2024 Gartner® Hype Cycle™ for Artificial Intelligence

Anonos recognized as a Sample Vendor in Gartner latest Hype Cycle report for synthetic data.

By Analyst(s): Afraz Jaffri, Haritha Khandabattu

Gartner Hype Cycles provide a graphic representation of the maturity and adoption of technologies and applications, and how they are potentially relevant to solving real business problems and exploiting new opportunities. This year's Hype Cycle for AI highlights synthetic data's potential to tackle challenges in AI development and predicts a massive increase in its adoption.

According to Gartner, "A major problem with AI development today is the burden involved in obtaining real-world data and labeling it. This time-consuming and expensive task can be remedied with synthetic data, where data can be generated faster and cheaper."

Synthetic data adoption is rising across various industries, driven by the need for privacy-preserving AI training data, expanding vendor offerings, and advancements in generative AI technologies.

This technology is now applied beyond traditional uses to areas like data monetization, external analytics, and test data development, with ongoing research expanding its applications to new data types and improving quality. The growing use of generative AI models further drives demand for synthetic data for pretraining and customization.

The 2024 Gartner Hype Cycle for Artificial Intelligence recognizes vendors and their technologies, including Anonos for synthetic data.

The Hype Cycle for Artificial Intelligence includes:

An overview of the most impactful technologies influencing the AI field;
Strategic recommendations for data and analytics leaders;
Recognized Sample Vendors and use cases.

Gartner, Hype Cycle for Artificial Intelligence, 2024, Afraz Jaffri, Haritha Khandabattu, 17 June 2024

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This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Anonos.