As AI continues to transform business operations globally, Gartner, Inc. is set to explore the most critical AI trends shaping the future of enterprise IT at the upcoming Gartner IT Symposium/Xpo, taking place September 8–10 on the Gold Coast. The event will showcase the 2025 edition of the Gartner Hype Cycle for Artificial Intelligence, highlighting AI agents and AI-ready data as the fastest-advancing technologies on the curve this year.
According to Gartner analysts, these innovations are now at the “Peak of Inflated Expectations”, signaling intense interest, ambitious projections, and rapid innovation. As businesses move beyond the GenAI hype, focus is shifting toward sustainable AI delivery, with foundational technologies enabling long-term operational scalability and real-time intelligence.
“There’s a sharper emphasis this year on building the right foundation for AI rather than chasing short-term hype,” said Haritha Khandabattu, Senior Director Analyst at Gartner. “AI-ready data and AI agents are the building blocks that will support robust, scalable AI ecosystems.”
Key Technologies to Watch from the 2025 Hype Cycle
1. AI Agents
These autonomous or semi-autonomous software entities leverage LLMs and other AI techniques to sense, decide, and act in digital or physical environments. While their potential is vast, Khandabattu cautions that “no AI agent is the same”, and successful deployment will depend on precise business context and use case alignment.
2. AI-Ready Data
Organizations are increasingly focused on preparing data for AI usage by ensuring its fitness for specific AI applications. AI-ready data minimizes bias, reduces hallucinations, and supports responsible, compliant AI development. This shift is prompting enterprises to rethink their data governance and management frameworks.
3. Multimodal AI
Expected to reach mainstream adoption within five years, multimodal AI uses diverse data types—text, audio, images, video—to develop deeper, more contextual understanding. Gartner predicts this technology will be integrated across nearly all software and AI applications in the coming years.
4. AI TRiSM (Trust, Risk, and Security Management)
AI TRiSM addresses governance, ethics, reliability, and compliance across AI deployments. With traditional controls proving insufficient, organizations must adopt layered AI risk management technologies to ensure ongoing policy enforcement and data protection.
“AI isn’t going to deliver business value on its own,” Khandabattu emphasized. “Enterprises must align AI projects with business goals, conduct infrastructure benchmarking, and foster collaboration between AI and business teams to ensure success.”
AI Strategy for the Future
Gartner’s AI insights are especially timely as organizations grapple with the double-edged sword of AI innovation and governance. The Symposium will provide deep dives into how companies can fortify four strategic pillars of AI—data readiness, trust, integration, and governance—to unlock tangible business outcomes.