2018 Outlook For Machine Learning – An Innovation In Its Teen Years

Katrin Schneider

A year ago, Gartner, the world’s leading research and advisory company, named artificial intelligence (AI), machine learning (ML), and conversational systems three of the top strategic tech trends for 2017. In May last year, SAP launched the SAP Leonardo Machine Learning portfolio at SAPPHIRE NOW in Orlando, Florida, and thus demonstrated that it’s on the pulse of innovation. Today, it is about time to sum up the latest developments and give an outlook on the potential of intelligent technologies.

Trend #1: ML platforms

Deep learning, neural networks, and natural language processing elevated ML to new levels. Thanks to mature ML algorithms, higher processing power, and the availability of huge data sets, machines are becoming intelligent and able to process unstructured data, like pictures, text, or spoken language – often even on a superhuman level. Additionally, deep learning is now stable enough to potentially establish ML as a standard commodity across businesses worldwide. Those who are interested in tailor-made and customized solutions require a ML platform to combine ready-to-use services to create their own intelligent applications.

Trend #2: Intelligent applications

Intelligent apps automate routine tasks that take time from value-adding activities and can provide precious insights into structured and unstructured enterprise data. This helps companies make better business decisions and increase productivity in several lines of business, like finance, HR, sales and service, and more. For enterprises lacking in-house ML expertise, intelligent applications are available that allow, for example, building self-driven customer service to enhance customer experience, automating financial services by matching incoming bank statements to open receivables, or helping marketing executives maximize sponsorship ROI.

Trend #3: Conversational systems

Thanks to great strides in natural language processing, conversational AI has fundamentally changed how we interact with computers and electronic devices. Today, millions of people use intelligent interfaces to satisfy their daily consumer demands. They serve users with music selections, vacation planning, pizza ordering, and much more. We are on the cusp of a world where conversational assistants will be retrievable at any time and place – including at work. These capabilities will connect data, processes, applications, devices, and people and will build the foundation for a new digital experience in the workplace.

What will the future bring us?

Technologies augmenting the human potential at work are no longer dreams of the future. But how will they evolve, and what will the trends in 2018 look like? I believe that some of these technologies might be about to reach maturity, but there is still a great deal of innovation potential, especially in the enterprise context. According to Gartner, 59% of organizations are still gathering information to start building an AI strategy for their organization – a huge competitive advantage in 2018 for those who have already started to adopt AI in their systems. I am convinced that more and more companies will leave the concept stages this year and really begin to apply ML. The hype around deep learning will flatten out as it becomes a commodity, but the efficiency and robustness of the underlying models will be the differentiator and therefore a relevant issue for enterprises to address in the upcoming year.

For Gartner, a rock-solid ML foundation, intelligent apps, and conversational platforms will make the difference between profit and loss for companies in the race to digital transformation in 2018. Platforms and solutions will evolve significantly, handling increasingly complex tasks. Further, Gartner predicts that over the next few years, every application will contain AI, creating an intelligent layer between employees and enterprise systems.

Overall, technology will become even more human-centric and will increase transparency between people, organizations, and things. In business and private life, augmented reality, virtual reality, or brain-computer interfaces will create immersive experiences beyond virtual assistants and chatbots.

Moreover, business will experience a shift from standalone intelligent objects to swarm AI – an approach that goes back to the behavior of animals that amplify their group intelligence to solve problems or make decisions. Swarm AI is the self-organization of systems for collective decentralized behavior that enables human swarms by bringing information of diverse groups into a single emergent intelligence. In an enterprise context, swarm AI helps to improve logistics or transportation, HR, or customer feedback gathering – for example, by eradicating the influence of preceding valuations on the voter. All of these AI developments will have an impact on the way enterprises are doing business, and not only on an operational level. I expect the emergence of new, AI-driven business models and a transition of innovation and research expertise, everywhere from universities to industries.

Explore machine learning applications and AI software with SAP Leonardo technology.

Katrin Schneider

About Katrin Schneider

Katrin Schneider is communications lead for SAP Leonardo Machine Learning at SAP. She is a graduate of the University of Mannheim with bachelor's and master's degrees in Business Administration and Culture.