Whether for simple DIY or sophisticated technical projects, inside everyone is an expert waiting to be unleashed.
This statement is sure to provoke skepticism in everyone from seasoned handymen to industry novices. One might scan the room they’re in to assess whether they could fix miscellaneous items that broke or became faulty. A frozen clock on the wall, perhaps. A blinking television set, maybe. The mysterious failure of a customer’s diagnostic equipment? Never.
But in the same way user manuals can walk the average person through simple projects without fuss, the growth of remote visual assistance is destined to fulfill the same function, offering access to rapid fixes and real-time education with the touch of a button on a smartphone. Artificial intelligence (AI) and augmented reality (AR) are the keys opening this proverbial door.
Depending on the level of integration remote support platforms have with a company’s job management software, days and hours are condensed into minutes and moments in delivering rapid, intelligent, and customized advice or problem resolution.
If scenarios like these are already a reality for numerous consumers and the experts who serve them, more widespread adoption invites a few questions: What does the future hold for field service? Just how far can technology go in bringing out a problem-solver even to someone new on the job? Perhaps most importantly, what benefits will be delivered for professionals who have dedicated their careers to maintaining the tools that enrich and sustain our lives?
Introducing AI and AR
AI and AR are two fundamental tools used to power remote assistance programs. Still futuristic in the public imagination, yet tried and tested by experts, companies have frequently tapped into them for myriad uses. IBM’s deployment of AI in its human resources department, for example, made headlines last year with initiatives like a “Netflix for employee development” and training, with AI reportedly saving the company nearly a billion dollars overall.
Evidence points to a much greater virtual presence in enterprise operations and, by extension, in daily life as service digitization expands. Just over a quarter of organizations in a large-scale 2021 survey said they operated revenue-generating AI projects, with another 35% indicating they had evaluated or tested such projects.
Well before the COVID-19 pandemic, an IDC study shared the prediction of a year-on-year increase of 78.5% in spending on AR and virtual reality (VR) technologies between 2019 and 2020, reaching just under $19 billion. The company’s projections for the global AI market were nearly a third of a trillion dollars by 2021, including spending on software, hardware, and services.
But skepticism is still there, as is widespread misunderstanding and fear about perceived threats posed by the wider integration of AI and AR into daily life. The idea that these tools will replace, rather than augment, human work and creativity continues to be the most harmful.
As such, adopters of these technologies need two things to achieve success. The first is a positive, transparent, and consistent message about how this technology will help ordinary people. The second, with supportive data behind them, should be clear goals and objectives in improving specific performance indicators. And few use cases are as real and meaningful as reimagining the customer experience.
AI and AR for Superior Knowledge Transfer
The use of AI and AR for remote repair and maintenance, helping and training customers and the technicians who serve them, arguably ticks both above boxes for a wide swath of companies.
These technologies lend themselves well to training – being intuitive, adaptable, and easily incorporated into a range of operations and functions. AR-powered support often features tools that allow both customers and support workers to make drawings or marks on each other’s screens, potentially eliminating confusing back-and-forth communication over identifying a small or obscure part or component.
AI, either coupled with or independent of AR in a visual support tool, can store information from a visual support session, which is then fed into a database of digitized knowledge that can detect patterns and make recommendations accordingly. Faster and more responsive work can result in productivity improvements between 25% and 50% in completing complex tasks.
AR has the potential to more than double learning outcomes compared to traditional training environments. Companies with minimal time to train a new worker or an existing technician on a complicated skill can potentially place them on a job site and provide immersive learning in real-time, with a remote expert guiding them through a task or through wearables like headsets that can provide instructional overlay.
To return to the example of diagnostic equipment, imagine that a field technician arrives at a job site to find it malfunctioning due to a small, broken part they have trouble identifying on their own. Remote support can bypass the traditional, time-consuming route of calling or requesting someone more senior. With a few taps inside an app on the technician’s smartphone, they are connected to an off-site expert who can not only walk them through the identification of the part but also order a new one for delivery then and there.
Removing several steps in the process frees up everyone to deal with more meaningful tasks – customers included. Productivity increases when a technician can accommodate more appointments in their day. And customer satisfaction improves when the expectation of a lengthy, complicated process is met instead by a succinct fix that puts their appliance back together and returns them to their day.
How Will Field Service Be Further Transformed?
Customer relationship expert Steven van Belleghem’s research found that 40% of people prefer self-service to human contact. The concept of AR- and AI-powered interfaces guiding them through simple fixes on their own with minimal or no technical involvement already exists in the field.
But given the sheer potential of these technologies, it’s worth asking just how central this will be to future service models. How much will customers want to fix on their own, particularly without companies facing a potential backlash for the perception that responsibilities and duties are being passed off? Do the limits of AR and AI technology determine what fixes are too complicated for people to perform themselves, or is this determination made another way?
These may remain open questions for some time. But currently crystal clear is that making knowledge long considered the purview of experts more accessible to everyone is a matter of quality of life – and an increase to your bottom line. When simple problems come with simple resolutions, and answers are more quickly at people’s fingertips, they can spend more time thinking, creating, and doing what matters most. The world, in turn, becomes a better place.
