The twin disciplines of machine learning (ML) and artificial intelligence (AI) have progressed through their somewhat clunky adolescence to now become real contributors within today’s IT systems. After a period of initial conceptualization in the 1960s, artificial intelligence spent most of the 1980s and 1990s hanging out in Hollywood movies and TV shows, providing a means for cars to talk and for clunky, yet fierce robots to threaten humankind. Today, they’re so much a part of how we do business, SAP introduced SAP Leonardo to help leverage these intelligent technologies as well as drive innovation within an organization.

SAP Leonardo makes it possible to unlock the intelligent enterprise and use ML and AI as tools within a company’s businesses processes across the board. 

At Home with Artificial Intelligence

Although both terms tend to appear together, artificial intelligence is the high-level concept of building machines that can replicate humanlike activities. Machine learning is the process of giving machines data so that they can learn for themselves. The post-millennial years have seen both artificial intelligence (and the machine learning that drives it) progress to a more-developed efficiency that is now making our software more predictive, holsitic, and useful.

We even carry artificial intelligence in our pockets now, in the form of the digital assistants in our smartphones. Or we use it for such mundane tasks as ordering laundry detergent and playing our favorite songs using the smart speakers that sit in our kitchens.

AI at Work in SAP ERP

At first glance, many people might fail to make the connection between artificial intelligence and its suitability for enterprise resource planning (ERP) systems. But, in fact, it’s a straightforward relationship.

Software systems from ERP specialists like SAP are designed to make businesses run. They are dedicated to ingesting, tracking, filtering, analyzing, and reporting on the individual granular components of business operations so business managers can make informed decisions about the best strategies and tactics.

Predictive Insights to Drive Decisions

With artificial intelligence in the ERP engine, we can make the analysis within business systems more predictively intelligent. And we can also, in some areas, automate some of the decision-making away from the human manager—if we build our business logic correctly, based on best practices and observed real-time data. SAP is addressing this by powering its machine learning processes with real data from real use cases, so you can take advantage of the benefits of machine learning without having to hire legions of data scientists. This is the backdrop to what customers are doing with artificial intelligence in SAP Leonardo.

What is SAP Leonardo and How Can it Help?

As a hypothetical (yet highly realistic example), SAP Leonardo machine learning can be used to analyze commercial deals (of any kind) as they play out. It can help predict the deal’s likelihood of success, value (profit or loss), and expected close date.

In a simpler scenario, SAP Leonardo machine learning could be tasked with tracking pending orders to examine the status of all factors that could affect customer-supplier interactions. For example, it could forecast that a part shortage from a supplier will prevent you from delivering the finished products your customers have already ordered and paid for.

In an even more basic scenario (but no less real example), SAP Leonardo machine learning can matching invoices to orders to automate the less-fulfilling, yet highly critical work of finding and correcting accounting errors.

For a couple of actual examples, you can see how Costco uses machine learning to keep its bakeries and food courts stocked, while reducing waste. And you can learn how train operator SNCF is using AP Leonardo Recast Conversational AI to deliver personalized service to its passengers at scale.

How SAP Machine Learning Works

At this point you might be asking how SAP Leonardo machine learning works? The answer comes in three parts:

  • Programmatic logic: Machine logic is programmatically applied to the task at hand using templated, best-practice data relating to specific industry use cases.
  • Human observation: The machine brain continues to learn as a result of observing the actions and decisions taken by human workers—within the defined boundaries of privacy and security, of course.
  • Exceptions and anomalies: Even the smartest machines get caught. SAP has engineered its machine learning to know when to perform a handoff to humans to deal with exceptions and anomalies. This provides a new tier of advancement, as the machine is able to learn from its mistakes.

All of this plugs into SAP S/4HANA Cloud, which includes further artificial intelligence and machine learning in the form of digital assistants with a voice command interface.

In our next article in this series, we’ll share additional real-world examples of how companies are building artificial intelligence and machine learning into a competitive advantage.

Watch our webcast series on demand to learn how you can use SAP Leonardo to take on innovative artificial intelligence projects at your company.