The Future of AIOps: Social, Causal, and Business Focused
Over the next five years, infrastructure and application management will come to depend upon machine learning and AI technology to ensure its ability to support digital business. AI will, itself, have to evolve, however, in order to serve this purpose. AI algorithms and systems will become increasingly distributed and social, advance more rapidly from correlational to causal analysis, and, finally, be driven by a deep awareness of business context.
The Economics of AIOps
While there is an intuitive appreciation for the value delivered by AIOps, the economic case for deploying such technology has proven difficult to articulate. This presentation will discuss the issues and sketch the elements of an AIOps value model.
Will Cappelli studied math and philosophy at university, has been involved in the IT industry for over 30 years, and for most of his professional life has focused on both AI and IT operations management technology and practices. As an analyst and former VP of Research at Gartner he is widely credited for having been the first to define the AIOps market and has recently joined Moogsoft as CTO, EMEA and VP of Product Strategy. In his spare time, he dabbles in ancient languages.