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AI PREDICTIONS 2019

20 More AI Predictions For 2019

“The adoption of artificially intelligent offerings will continue to scale into different verticals from manufacturing to education, retail and more in 2019. In the healthcare sector, for example, AI-enhanced applications have the capability to reduce emergency waiting room times and even free up doctors’ time through the use of AI in detecting and diagnosing tumors. As new advances and applications make their way into various verticals, expect to see accelerated adoption as technology costs come down and organizational and business outcomes improve. At Lenovo, we’re already using AI in our supply chain and parts planning process so that we can better develop best in class experience for customers also keen to transform their business with artificial intelligence”—Gianfranco Lanci, Corporate President and Chief Operating Officer, Lenovo

“Patients will find themselves talking via a variety of omni-channel UIs in addition to the pre-existing chat bots that are currently available on mobile apps and other health care IT platforms. Consumer frameworks for conversational experiences like Alexa and Google Home may add HIPAA privacy support that opens the gates for bots to keep the dialog going during the big gaps in time between patient visits. In care settings, nurse call buttons beside hospital beds, forms to collect health histories, and klunky scheduling apps will evolve into customer-focused robot medical assistants”—Dan Housman, chief technology officer for ConvergeHEALTH, Deloitte

“2019 will see the pendulum shift to a focus on performing analytics at the edge. Organizations will save time and money by processing and analyzing data at the edge versus moving it back to a core, storing it and applying traditional analytics. Use cases include anomaly detection (fraud), pattern recognition (predicting failures/maintenance) and persistent streams. Autonomous vehicles, Oil and gas platforms, medical devices are all early examples of this trend that we will see expand in 2019. Cost drivers for this trend are bandwidth (semi-connected environments as well as expensive cellular) considerations and storage (reduce the amount of data sent to the cloud)”—Jack Norris, Senior Vice President, Data and Applications, MapR