Gartner recommends projects involving Natural Language Processing (NLP), machine learning, chatbots and computer vision to be prioritized above other AI initiatives. Gartner clients are wisely moving to minimum viable product and accelerating AI development to get results quickly in the pandemic. Before the pandemic, pilot projects’ success or failure was, for the most part, dependent on if a project had an executive sponsor and how much influence they had.
AI-based minimum viable products and accelerated AI development cycles are replacing pilot projects due to the pandemic across Gartner’s client base. According to the Hype Cycle, it may be economical for applications where utilization is low, but the urgency of completion is high. GPU computing is also available as a cloud service. Gartner advises its clients that GPU-accelerated Computing can deliver extreme performance for highly parallel compute-intensive workloads in HPC, DNN training and inferencing. 
Gartner predicts GPU Accelerators will see a 100% improvement in adoption in two to five years, increasing from 5% to 20% adoption last year to 20% to 50% this year.
GPU Accelerators are the nearest-term technology to mainstream adoption and are predicted to deliver a high level of benefit according to Gartner’s’ Priority Matrix for AI, 2020. Bot vendors to watch include Amazon Web Services (AWS), Cognigy, Google, IBM, Microsoft, NTT DOCOMO, Oracle, Rasa and Rulai. Gartner points to chatbot’s successful adoption as the face of AI today and the technology’s contributions to streamlining automated, touchless customer interactions aimed at keeping customers and employees safe. Gartner revised the bots’ penetration rate from a range of 5% to 20% last year to 20% to 50% this year. Chatbots are projected to see over a 100% increase in their adoption rates in the next two to five years and are the leading AI use cases in enterprises today. The Gartner Hype Cycle for Artificial Intelligence, 2020, is shown below:ĭetails Of What’s New In Gartner’s Hype Cycle for Artificial Intelligence, 2020 Reusability, scalability, safety and responsible use of AI and AI governance are the catalysts contributing to the second theme. The second theme is the industrialization of AI platforms. The greater the democratization of AI, the greater the importance of developers and DevOps to create enterprise-grade applications. The first theme is the democratization or broader adoption of AI across organizations. Two dominant themes emerge from the combination of 30 diverse AI technologies in this year’s Hype Cycle. These and many other new insights are from the Gartner Hype Cycle for Artificial Intelligence, 2020, published on July 27 th of this year and provided in the recent article, 2 Megatrends Dominate the Gartner Hype Cycle for Artificial Intelligence, 2020. Five new technology categories are included in this year’s Hype Cycle for AI, including small data, generative AI, composite AI, responsible AI and things as customers. AI projects continue to accelerate this year in healthcare, bioscience, manufacturing, financial services and supply chain sectors despite greater economic & social uncertainty. 
30% of CEOs own AI initiatives in their organizations and regularly redefine resources, reporting structures and systems to ensure success. 
47% of artificial intelligence (AI) investments were unchanged since the start of the pandemic and 30% of organizations plan to increase their AI investments, according to a recent Gartner poll.
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