The future of ERP is AI

Despite cultural barriers and legacy tech, AI is poised to take over ERP functions, with ERP vendors adding new machine learning features and enterprises keen to investigate.

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"Most of those tend to be very conservative in any endeavor," he says.

In particular, they're hesitant about "black box" AI systems, where the reason behind a recommendation isn't clear.

"It's important to business leaders to be look investors in the eye and say, 'I understand the process by which we are making these decisions,'" he says.

For example, Vendavo can automatically sort customers into market segments, but customers need to be able to see why the system has created the clusters it did, and why a particular customer is in one cluster and not another.

"You might know something that's not in the data, your business knowledge, your general knowledge that isn't incorporated in the system," he says.

About 10 percent of customers are already using the machine learning technology to automatically identify market segments and calculate pricing power, Lee says, and those recommendations are then reviewed by humans.

"It's monitored over time to see if the recommendations are working, or if the new pricing is either not winning the business, but winning business but at a lower price," he says.

"But corporations are hesitant to flip the switch and have it go automatic," he adds. "People are used to making these decisions themselves, and the consequences of a machine-produced error, the consequences of some of those recommendations could be consequential."

"We are looking to applying machine learning to many domain-specific areas in ERP," says Ajoy Krishnamoorthy, vice president for platform strategy at Acumatica, a cloud ERP vendor.

For example, users will be able to ask, "Alexa, ask Acumatica how many laptops I have in stock," he says.

There are companies already piloting some of the new features, but they aren't in production yet.

In the case of the Alexa integration, the company is close to rolling it out, but security concerns remain. For example, you don't want random people asking for and getting company data.

"We need the voice authentication piece done," he says, "and we'll have that soon."

Another company with a cloud-based ERP product is VAI, which serves mostly midsize companies. It started working on AI about a year ago.

The company has the IBM Cognos line of business intelligence products built into its applications, and is also integrating with IBM's Watson artificial intelligence platform.

"A lot of our customers in the traditional pillars of industry are looking at what AI can do for them," says Kevin Beasley, CIO of VAI. "In the future, that is going to expand as we develop more and more AI capability."

"We're just getting started," says Aaron Harris, SVP and head of engineering and technology at Sage Intacct. "This is all pretty new stuff. We're just building out the underlying technology, but we're not quite ready for customers to start using this yet."

Sage Intacct plans to completely eliminate the close, so that corporate books are always up-to-date, and problems are spotted and addressed immediately, instead of at the end of the quarter. Plus, instead of creating reports, users will simply ask a natural-language question, and the platform will pull in data not just from the financial system, but from a multiple sources.

"We're getting a lot of excitement from customers," Harris says.

Nintex, a vendor that focuses on workflow automation, is working on adding machine learning and natural language processing to help its customers move away from rules to smarter, more flexible workflows.

The technology is in the testing stages, says Matt Fleckenstein, CMO at Nintex, and will be launched in early 2018.

"We've got a bunch of customers in the advanced preview stage right now," he says.

Some companies, for example, have more than 100,000 different workflows, he says. Intelligence can suggest actions to employees, or even automatically perform some of the actions.

"First, it's saying, 'You always tend to approve contracts below a certain amount from a certain person. Do you want to approve these?'" he says.

Then, in two or three years, once companies have gained confidence in the recommendations, the system can skip the recommendation step and just go ahead and take the action.

"As I build more trust over time, and actually see the value of it, and see that there's limited downside to it, I'll give it more power," he says. "It's not all that different than if you had a new employee who joined your team — as you get your confident in them you give them more responsibilities."

Learning by doing

To get started with AI and machine learning, doing is the best first step, says Helio Mosquim, IT innovation manager at Brasil's Vale, one of the world's largest mining companies.

Vale has been experimenting with machine learning using SAP's Leonardo platform by building prototype AI-powered services.

For example, employees trying to order replacement parts currently have to go through supplier catalogs, find part numbers, then enter those numbers into the system.

"It's a complex process, with a lot of mistakes," Mosquim said in a conference presentation last month.

The company considered using voice recognition, but that turned out not to work in practice. "The equipment is out there in the maintenance area, where it is so loud, so noisy," he says. So Vale decided to go with image recognition, and used SAP Leonardo's machine learning capabilities to learn to identify parts by sight.

"Now a guy in the field can take a picture with an iPad and create the request right out there in the field," he says.

The potential for AI in ERP is incredible, says Patrick Bakey, president of SAP Industries.

"In the next few years, repetitive, boring tasks that can be automated, will be automated, which will increase productivity and allow companies to reallocate jobs and create new roles," he says. "Companies will be able to dedicate more talent for strategic and creative projects."

Plus, employees will have a much easier time interfacing with enterprise technology.

"Today, you are using an AI-powered bot in your home like Alexa or Siri to look up pizza delivery restaurants nearby, with recommendations, reviews and coupons," he says. "We will bring the same level of convenience and intelligence to enterprise. applications."

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Copyright © 2017 IDG Communications, Inc.

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