January 21, 2025 How Gen AI Fuels Transformation In Aftermarket Services

In a rapidly changing aftermarket landscape, OEMs who make calculated investments in generative AI can unlock new value for customers.

By Peter Anderson, global supply chain lead, Genpact and
Kunal Kumar, manufacturing leader, Genpact

Do you remember when heavy equipment manufacturers considered aftermarket services a cost center focused on break-fix support for customers and operators? It’s a whole different world now. Original equipment manufacturers (OEMs) are forging a competitive edge by providing operators with comprehensive lifecycle solutions to extract greater value from machines and improve lifetime value. It’s a shift underpinned by advanced analytics and generative AI (gen AI) copilots fueling aftermarket transformation. And it’s a win-win for operators as their end-to-end experience improves from product purchase to its end of life.

Already, 61% of executives and services leaders have earmarked up to 10% of their technology budgets for gen AI, according to HFS and Genpact’s gen AI report. And they anticipate expanding these investments, with an average 30% jump in funding over the next year.

So how can these investments be used to reimagine aftermarket services?

Six strategies to maximize returns from aftermarket services

Here are six ways gen AI can spark commercial innovation, support business objectives, and enhance customer loyalty:

1. Think commercial innovation: As manufacturers try to increase recurring revenue streams from their installed base, gen AI provides a way to mine real-time equipment data and customer interactions to design smart offerings and pricing models. Let’s say, you offer a monthly subscription for a machine’s health report or introduce a new contract tier that offers 24*7 service chatbots. These add-ons can help minimize equipment downtime and improve repeat business. Perhaps more importantly the new tools can drive more profitable business models, such as “power by the hour” (PBH) where a customer pays a fixed hourly rate for the use of equipment.
2. Personalize experience: Gen AI offers new avenues to reimagine service interactions between OEMs and operators throughout the lifecycle of the equipment. Companies can use it to design personalized marketing campaigns and customer success initiatives with minimal effort. It also extends to service interventions by providing a 360-degree customer view through short summaries and next best actions at service interaction points, significantly elevating the experience and improving loyalty.
3. Empower technicians: Suboptimal technician productivity and skills gaps significantly hinder a seamless service experience. But with the adoption of gen AI, you can customize technicians’ work instructions for break-fix events in real-time in their language of choice. This way, you can equip your field technicians with the required knowledge and tackle skills loss due to an aging workforce. Gen AI already assists technicians documenting tech logs more comprehensively. It not only drives higher technician productivity but also helps build a fit for use knowledge bank that trains product failure algorithms for proactive product downtime management. The technology can also assist in creating a more controlled environment, reducing safety incidents and driving employee satisfaction and security.
4. Optimize supply chain decisions: Spare parts supply chain leaders often struggle with dynamic planning and decision-making on refurbishment and repair processes to achieve optimal service and inventory levels. Static dashboards and limited visibility can cloud these decisions. Gen AI’s ability to provide natural language explanations and adaptive visualization helps supply chain leaders take faster and more informed actions to navigate unforeseen events. We will soon be able to proactively direct resources to pre-empt failure, minimizing costs and elevating the customer experience.
5. Integrate self-service support: Over the years, self-serve has become a powerful tool to elevate customer experiences, especially for manufacturers. You can integrate self-serve modules – powered by gen AI bots and search algorithms – within existing customer facing platforms like web commerce and customer portals to cut wait times. You can use these modules in areas such as parts recommendations and real-time warranty adjudication to help customers do business with you.
6. Reimagine regulatory compliance: A large set of manufacturers work in a highly regulated environment and must adhere to post-market quality obligations. They need to meet compliance standards and report on the product safety. Combining gen AI with traditional AI can help meet stringent reporting guidelines, generate comprehensive regulatory reports, and reduce effort and cycle time significantly. An improved track record on safety and product quality drives better service contract penetration, yielding a higher lifetime value.

Developing a shift in mindset to increase gen AI adoption

Manufacturers are finding aftermarket success increasingly important as gen AI fuels service innovation and creates superior experiences. But, to thrive in today’s AI-first environment, leaders must engender a mindset change.

Gen AI is rapidly transforming our world and our personal lives. Although concerns about job displacement are still prevalent and contribute to cynicism, focusing on growth opportunities holds the key. Companies need to encourage a positive outlook and embed a more objective and adaptive approach to enable teams to respond to this technology change. But how?

By investing in reskilling and upskilling programs that equip individuals with the necessary skills for the evolving job market. Along with upskilling your teams, it is crucial to make them aware of long-term gains rather than short-term wins. When leaders take a scalable approach, returns on AI investments can be substantial.

Benefits of gen AI in the aftermarket are real, but don’t overlook its shortcomings

While the benefits of gen AI in the aftermarket sector are substantial, it’s crucial to be aware of its potential drawbacks. Gen AI requires the careful handling of large volumes of sensitive data, raising data privacy and security concerns. It can also be expensive. The initial investment for deploying gen AI solutions includes costs for infrastructure, training, ongoing maintenance, and integration into existing systems. Investments in data may also be required as poor-quality data will lead to incorrect predictions.

Addressing these challenges involves using digital solutions, ethical frameworks, and regulatory guidelines. But it’s worth the effort as the benefits become tangible when you scale gen AI across functions and unlock more creative and personalized aftermarket experiences through new business models.

About the Authors:

Peter Anderson is the global supply chain lead at Genpact, a global professional services and solutions firm delivering outcomes that shape the future. He has led supply chain transformation for more than two decades, previously holding leadership roles at EY, Cummins and WestRock.

Kunal Kumar is a global manufacturing leader at Genpact. He leads strategic initiatives for the company’s manufacturing clients, delivering superior aftermarket services and supply chain outcomes leveraging advanced technologies.

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