The overarching term “artificial intelligence (AI)”  is a hub with many spokes. One of the most exciting of these from a business perspective is machine learning. As I explained in my first blog in the series,  at its most basic, machine learning involves ‘teaching’ a computer to learn and change when given a vast amount of data. The computer is not necessarily explicitly programmed for these changes, but instead learns to spot patterns and make connections. Therefore, the machine learns (get it?) to complete the task on its own.

SAP’s machine learning platform, SAP Clea, is embedded in our cloud platform and applications, enabling cutting edge algorithms to be utilized for predictive analytics and more.

What Does It Mean for the Customer?

But what are some of the things that SAP Clea can actually DO for our consumers? Let’s take a look at a short video on predictive analytics and machine learning with SAP HANA.


So you get the depth and speed of SAP HANA’s in memory analytics, with the power of native predictive algorithms. Pretty exciting stuff, but it doesn’t stop there.

SAP Application Intelligence

In addition, SAP Application Intelligence, announced last year at SAP TechEd in Barcelona, enables partner solutions for the end consumer with platform compatibility. This encompasses existing service partners as well as machine learning startups and other technology providers, opening a new range of opportunities for SAP and most importantly, our customers.

“SAP’s vision for machine learning and artificial intelligence goes way beyond one business application. It’s about creating business value by infusing our entire set of solutions with more intelligence, and providing a platform for our employees and an ecosystem to build machine learning solutions on,” said Juergen Mueller, chief innovation officer at SAP. “Data is the fuel for machine learning. SAP systems touch more than 70 percent of the world’s business transactions. With this asset, and our deep knowledge of business processes, we are poised to create an end-to-end intelligent enterprise.”¹

Machine Learning for B2B

How can machine learning assist business-to-business processes? Many business administration tasks are likely to be outsourced to AI technology, as machines begin to develop more and more “human thinking”-style intelligence. This behavior is already being tested in many industries globally. Invoice processing and expense reports, for example, can be performed by algorithms that respond to set parameters and only require human review for outliers.

The possibilities are quite broad, but that is not to say there aren’t significant challenges ahead for both the accountability of results and widespread adoption of this technology.² These are not insurmountable, by any stretch, but will require detailed planning, testing, monitoring, and controlling as the technology becomes more viable.

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