State of AI Agents: Insights from 1,300+ Professionals

Why it matters: AI agents are transforming workflows, automating repetitive tasks, and driving efficiency. LangChain.com surveyed over 1,300 professionals—engineers, product managers, and executives—to understand how AI agents are being used and the challenges in scaling them.

Key findings from the research:

Adoption trends:

? 51% of respondents report using AI agents in production today, with mid-sized companies (100–2000 employees) leading adoption at 63%.

? 78% of professionals have active plans to implement agents soon, signaling widespread momentum across industries.

? Top use cases:

? Research and summarization (58%) and personal productivity tasks (53.5%) lead adoption.

? Customer service (45.8%) also benefits from agents, improving response times and streamlining support processes.

? Controls and guardrails:

? Tracing and human oversight are critical for ensuring reliability and safety in agent deployment.

? Larger enterprises rely on “read-only” permissions, while smaller companies focus on tracing to understand agent performance.

? Barriers to adoption:

? Performance quality is the biggest concern, cited by 45.8% of small companies and 32.5% of larger enterprises.

? Knowledge gaps and significant time investments for building and deploying agents remain key challenges.

Between the lines: LangChain’s research highlights growing interest in AI agents beyond tech. 90% of respondents from non-tech industries have plans to adopt or are already using agents, nearly matching the tech sector at 89%.

What’s next: Companies leading the charge—such as Cursor, Replit, and Perplexity—showcase how AI agents are solving real-world problems. Emerging trends identified in the research include:

? Automating complex, multistep workflows.

? Enhancing collaboration in multi-agent systems.

? Expanding open-source AI initiatives for faster innovation.

The bottom line: AI agents are gaining traction across industries, but challenges around performance, explainability, and controls remain. LangChain’s insights suggest that companies overcoming these hurdles will drive the next wave of AI-powered transformation.

Research methodology:

Conducted by LangChain.com, the survey gathered responses from over 1,300 professionals across industries, including technology, financial services, and healthcare, and spanned organizations of all sizes, from startups (<100 employees) to enterprises (10,000+ employees).