Rise of AI Agents

The Shift

The AI industry is undergoing its most significant transformation since ChatGPT launched: the move from chatbots to agents. While chatbots answer questions, agents take action. This is the difference between AI that informs and AI that works.

• 2022-2024: The chatbot era - AI you talk to
• 2024-2026: The agent era - AI that works for you

Gartner predicts that by 2028, 33% of enterprise software will include agentic AI, up from less than 1% in 2024.

What Changed

Tool Use Matured

Models learned to reliably call external functions and APIs. This "tool use" capability transforms language models from text generators into system operators.

Context Windows Expanded

With 100K+ token contexts, models can understand entire workflows, codebases, and conversation histories—essential for complex task execution.

Reliability Improved

Hallucination rates dropped below 1% for leading models. When AI takes actions with real consequences, accuracy becomes non-negotiable.

Enterprise Demand Crystallized

The $37.5B enterprise AI market wants AI that does work, not just AI that answers questions.

The Agent Landscape

Coding Agents

• Claude Code: Anthropic's CLI for development tasks
• Cursor: AI-native code editor
• GitHub Copilot Workspace: End-to-end development
• Devin: Autonomous software engineer

Business Agents

• Intercom Fin: Customer support resolution
• Salesforce AgentForce: Sales and service automation
• Harvey: Legal document workflows
• Glean: Enterprise knowledge work

Personal Agents

• Operator (OpenAI): Browser-based task completion
• Apple Intelligence: System-level assistance
• Google Project Astra: Multimodal personal agent

How Organizations Are Adopting

The Typical Journey

Stage 1 - Chatbots: Deploy AI for Q&A and information retrieval

Stage 2 - Copilots: AI assists humans with suggestions and drafts

Stage 3 - Supervised Agents: AI takes actions with human approval

Stage 4 - Autonomous Agents: AI operates independently on delegated tasks

Most enterprises are currently transitioning from Stage 2 to Stage 3.

Where Agents Excel

Who's Driving This

Mustafa Suleyman (Microsoft AI):

"The next era is agents - AI that doesn't just respond but takes action on your behalf."

Sam Altman (OpenAI):

"We're moving from AI you talk to, to AI that works for you."

Eoghan McCabe (Intercom):

"Fin resolves 50% of customer issues without human intervention. That's not assistance—that's work."

Implications

For Workers

The nature of knowledge work changes fundamentally:

• Less execution: AI handles routine tasks
• More oversight: Humans manage and correct AI work
• Higher leverage: One person orchestrates multiple agents

For Organizations

New capabilities and challenges:

• Scale without proportional headcount: Agents handle volume
• New skill requirements: Prompting, orchestration, AI oversight
• Trust and governance: When can agents act autonomously?

For Society

The agentic era accelerates existing trends:

• Labor market disruption: Entry-level knowledge work faces pressure
• Productivity potential: Economic output per person increases
• Inequality risks: Benefits may concentrate among those who deploy agents

Timeline

What's Next

The agent era is just beginning. Key developments to watch:

• Multi-agent systems: Teams of specialized agents working together
• Agent-to-agent communication: AI systems coordinating without human mediation
• Persistent agents: Long-running agents that maintain state and context
• Physical agents: Robotics bringing agents into the physical world

Related Reading

• AI Agents - Understanding the core concept
• Knowledge Work Disruption - The business impact
• Tool Use - The enabling technology