TL;DR
High-profile predictions that AI agents would begin doing real-world work in 2025 did not materialize. Early agent products underperformed, experts flagged technical limits, and some observers say it's time to focus on what current AI actually does rather than on hype.
What happened
In late 2024 and early 2025, leaders in the AI industry publicly forecast that autonomous AI agents would begin doing substantive workplace tasks in 2025. Executives pointed to tasks like filling forms and booking travel as examples of near-term agent capabilities, and commentators described 2025 as the year of the AI agent. Optimism drew on prior gains in specialized coding agents such as Claude Code and Codex. By year’s end, however, the anticipated broad deployment of reliable agents had not occurred. Early releases like ChatGPT Agent struggled with routine web interactions in real-world tests, and reporting surfaced examples of prolonged failure modes. Critics argued the underlying large language model technology and current integration approaches remain inadequate for general-purpose digital labor. The author of the source piece recommends shifting focus away from speculative timelines and toward the concrete impacts of the tools that already exist.
Why it matters
- Mismatch between industry promises and delivered capability can distort business planning and investment decisions.
- Expectations of rapid, large-scale job displacement shape public debate even when evidence of such displacement is limited.
- Technical shortcomings in agents highlight the need for better evaluation on real-world, multi-step tasks before widescale deployment.
- Refocusing on present capabilities could produce more practical policy and workplace responses than reacting to speculative futures.
Key facts
- Sam Altman predicted in early 2025 that the first AI agents might 'join the workforce' that year.
- OpenAI executives and some press coverage characterized 2025 as a watershed year for AI agents.
- Prior agent successes cited in the industry included Claude Code and OpenAI’s Codex for multi-step programming tasks.
- Salesforce CEO Mark Benioff described an impending 'digital labor revolution' worth trillions early in 2025.
- Released products such as ChatGPT Agent failed to reliably complete everyday web tasks in reported tests.
- A reported example showed ChatGPT Agent spending many minutes attempting a simple selection on a real estate site.
- Skeptics including Gary Marcus argued that the same large language model technology powering chatbots won’t deliver the promised agents, calling current approaches 'clumsy tools on top of clumsy tools.'
- Andrej Karpathy warned of industry overpredictions, while characterizing the period as potentially the 'Decade of the Agent.'
- The source author urges moving away from hypothetical predictions and toward assessment of the actual impacts of existing AI systems.
- Sal Khan wrote an op-ed warning of large-scale worker displacement; the source notes specific examples cited in that piece but questions whether they demonstrate broad economic transformation.
What to watch next
- Improvements in agent reliability on multi-step, interactive web tasks — not confirmed in the source
- Clear, documented evidence of large-scale displacement of workers directly tied to deployed AI agents — not confirmed in the source
- Regulatory or enterprise policy responses focused on demonstrable capabilities of current AI systems rather than speculative futures — not confirmed in the source
Quick glossary
- AI agent: A software system designed to perform tasks on behalf of a user, often by combining multiple steps and decisions to achieve a goal.
- Large language model (LLM): A type of AI trained on large amounts of text to predict and generate natural language, often used as the core component of chatbots and agents.
- Chatbot: An interactive system that responds to user input in natural language, typically used for question answering, summarization, or conversational tasks.
- Automation: The use of technology to perform tasks with reduced human intervention, ranging from simple rule-based scripts to complex AI systems.
Reader FAQ
Did AI agents actually join the workforce in 2025?
No. According to the source, the broad arrival of reliable AI agents in workplaces did not occur in 2025.
Were there any successful agent applications in 2025?
Specialized coding agents like Claude Code and Codex showed strong performance on programming tasks, but equivalent general-purpose agents for other types of work did not appear.
Why didn’t agents deliver as promised?
The source cites technical limitations of the large language model–based approach, integration challenges, and industry overprediction as key factors.
Will AI displace large numbers of workers soon?
The source references claims of potential displacement but says broad, large-scale displacement tied to agents is not demonstrated in the examples discussed and thus is not confirmed in the source.
Why Didn’t AI “Join the Workforce” in 2025? January 5, 2026 Exactly one year ago, Sam Altman made a bold prediction: “We believe that, in 2025, we may see the…
Sources
- Why didn't AI "join the workforce" in 2025?
- How AI renders certain types of jobs obsolete and is changing …
- Why A.I. Didn't Transform Our Lives in 2025
- The great AI hype correction of 2025
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