts independently to accomplish tasks, with minimal human oversight. In other words, it's an AI system that has agency. It can use external tools, such as databases and application programming interfaces (APIs), to develop and execute action plans.

Generative AI tools, such as ChatGPT and Microsoft Copilot, use large language models (LLMs) to generate content in response to user prompts. Agentic AI, on the other hand, employs LLMs as well as technologies like natural language processing, machine learning and reinforcement learning to make decisions based on context. That means AI agents can easily adapt to changing conditions.

Multi-agent systems go even further. As the name suggests, they're composed of multiple AI agents that work collectively in a shared environment to perform tasks for a user or another system. A system might comprise thousands of agents; each has individual properties, but they all work collaboratively to achieve large-scale objectives or complex workflows.

Agentic AI has multiple use cases for manufacturing aftermarket services. It can, for example, take predictive maintenance to another level. Like traditional predictive analytics, AI agents can gather and analyze vast amounts of relevant data, from seasonal variations, life cycle information and service histories to sensor data, technician notes and performance metrics. But they can go beyond that to order replacement parts, locate the right service providers and schedule appointments on a timely basis. They can also leverage this information to optimize a manufacturer's inventory management.

AI agents could even preempt service calls. They can respond to service requests by providing step-by-step instructions that let customers resolve relatively minor issues on their own. This ability may be particularly important for manufacturers that are struggling to hire employees with the necessary skills and expertise to make service calls. Even if you have a healthy workforce, AI agents can complement your employees' abilities and improve their efficiency so employees have more time to focus on their core competencies and higher-value work.

AI agents can crunch the data to adjust service agreements, too. These agreements tend to be complex, with varying requirements for different customer types. AI agents can amend service contracts based on real-time information.

No small task

Agentic AI has the potential to transform your manufacturing company's approach to aftermarket services, but it requires extensive pre-implementation planning. For example, you'll need to determine the areas where AI agents could make a difference, establish clear thresholds for when humans should become involved and ensure your data is "AI ready." The initial stages may seem burdensome, but the payoff could ultimately boost your bottom line. Contact us for help determining if this technology is right for your manufacturing company.