How to Integrate Semantic AI into Enterprise Processes? 5 experts share their Tips and Trends.

Position:DATABASE AND NETWORK INTELLIGENCE: CONFERENCE REVIEW
 
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The central challenge for companies dealing with large amounts of data is a digitization strategy. Here it comes to artificial intelligence and semantic technologies. Prior to the SEMANTICS 2019 conference, five international economists and researchers not only reveal what trends will hit companies over the next years but also share with us their tips creating more value from data.

Juan F. Sequeda, co-founder of Capsenta, and Senior Director of Capsenta Labs.

Tips I. Focus on the business problem that needs to be solved instead of the technology.

  1. Getting value out of your data is a social-technical problem. Not everything can be solved by technology and automation. It is crucial to understand the social/human aspect of the problems.

  2. Avoid boiling the ocean. Be agile and iterate.

  3. Recall that it's a marathon, not a sprint. Hence why you shouldn't focus on boiling the ocean.

    Trends We are working on the next generation of knowledge graphs that will capture more detailed information. Graphs are very easy for people to understand and express the complex relationships between concepts. We have even had C-level executives look at a Knowledge Graph and immediately see how it expresses a portion of their business and even offer suggestions for additional richness. This is in sharp contrast to the data itself, which is almost always very difficult to understand and overwhelming in scope. Critical business value is available in a subset of this data. A Knowledge Graph bridges the conceptual gap between a critical portion of the inscrutable data itself and the business user's view of their world. It's incredibly empowering when data that is clear and understood--what we call "beautiful data"--is available to the data workforce.

    Volker Tresp, Distinguished Research Scientist at Siemens.

    Tips The most important question is to come up with a business model that works for your company. I would claim that any company has successful AI projects. Machine Learning is a very strong and a very robust technology. But this does not mean that each company knows how to transfer this success into a business. Currently, no company, whose business is on the internet, can do without AI. If it turns out that your company has an AI business, then you might have to drastically change the culture in your company. You can only be successful if you manage to hire the best talents and if you change the culture in your company so that it values, appreciates and listens to...

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