Bridging the Service Gap: How AI Transforms the Service Lifecycle – and All of the Jobs Involved


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Manufacturers and servicers of complex machines and equipment face a significant challenge in the industry – the service gap. This gap arises from the constant growth in product complexity, attributed to the rapid pace of innovation and the introduction of new features such as remote connectivity, IoT, and more, coupled with a shortage of skilled technicians and limited service capacity. This gap impacts all members of a service team, including service leaders, field technicians, customer service representatives, and end-customers, and can be a considerable roadblock.

However, AI is emerging as a powerful solution that can help bridge this gap and revolutionize the service journey for all stakeholders involved. And now with the emergence of generative AI and the momentum it brought to market, more and more service teams, in a broad range of industries anywhere from medical device to printing to food equipment, are keen on investing in solutions that will help alleviate the challenges associated with the gap, enhance the customer experience, and maximize the uptime of the machine for the customer.

Empowering Every Participant in the Service Lifecycle

Whether you’re a vice president, executive, day-to-day service manager, field technician, call center agent, or a customer, AI has the potential to offer expert guidance, enhance decision-making, and streamline processes at every stage of the service cycle. AI that comprehends the context of each issue and the unique characteristics of your industry can be a game-changer, creating value for all. Here’s how AI technology is transforming the service journey for each stakeholder:

VPs and Executives:

AI is enabling VPs and executives to proactively generate analytics that provide valuable insights. These insights empower them to make better business decisions, guide strategic operations, mitigate escalations, and facilitate organizational growth. With AI-generated analytics, they can effectively identify trends, allocate resources efficiently, and drive the company towards success.

Day-to-Day Managers:

AI offers daily updates that include performance metrics and resource allocation guidance. This data pinpoints team strengths and weaknesses, enabling personalized coaching and feedback. Managers and directors can assign work based on agent and technician strengths and experience, ensuring a more efficient allocation of resources and improved overall performance.

Field Workers, Technicians, Support Agents:

Field workers, technicians, and support agents can instantly access AI-powered resources to troubleshoot and resolve issues effectively. AI can predict potential equipment failures, enabling proactive maintenance and reducing downtime. This not only saves time and resources but also enhances the overall reliability of the equipment.

Call Center Agents:

AI technology assists call center agents in diagnosing issues correctly with personalized guidance for each machine or client. Automated prompts can help agents ask questions in multiple ways, resulting in instant responses that guide customers to address issues remotely. Call center agents can also provide comprehensive intelligence to field teams before their arrival, improving efficiency and increasing the likelihood of fixing the issue on the first visit.


Customers now benefit from personalized recommendations and solutions based on their specific needs. AI can automate self-service interactions, reducing the need for agent assistance and providing quick, efficient solutions to common issues. This enhances the overall customer experience and satisfaction.

The service gap has been a persistent challenge for manufacturers and servicers of complex equipment for a while now. However, AI is ushering in a new era, transforming the service journey for all stakeholders and encouraging teams to lead with a “shift left” approach to service. Embracing a ‘shift-left’ approach is increasingly recognized as an industry best practice, playing a pivotal role in transforming the customer service landscape. This strategy entails moving away from field-based engagements and customer escalations and towards emphasizing remote solutions and self-service.

With AI’s ability to understand context and industry-specific nuances, it offers expert guidance at every stage of the service cycle, making optimal decision-making a reality for all. From VPs and executives to field workers and customers, AI is reshaping the service landscape, ensuring efficiency, accuracy, and satisfaction for everyone involved. As we move forward, AI will continue to play an instrumental role in bridging the service gap, shifting the service journey left, and improving the lives of all participants in the service journey.

Assaf Melochna
Assaf Melochna’s experience includes strong leadership skills built upon a strong technical foundation. He is an expert in service, and has business and technical expertise in enterprise software. Assaf started Aquant with his co-founder Shahar with the vision of helping service companies transform the way they deliver service through data and AI. Prior to starting Aquant, Assaf spent 10 years at ClickSoftware where he served in various positions.


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