Despite previous doubts, AI is becoming something that enterprises see as having a positive impact as it makes human lives easier. In field service, for example, where you have 1,000 tasks and 100 field service technicians available, AI quickly and efficiently determines which technician to send where. With all the permutations and combinations, this is not a task for humans!
AI can access a wealth of historical information (the weather, parts required, at what point in the day the appointment takes place, the number of similar tasks the technician has done and more) to then discern which of these characteristics correlate, and to what extent, with the length of time the task takes. Using this much more complete knowledge, and adding to it over time, the system can use the characteristics of future tasks to predict a likely task duration. This approach is much more effective: customers of ClickSoftware have improved task duration accuracy by 20%, greatly increasing efficiency and customer satisfaction.
Can AI be used to deliver more effective services and processes?
One of the most common use cases for AI in field service is identifying the right field service management resource to address a particular task at a time that makes sense for both the customer and the business. This is a challenging problem that depends on the characteristics of the task and the capabilities of the field service professionals, amongst many other variables, to determine the best solution.
By incorporating AI into field service processes to estimate travel times, task durations and other key components of service delivery, organisations can do more work with the same number of resources. In delivering greater efficiency and resource utilisation, improving effectiveness through better first-time fix rates, and responding faster to emergency situations, the organisation benefits from more accurate resource plans and smaller service windows. Customer satisfaction is enhanced through customers getting a more precise estimate of when service will take place and an overall higher quality service.
How might AI develop moving forward?
AI is still in its infancy, and, while we can surmise about the future, the seemingly endless potential is both promising and intriguing. By helping manage simple customer interactions and streamlining complex processes behind the scenes, AI can become a secret weapon for supercharging customer experience.
Technological advances and saturated markets have led to products and offerings that are very similar, leading companies to compete on price with narrow margins. Companies have a real opportunity to differentiate with service. One example where AI is already helping customer service centres solve the problem of long hold times are chat bots. Chat bots are often able to solve a customer’s problem without wasting the customer’s time waiting for a person to respond.
Other examples of AI in service involve machine learning models predicting with increasing accuracy the likelihood that a customer will cancel an appointment, what parts will be needed to fix a particular customer problem, or the likelihood of a first-time fix.
AI enables service organisations to create new business models where customers pay for uptime, rather than buying or leasing equipment from manufacturers. In this case, it is critical the machines never go down, because the penalties for violating SLAs is costly to service businesses. AI will set predictive maintenance programmes for this equipment, so it is always in good working order.
While the promise of AI is not yet fully realised, there are already many ways to integrate it into existing service and support channels to drive operational improvements. This not only frees employees to focus on important tasks, but also creates new opportunities to delight and retain customers.
Eventually, will AI robots replace human workers?
There’s no doubt that technology is becoming faster, smarter, better – but so far there’s no technology that is not powered, at least initially, by humans. Many jobs, by their very nature, require human intervention, which to-date cannot be programmed into a machine. The world will seemingly always have a need for compassion, empathy, trust and personality, and it will take a long time for robots to learn the social skills that human beings have.
Analysts including Forrester report that automation “won’t destroy all jobs, but it will transform the workforce”. One example of this is how AI can make a positive impact on employee experience within field service. The use of AI will allow dispatchers to become exception handlers, freeing up their time to focus on more strategic priorities, while technicians are able to spend more of their time helping customers.
Rather than replace employees, AI and other automation technologies “can augment human capabilities to help employees do their jobs more efficiently.”
While some jobs may be lost due to AI, automation will still create a new division of labour, with humans being retrained to work in robot support and programming roles.
This idea is supported in a survey by Adecco where almost 65% of senior leaders felt that AI technology would increase the number of jobs available while the majority believed it would make jobs easier and free employees up to work on more important and enjoyable tasks.
Could AI help to close the skills gaps?
While simple and monotonous tasks can be easily automated, gradually resulting in certain roles becoming obsolete, today’s consumers demand an unprecedented level and speed of service. So, AI solutions can be utilised to enhance the ability of technicians to resolve issues on the first visit, or perhaps resolve an issue remotely.
Artificial intelligence and machine learning can help close any skills gaps by applying data on individual performance to the task at hand to determine who is the most adept at a certain activity. If there’s a lack of workers with the skills to complete the task, it is flagged immediately, allowing leaders to either fill the hole or find another solution. Machine learning can hold information on employees’ past jobs and behaviours and make informed decisions to optimise the service provided by engineers.
Organisations can then plug in workers with specific skill sets or credentials to solve problems on demand, as and when they are needed, such as preventative maintenance measures to reduce downtime.
Are there any countries leading the way in AI adoption? Which industries stand to benefit most from AI?
According to media reports, China and the US are leading the way in adopting AI, with the former’s percentage of AI patents granted growing by 190% in a five-year period and the latter investing close to $10 billion in venture capital. Not to be left behind by the other two superpowers though, Russia’s president has announced his intentions to make 30% of its military equipment robotic by 2025.
The compound annual growth rate of AI has hit 60% and is still growing. The UK is itself funding more £603 million investment in AI and one industry here that stands to benefit from AI is field and customer service.
Field service organisations increasingly feel the pressure to maximise the productivity and efficiency of their workforce so they get every job right on the first try, keeping customers happy and reducing costs through increased productivity and SLA compliance. AI makes this possible. AI enables “predictive field service”, which anticipates service requirements and automatically adjusts business processes accordingly. For example, the technology automatically reshuffles technician schedules if there are more optimal ways to deliver service as the day progresses.
If an emergency situation arises, such as a gas leak for a gas utility company, the system can propose how best to address this from a resource perspective, while minimising the impact on other previously scheduled tasks.
Interested in hearing industry leaders discuss subjects like this and sharing their use-cases? Attend the co-located IoT Tech Expo, Blockchain Expo, AI & Big Data Expo and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London and Amsterdam and explore the future of enterprise technology.