AI agents and AI-ready data hit peak hype, claims report

Gartner’s 2025 Hype Cycle report identifies AI agents and AI-ready data as the most overhyped technologies currently at the “Peak of Inflated Expectations,” warning that generative AI disillusionment is approaching. The research firm, which analyzes emerging technology trends, emphasizes that while these technologies show promise, they require precise strategic application rather than broad organizational deployment to deliver meaningful results.

What you should know: Gartner named four main technologies dominating the AI landscape: agents, AI-ready data, multimodal AI, and AI trust, risk and security management (TRiSM).

• AI agents refer to increasingly autonomous systems that can carry out tasks for humans, though their sophistication ranges from simple chatbots to complex automated assistants.
• AI-ready data is information correctly structured for AI systems to process, optimized for efficiency and accuracy.
• Unlike other technologies, AI-ready data has a longer plateau timeline of five to 10 years compared to the two to five-year timeline for others.

The big picture: Several AI areas have already slipped into the “Trough of Disillusionment,” where technologies fail to meet lofty expectations set during the hype stage.

• Synthetic data and generative AI now occupy this section of the Hype Cycle graph.
• Both are expected to plateau in about two to five years.
• This shift reflects growing scrutiny of AI’s practical applications versus ambitious promises.

Why strategic application matters: Businesses are pivoting from generative AI as a central focus toward foundational enablers that support sustainable AI delivery.

• “This has led to a gradual pivot from generative AI (GenAI) as a central focus, toward the foundational enablers that support sustainable AI delivery,” said Haritha Khandabattu, senior director analyst at Gartner.
• Organizations need concrete outcomes to match big promises as AI investments remain consistent.

What they’re saying: Industry experts emphasize the need for targeted rather than blanket AI implementation.

• “To reap the benefits of AI agents, organizations need to determine the most relevant business contexts and use cases, which is challenging given no AI agent is the same and every situation is different,” Khandabattu said.
• “Although AI agents will continue to become more powerful, they can’t be used in every case, so use will largely depend on the requirements of the situation at hand.”

The promising technologies: Multimodal AI and TRiSM show fewer caveats despite also dominating the Peak of Inflated Expectations.

• Both will be adopted by mainstream in the next five years and “will enable more robust, innovative and responsible AI applications, transforming how businesses and organizations operate.”
• Multimodal AI trains on and outputs multiple data types including audio, text, images, and video, creating richer context than text-only models.
• AI TRiSM addresses new security issues and ethics questions that conventional controls don’t address.

Key challenge for organizations: Data management evolution is critical for AI effectiveness, as simply having data isn’t sufficient.

• Companies must evolve their data management to meet AI requirements.
• Proper implementation will “cater to existing and upcoming business demands, ensure trust, avoid risk and compliance issues, preserve intellectual property and reduce bias and hallucinations.”