How might AI change the way service-led companies operate?

With advances in technology moving fast, it can be difficult to predict what you might need to run your field service business even five years from now. This is particularly pertinent due to developments in artificial intelligence (AI).

“Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart.”

But, while the potential of artificial intelligence has no ceiling, at Key Computers, we’ve taken a quick look at current developments in AI, and how it might impact your business in the not too distant future.

  1. People being replaced by robots

Every few months a new study seems to hit the headlines, warning us mere mortals that many of us are going to lose our jobs because of AI. However, when we delve down into the detail, in the short-term at least, it appears that these fears are being exaggerated. In fact, according to a recent study[1] of manufacturing and service industries in North America, Europe, Asia-Pacific, and Latin America, when it comes to AI, it is largely computer-to-computer activities that are being automated rather human activities. And this machine-to-machine interaction has the potential to deliver tremendous benefits to service-led businesses.

“Machine Learning is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves”. [2]

  1. AI and customer service

For many service companies, customer issues are still dealt with via call/support centres. But the sheer number of calls being made can make excellent customer service difficult; particularly for non-routine calls. AI technology could provide the answer; taking over basic, mundane tasks, and freeing employees to deal with more complex issues and provide more proactive customer service.

  1. AI and maintenance

Solutions already exist that can calculate when tools or equipment require repairs; so businesses can make fixes or replacements before a breakdown. And, soon, machines that predict when they need maintenance, and automatically order the parts required will be the norm. AI capabilities will also ensure that these machines know when the best time to be taken offline for maintenance is. This bringing together of operational and informational technology can generate savings of up to 12% over scheduled repairs, leading to a 30% reduction in maintenance costs and a 70% cut in downtime from equipment breakdowns.[3]

  1. AI and scheduling

With AI, automating scheduling is easy. Jobs will be assigned to engineers in the field using algorithms and geolocation data; delivering the most efficient use of time possible. Ultimately, this will reduce the time between jobs, ensure your technicians are armed with all the information and equipment they need, and – ultimately – improve your customer service.

Of course, with cloud computing, a lot of this functionality is already available. Indeed, with a fully integrated, cloud-enabled Service Manager you can control stock, manage materials, schedule engineers, control customer data, and manage hire contracts, all from one integrated system. So, it’s no wonder, that connected devices will eventually be used in most, if not all businesses. And that’s before we even look at how such technology can lead to cost savings, new revenue streams, and enhanced productivity. What’s more, as AI continues to advance, its potential when it comes to employee productivity and the automating of business processes is only going to increase.

However, a quick word of warning: to capitalise on the deep learning capabilities of AI, interoperability between devices and systems is a must. So, investing in could-based SaaS now could help your business to future-proof its position and evolve with the development of AI in the upcoming years.

 

To find out more about how we can help your business capitalise on developments in AI, speak to a member of our team on 01942 261 671 or email info@servicegeeni.com to find out more.

[1] Accenture LLP

[2] Forbes

[3] https://www.accenture.com/us-en/insight-industrial-internet-of-things