How AI Agents and AI-Ready Data Are Shaping the Future of Business
Analysts to Spotlight AI’s Next Big Shifts at Gartner IT Symposium/Xpo, September 8–10, Gold Coast
According to Gartner, Inc., two technologies stand out as the fastest movers on the 2025 Gartner Hype Cycle for Artificial Intelligence: AI agents and AI-ready data. Both are drawing significant attention this year, with ambitious forecasts and bold promises placing them firmly at the Peak of Inflated Expectations.
The Gartner Hype Cycle provides a visual framework for understanding the maturity and adoption path of emerging technologies, highlighting their potential to solve real business challenges and unlock new opportunities. By mapping how innovations evolve over time, it equips organizations with insights to guide investment strategies and align deployments with long-term business objectives.
Figure 1: Hype Cycle for Artificial Intelligence 2025
“AI spending remains strong in 2025, but the focus is shifting,” said Haritha Khandabattu, Senior Director Analyst at Gartner. “We’re moving beyond the hype around generative AI and toward the foundational enablers that will sustain its delivery — namely, AI-ready data and AI agents that drive operational scale and real-time intelligence.”
Among the technologies Gartner expects to hit mainstream adoption within five years, multimodal AI and AI trust, risk, and security management (TRiSM) are rising fast. Positioned at the top of the hype cycle, these innovations are seen as essential for building more resilient, innovative, and responsible AI systems — setting the stage for the next wave of enterprise transformation.
Key Trends at the Peak of AI Adoption
AI Agents
AI agents are autonomous or semi-autonomous systems capable of perceiving environments, making decisions, and executing actions to achieve defined goals. Leveraging techniques such as large language models (LLMs), organizations are deploying agents to handle increasingly complex business tasks.
“Adoption, however, must be contextual,” noted Khandabattu. “AI agents are powerful but not universal. Each implementation must be tailored to the business need, with careful consideration of scope and relevance.”
AI-Ready Data
AI-ready data is becoming a critical foundation for trustworthy and efficient AI applications. It refers to data sets optimized for AI use, validated for their quality, contextual relevance, and readiness for specific AI models.
Gartner stresses that enterprises scaling AI must evolve data management practices, ensuring data trustworthiness, reducing bias and hallucinations, and safeguarding compliance and intellectual property.
Multimodal AI
Multimodal AI models process and learn from multiple data types simultaneously — including text, images, audio, and video — creating deeper contextual understanding than single-modality models. Gartner predicts that over the next five years, multimodal AI will be embedded across software, platforms, and industries, driving richer insights and more intelligent applications.
“While AI’s potential is immense, business value won’t emerge automatically,” Khandabattu emphasized. “The winners will be those that run business-aligned pilots, benchmark infrastructure proactively, and foster tight collaboration between AI and business teams.”
Source: Gartner
