5 steps for becoming AI-ready in field service
This post was co-authored by Michael Mendoza, Director of Service Transformation, Hitachi Solutions.
The era of AI came upon us quickly, and many business leaders are scrambling to determine AI strategies that provide the best way forward for their employees and customers alike. The 2024 Microsoft Work Trend Index shows that 79% of leaders agree that their company needs to adopt AI to stay competitive; however, 60% of leaders worry that their organization lacks a plan and a vision for implementing AI.1
Many leaders in service organizations see AI as a boon for providing capabilities that can help them improve operations and serve customers better. After all, these days, high service quality is absolutely critical to driving greater revenue and customer satisfaction. But having a vision for AI and implementing that vision are two different things. Service leaders want to implement AI solutions in the most impactful way possible to ensure that service agents and field technicians alike feel confident using the solutions to help them be more productive throughout the day. And they also want to ensure that customers reap the benefits of these AI solutions as well through more positive and efficient interactions with agents and technicians and faster resolution times.
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The promise of AI for field service organizations
Enabling quick, first-time resolution of customer issues in the field is critical to ensuring the efficiency of service operations and providing the best possible experience for customers, to help build loyalty and grow revenue. Arming field technicians with intuitive, AI-powered solutions that combine capabilities such as workflow automation, scheduling algorithms, and mobility can significantly enhance service outcomes. Research shows that high performing field service organizations have been early to embrace AI and automation to help improve job performance—and 93% of mobile workers in high performing organizations also report job satisfaction as a significant benefit.2
A key area for modernizing field service and improving operational efficiency is automation. Over 60% of frontline workers like service agents and field technicians struggle with having to do repetitive or menial tasks that take time away from more meaningful work. According to a recent McKinsey study, service organizations have the potential to use AI-powered workflows to help automate tasks that currently take up to 70% of field service employees’ time.3 This means that both agents and technicians can get back time that lets them focus on servicing more customers.
And all of this is good news for business: more than 55% of GDP gains by 2030 are expected to be driven by improved labor productivity powered by AI.4 Smart service organizations know that strategic implementation of AI-powered solutions helps agents and technicians find information and experts, personalize service, and automate mundane tasks. So the question is: Where to begin?
Preparing field service for AI
The benefits of AI—improved service, increased efficiencies, and deeper business intelligence—to name a few—are clearly compelling. But successfully implementing AI solutions and making them part of the organization’s work culture requires careful planning and certain key steps.
We’ve identified five critical steps to help field service organizations prepare for implementing AI solutions in a way that benefits employees and customers alike.
Step 1: Focus on a framework for capturing and proving business value
Proving business value is absolutely critical to the success of any AI strategy. Field service leaders must identify their overall goals for adopting AI solutions, ensuring they are relevant and aligning them with the organization’s overall priorities for the business. They must consider the specific goals, whether they include optimizing processes for faster service resolution, improving customer experience by enhancing key customer touchpoints, or increasing overall revenue by servicing more customers. Then, they can identify their key performance indicators (KPIs) aligned with these goals, such as resolution rates, customer satisfaction scores, or revenue goals.
Step 2: Evaluate the use cases for AI applicability
Once the high-level objectives are clear, field service leaders should take a closer look at daily operations to understand where AI solutions can most help them improve. For example: Do service agents waste a lot of time responding to and managing customer email, or searching for customers’ service history? What processes are they using to schedule field technicians? Do they need help automating scheduling and filling gaps for service? In the field, do technicians need better access to service manuals or technical experts that can help them resolve issues quickly?
Identifying these use cases can help field service leaders understand which areas could benefit from AI-powered solutions most quickly to gain quick wins, and which AI use cases might take more time and training to implement.
Step 3: Enable innovation and collaboration early on
The whole idea behind adopting AI-powered solutions for field service is to help break down information and communication siloes and improve processes to increase efficiency and keep customers happy. The right AI tools provide clear visibility into processes, surface experts and other critical contacts, and enable collaboration to resolve customer issues—all within the flow of work.
Step 4: Design for iteration, feedback, and agility
Empowering field service organizations with AI-powered, low-code solutions provides the opportunity for field service teams to develop and test new apps and processes quickly. This keeps the service organization agile and helps it do a better job of both meeting the demands of the business and improving customer experience. For example, the ability to tweak a new automated scheduling process based on real-time feedback from field technicians could show immediate benefit in helping technicians reach more customers and resolve more issues each day.
Step 5: Ensure training and enablement to drive adoption
While resistance to change can sometimes be a barrier, the latest Microsoft Work Trend Index shows that when it comes to AI, employees are ahead of employers when it comes to being ready. However, even the most exciting technologies can end up on the shelf—so to speak—once the novelty has worn off. That’s why field service leaders need a clear plan for driving adoption and training for AI solutions. Selecting an AI solution provider that provides training resources, along with developing internal champions within the field service organization, can help employees feel more confident about when and how to use AI solutions in their daily work.
Making the AI vision a reality
AI has the power to drive new levels of productivity and efficiency in field service, so it’s critical to take the right steps to ensure your organization has the most effective approach to adopting—and gaining the most value from—AI solutions. If you want to learn more about how to turn your AI vision into a reality, register for our upcoming webinar.
Sources:
1 2024 Work Trend Index Annual Report, AI at Work Is Here. Now Comes the Hard Part, May 2024
2 ZDNET, AI improves field service quality and customer experience, January 2023
3 McKinsey Digital, The economic potential of generative AI: The next productivity frontier, June 2023
4 PwC, Sizing the prize: What’s the real value of AI for your business and how can you capitalise?
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