Machine learning can turn an avalanche of unstructured information – images, documents, text, videos, speech – into something with real business value like less down time in the field or on the factory floor, faster sales cycles, happier customers, and yes, greater revenue. To be sure, intelligent machines working in isolated parts of the organization aren't new. What's exciting now is how companies are infusing machine intelligence across the business for even greater benefits. I sat down recently with Dr. Markus Noga, senior vice president of Machine Learning at SAP, for his take on machine learning and what people can expect to see at the upcoming SAPPHIRE NOW conference, June 5-7 in Orlando, Florida. "Machine learning unlocks the ability to rethink business processes across the company from sourcing and human resources to finance and customer service," said Noga. "SAP is committed to making all of our applications intelligent. We began with SAP Cash Application in finance, and now we're expanding machine learning across the entire accounts receivable value chain. Conversational AI can help companies satisfy the spikiest customer demands. "In the United States alone, companies lose $1.6 trillion due to poor customer service," said Noga. "Machine learning that understands what customers are asking for, coupled with the ability to integrate those requests deep into backend systems, allows companies to answer questions and fulfill requests much more efficiently and cost-effectively." Many customer service-intensive organizations in industries like utilities and insurance are already seeing business outcomes from AI through Recast.AI, a recent SAP acquisition, now called SAP Conversational AI. "After putting their customer service on a bot, these companies have experienced very rapid implementation of projects in weeks, with just as rapid payback," said Noga. "Machines can help companies achieve significant cost savings per incident while increasing customer service consistency and reliability." As for what to do next, Noga advised customers to experiment with free trials. "There's a community of over 30,000 developers using SAP Leonardo Conversational AI to help get started with bots.

Investors dropped 681 million into A.I.-centric startups in Silicon Valley last year. This year, the number will likely reach 1.2 billion. Five years ago, total A.I. investment spiked at roughly 150 million. This is how Silicon Valley works: When something new is hyped and seems to have investor trust, everybody jumps on the train without asking, "Where does this train go?" The truth is that artificial intelligence does not exist yet, and most companies claiming to have A.I. technology are arrogantly re-selling an old concept of machine learning -- a technology that was first introduced in 1959 but which truly started to take off in the 1990s.

Investors dropped 681 million into A.I.-centric startups in Silicon Valley last year. This year, the number will likely reach 1.2 billion. Five years ago, total A.I. investment spiked at roughly 150 million. This is how Silicon Valley works: When something new is hyped and seems to have investor trust, everybody jumps on the train without asking, "Where does this train go?" The truth is that artificial intelligence does not exist yet, and most companies claiming to have A.I. technology are arrogantly re-selling an old concept of machine learning -- a technology that was first introduced in 1959 but which truly started to take off in the 1990s.

Investors dropped 681 million into A.I.-centric startups in the Valley last year. This year the number would reach 1.2 billion. Five years ago total A.I. investment piked at roughly 150 million. This is how Silicon Valley works: when there is a new hype that seems to have investor trust everybody jumps on the train without asking any questions. No one asked: "Where does this train go?"