After a journey along the 2023 Gartner Hype Cycle™ for Artificial Intelligence, we’ve reached the final two stages: the Slope of Enlightenment and the Plateau of Productivity. Here, technologies have moved past the initial hype, and organizations are effectively putting them to use.
In this episode, Senior Director Analyst Jim Scheibmeir discusses cloud AI services, many of which are low-code, and their potential to transform industries from manufacturing to finance. Then, Afraz Jaffri, a Director Analyst who focuses on data and analytics and AI and the editor of this year’s AI Hype Cycle, speaks to Gartner’s expectations for the future of AI technologies.
Watch Now: Gartner Hype Cycles, Explained
Read: What’s New in Artificial Intelligence From the 2023 Gartner Hype Cycle
Learn More: Gartner Hype Cycle Research Methodology
Opening Thoughts
How to Tell When Disillusionment Transforms Into Enlightenment
Introduction to Cloud AI Services
How Enterprises Can Use Cloud AI Services in the Near Future
Characteristics of the Slope of Enlightenment
Why the Plateau of Productivity Is Empty This Year
Closing Thoughts and Series Wrap-Up
James Anthony Scheibmeir | Sr Director Analyst
Jim Scheibmeir, Ph.D. (systems engineering), is a Research Analyst covering the enablement of digital business through DevOps practices. Dr. Scheibmeir researches on agile and DevOps practices and tools, with a focus on software test automation, multiexperience development and advises software engineering leaders in midsize and large enterprises. He has 20 years of industry experience including development, test and operations roles in government, manufacturing and retail enterprises.
Afraz Jaffri | Director Analyst
Afraz Jaffri is a Research Director at Gartner, where Mr. Jaffri focuses on Analytics, Data Science and AI. He advises Data and Analytics leaders on making the most from their investments in modern data science, machine learning and analytics platforms. He has particular focus on how to organize analytics and data science teams, implementing graph-based data management and analytics solutions and developing best practices for operationalizing machine learning models.
Hosted by: Karen Lockhart
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