Rachel Dunning is a Research Analyst in the Data, AI & Analytics channel at 451 Research, a part of S&P Global Market Intelligence. She has worked alongside the Datacenter Services & Infrastructure channel and the Internet of Things (IoT) channel, and assists with Voice of the Enterprise surveys and deliverables. Her primary interests lie in the AI and machine learning space as well as the agricultural technology sector. Prior to joining 451 Research, she graduated from Fitchburg State University Magna Cum Laude with a BS in Cognitive Psychology and Economics. While attending school, she gained exposure to research methodology and data analytics through her involvement in several academic research projects. She is conversationally fluent in German.
Our Voice of the Enterprise: AI & Machine Learning, Use Cases 2023 survey collects insight on AI initiatives and their progress from 1,011 midlevel and senior IT and line-of-business professionals across the US, UK, France and Germany. This report highlights some of the key findings from that survey.
AI and machine learning require infrastructure to work at scale. That infrastructure will include a lot of investment in the edge in the near future. In this report, we investigate the current state of AI workloads, the venues they are deployed in and growing interest in AI at the edge.
This report highlights some of the key topics we expect to be prominent in 2023 in the Data, AI and analytics sectors. It's been a truism for some time that organizations want to derive more insight from their data and do so more quickly and easily than ever before. These are some of the trends that will help them to achieve this goal.
Results from our Voice of the Enterprise: AI & Machine Learning, Infrastructure 2022 survey highlight the insight and developments that are driving change in AI infrastructure. Diving into this insight reveals many trends and developments in the market, including the ever-increasing volumes of data and models requiring management, a shift toward the cloud and the edge, and several hurdles that need to be overcome to get AI projects from concept into production.
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