By Derek Handova

Artificial intelligence and machine learning are speeding up the process of automation and support for mobile and remote workers, freeing skilled workers from routine tasks like setting up instances and on-boarding users to concentrate on more value-added activities, such as custom coding, tighter integration between cloud platforms, and more bulletproof APIs and UXs.

A recent Mobi (acquired in December by Tangoe) mobility landscape survey of 100 US IT decision makers at companies with at least 5,000 employees found that 88 percent are either deploying or planning AI-driven automation initiatives, with 75 percent of those underway already seeing return son their investments.

Tangoe’s Josh Garrett

“One of the biggest takeaways from this survey is that IT decision makers understand the enterprise mobility landscape is changing,” said Josh Garrett, president, MMS at Tangoe, which enables enterprises to centralize, comprehend and control their connected devices. “AI and 5G are no longer just futuristic concepts — they’re taking shape in businesses today and changing how we work. What businesses now need to focus on is how to manage an evolving mobile ecosystem.”

For example, Mexico-based MejorTrato, a financial products comparison website, has 34 remote employees across Latin America involved in customer service who spend two-thirds of their time reading client questions, finding the answers and replying. Today, AI using TensorFlow automates this task and stores the information in an internal database. Now employees have more time to contact important clients and learn what new services the company can develop and grow, noted Cristian Rennella, CEO and co-founder of MejorTrato.

“AI is helping with already asked questions, so we can invest more time to answer questions that we have never seen before,” Rennella says. “And only humans can do the new ones. In the future, this will help AI because we upload those new answers to the database.”

On-Boarding, Churn Reduction

One of the key challenges for companies when it comes to remote workers is speeding the on-boarding process and reducing employee churn. Fortunately, there are several ways that AI, automation and bots can help.

Genesys’ Graeme Provan

“The on-boarding process can be faster and simpler using AI and robotic process automation to help with learning and development,” said Graeme Provan, global director of business automation, Genesys, provider of omnichannel customer experience and contact-center solutions. “AI-powered bots can also see repetitive actions, learn the employees’ workflow, determine which actions are taking the longest time to do and find where there’s significant business benefit in automating those actions.”

For example, when AI is purposefully utilized by an employee, the company can have the bot walk the employee through actions in “teach me” mode or even automate the entire activity.

“This is powerful because remote employees use this capability to learn how to perform tasks while on the job,” Provan says. “And the enterprise can centrally monitor or manage how the bots are used.”

Advanced automation tools can also …

… accelerate the on-boarding of new clients or execute service requests from MSP tenants. This will offload a significant element of the daily work, experts say.

Ivanti’s Kevin Smith

“We also expect to see machine learning help with the analysis of the large amounts of data the MSP business manages,” said Kevin Smith, senior vice president, Ivanti, which unifies IT and security operations to better manage and secure the digital workplace. “Then use this insight to offer new services, better serve existing customers and improve the performance of existing services.”

Front-End, Back-End Developers

Along with accelerating the on-boarding process for employees and customers, AI and automation will also help developers by clearing away some tactical clutter that distracts them every day. This will enable them to focus on strategic improvements to the MSP model and to the services that can be offered to clients, Smith said.

“The future success of the MSP will depend on its ability to offer more targeted and personalized services to clients, and developers can help bring these new services to life — but only if time is created to strategize, design and implement these new models,” Smith said. “With AI and automation, we can now delegate a number of daily throughputs to these technologies and create time that talented developers need to work through this new innovation cycle. This is powerful stuff — good for the business and good for the MSP customer.”

Indeed, the amount of work MSPs and their customers do is not static, with businesses constantly looking to take on more responsibility, but not always more staff to support it. This results in increased workloads for existing employees, who are expected to adapt to new areas of their role.

“As back-office processes add no value to the business but are fundamental to the smooth running of operations, AI and automation are the ipso facto way to improve process efficiencies and quality while freeing up budget,” said Neil Kinson, chief of staff, Redwood Software, provider of robotic back-office processes. “Then redirected resources can be utilized where [they] deliver real impact to the business, such as in customer service, marketing and product innovation.”

Meeting the Hype

PFS’ Noel Moran

AI, machine learning and automation are more than buzzwords. From customer service to fraud prevention and risk management to digital assistants, they are the way forward, say industry insiders.

“Tech-savvy millennials are the next big market for fin[ancial] technology and they expect digital solutions for everything,” says Noel Moran, CEO of PFS, a financial services technology company and e-money payment institution. “Machines can ‘think’ faster, and they are more accurate, more secure and – if built correctly – more intuitive.”

By its very nature, for AI to function, it needs a continuous stream of high-quality and relevant big data. And PFS is in position to provide some of the highest volumes of data – a billion dataset – in financial tech, which powers strategic decision making and next-generation development processes and analytical tools, said Moran.