Research Director, Cognitive/Artificial Intelligence Systems
Dave Schubmehl is Research Director for IDC's Cognitive/Artificial Intelligent Systems and Content Analytics research. His research covers information access and artificial intelligence technologies including content analytics, search systems, unstructured information representation, cognitive computing, deep learning, machine learning, unified access to structured and unstructured information, Big Data, visualization, and rich media search in SaaS, cloud and installed software environments. This research analyzes the trends and dynamics of the content analytics, discovery and cognitive systems software markets and the costs, benefits and workflow impacts of solutions that use these technologies.
David Schubmehl is speaking at the following session/s
Empowering the Digital Workforce: The Five Tenets of Success
Artificial intelligence (AI) impacts every aspect of enterprise work, from digital twins and preventative maintenance to AI-based conversational interfaces that provide customer care and support. These trends are changing the nature of work and how digital workers use AI/ML based search to make decisions. AI also improves how digital workers perform their jobs by augmenting human intelligence to drive better results faster with less risk and fewer errors.
At the same time, digital workers must handle an exponentially increasing amount of data. According to IDC's Worldwide Global DataSphere Forecast, 2019–2023, enterprise data will grow from 5 petabytes in 2018 to over 31 petabytes in 2023, a compound annual growth rate of almost 45%. The increase in unstructured data, combined with mounting pressure to improve digital worker productivity, makes it critical for workers to locate the right information at the right time - in context. Information-driven organizations need to improve their enterprise search capabilities in order to maximize revenue, manage costs, increase productivity and minimize risk. IDC has determined five key tenets of success to assisting digital workers. These are: integrating diverse content types and sources, applied AI, search relevancy, performance at scale, and ease of use.
This session will highlight the current investment patterns in AI technologies and solutions as it relates to the digital worker. It will highlight use cases and case studies in the adoption of this technology as distinct platforms, as embedded functionality in applications, analytics and information management software, and in the form of digital assistants for enterprise knowledge workers.