They promise efficiency, speed and entirely new ways of working. The problem? Most enterprises lack a clear view of what’s working, what’s failing, and what’s still out of reach.
This report, created with WIRED, gives you that clarity: where AI agents are producing ROI today, why some initiatives collapse, and what to expect next.
Discover why 93% of IT leaders plan to deploy AI agents by 2026 and how early deployments are delivering measurable ROI with task-specific human-supervised systems.
See how pioneers like Bayer and Siemens are achieving real-world ROI, with some early deployments showing up to 30% faster resolution times.
Learn why 40% of agentic AI projects are expected to be canceled by 2027 due to reliability, governance and security issues, and how to mitigate these risks.
Unpack a five-step roadmap from Thoughtworks experts for scaling AI agents with confidence, from data prep and security to staff training and organizational buy-in.
Explore what’s next for agentic AI, including rapid advances in capability, emerging standards and how "superagents" could soon reshape business models.
Rachel discusses the architectural and cultural groundwork every enterprise needs to build before scaling AI agents, from secure data foundations to human-in-the-loop design.
Shayan examines the trust, reliability, and ethics challenges that define agentic AI, and what it means when intelligent systems stop assisting and start collaborating.
Gene unpacks the strategic implications of agentic AI, revealing how businesses can turn disruption into competitive advantage and prepare for a fundamentally new digital operating model.
Danilo explores how enterprises are moving from experimental LLM workflows to scalable, autonomous agents, and what it takes to make AI reliable, governed, and truly useful in production.
AI agents are software systems that can plan, decide and act on tasks, not just answer questions. In enterprises, they’re being used for customer service, workflow automation, research and even code development.
Because adoption is accelerating. 93% of IT leaders plan to use AI agents by 2026. Early movers already see ROI in speed, efficiency and decision-making, while late adopters risk falling behind.
Without guardrails, AI agents can fail in costly ways. Common risks include reliability gaps, hallucinated outputs, governance failures and cybersecurity vulnerabilities. Gartner predicts that up to 40% of agentic AI projects may be canceled by 2027 due to unclear value or poor controls.
Start with focused, measurable use cases—such as improving resolution times in customer service, accelerating research or streamlining code delivery. Pair modern platforms with strong governance and human oversight to scale responsibly.
Agents are rapidly evolving toward greater autonomy and collaboration. In the near future, they could optimize entire value chains, orchestrate multi-agent systems, and reshape business models. Organizations that prepare now will be best positioned to capture that advantage.
