AI Agents and AI-Ready Data Lead Gartner’s 2025 Hype Cycle for Artificial Intelligence

AI agents and AI-ready data are the two fastest advancing technologies on the 2025 Gartner Hype Cycle for AI, placing them at the Peak of Inflated Expectations. “With AI investment remaining strong this year, a sharper emphasis is being placed on using AI for operational scalability and real-time intelligence,” says Gartner’s Haritha Khandabattu. “This has led to a gradual pivot from generative AI (GenAI) as a central focus, toward the foundational enablers that support sustainable AI delivery, such as AI agents.” Among the AI innovations Gartner expects will reach mainstream adoption within the next five years, multimodal AI and AI trust, risk and security management (TRiSM) have been identified as dominating the Peak of Inflated Expectations.

Hype Cycle for Artificial Intelligence 2025

Source: Gartner (August 2025) “Despite the enormous potential business value of AI, it isn’t going to materialize spontaneously,” says Khandabattu. “Success will depend on tightly business-aligned pilots, proactive infrastructure benchmarking, and coordination between AI and business teams to create tangible business value.” AI agents are autonomous or semiautonomous software entities that use AI techniques to perceive, make decisions, take actions, and achieve goals in their digital or physical environments. Using AI practices and techniques such as large language models (LLMs), organisations are creating and deploying AI agents to achieve complex tasks. “To reap the benefits of AI agents, organisations 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,” says Khandabattu. “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.” AI-ready data ensures datasets are optimized for AI applications, enhancing accuracy and efficiency. Readiness is determined through the data’s ability to prove its fitness for use for specific AI use cases. It can only be determined contextually to the AI use case and the AI technique used, which forces new approaches to data management. According to Gartner, organizations that invest in AI at scale need to evolve their data management practices and capabilities to extend them to AI. This will cater to existing and upcoming business demands, ensure trust, avoid risk and compliance issues, preserve intellectual property, and reduce bias and hallucinations. Multimodal AI models are trained with multiple types of data simultaneously, such as images, video, audio, and text. By integrating and analyzing diverse data sources, they can better understand complex situations than models that use only one type of data. This helps users make sense of the world and opens up new avenues for AI applications. Multimodal AI will become increasingly integral to capability advancement in every application and software product across all industries over the next five years, says Gartner. AI TRiSM plays a crucial role in ensuring ethical and secure AI deployment. It comprises four layers of technical capabilities that support enterprise policies for all AI use cases and help assure AI governance, trustworthiness, fairness, safety, reliability, security, privacy, and data protection. “AI brings new trust, risk and security management challenges that conventional controls don’t address,” says Khandabattu. “Organisations must evaluate and implement layered AI TRiSM technology to continuously support and enforce policies across all AI entities in use.”

FAQ

What are AI Agents?

AI agents are autonomous or semi-autonomous software entities that leverage AI techniques to perceive their environment, make decisions, take actions, and achieve specific goals.

What is AI-Ready Data?

AI-ready data refers to datasets that are optimized for AI applications, ensuring higher accuracy and efficiency. The fitness of data for specific AI use cases is determined contextually.

What is Multimodal AI?

Multimodal AI models are trained on multiple types of data simultaneously, such as text, images, audio, and video, enabling a more comprehensive understanding of complex situations.

What is AI TRiSM?

AI TRiSM (Trust, Risk, and Security Management) is a framework designed to ensure the ethical and secure deployment of AI, covering aspects like governance, trustworthiness, fairness, safety, reliability, security, privacy, and data protection.

What is the significance of the Gartner Hype Cycle for AI 2025?

The Gartner Hype Cycle for AI 2025 highlights AI agents and AI-ready data as the fastest-advancing technologies, indicating their current high level of interest and expectation within the industry.

Crypto Market AI's Take

The Gartner Hype Cycle's emphasis on AI agents and AI-ready data aligns perfectly with our platform's core offerings. At Crypto Market AI, we understand that realizing the full potential of AI in finance requires robust underlying data and intelligent, autonomous agents. Our advanced AI agents are designed to navigate the complexities of the cryptocurrency market, providing users with sophisticated trading strategies and market analysis. Furthermore, our commitment to AI-ready data ensures that our systems are built on a foundation of accuracy and efficiency, critical for making informed decisions in the fast-paced crypto world. We believe that by focusing on these foundational elements, we can deliver truly transformative solutions for our users.

AI Agents and A-ready data top Gartner Hype-Cycle