The Rise of the AI Agency: Shifting from Services to Products
Published on 15.12.2025
Everyone's an AI Agency Now
TLDR: A recent survey reveals that while many companies use AI for tasks like marketing copy, very few are building with AI agents. This insight sparks a strategic pivot for one agency: shifting from selling AI automation services (a vitamin) to building commercial agentic AI products that generate recurring revenue (a painkiller).
Summary: The author highlights a critical gap in the current AI landscape, citing a survey of Dutch marketing professionals that found only 9% of their companies are working with AI agents, even though 64% use AI for basic marketing tasks. This distinction between using AI as a simple productivity tool (like generating copy) and integrating it as a core part of the business model is profound. The former offers an efficiency boost, while the latter represents a fundamental business transformation. This realization prompts the author to pivot their own agency away from providing AI automation services and toward a more impactful offering: helping clients build and launch their own commercial, agentic AI products.
The proposed shift is framed as moving from selling "vitamins" to selling "painkillers." An AI automation service is a vitamin—nice to have, but not essential. An agentic AI product that creates a new revenue stream is a painkiller—it solves a deep, structural problem. The author provides a compelling example of a regulatory compliance consultancy that is limited by billable hours. The "painkiller" solution is to package their expertise into an AI agent that proactively monitors regulatory changes and alerts clients. This transforms their business model from selling time to selling scalable, high-value outcomes.
To demonstrate the power of this new approach, the author details how they rebuilt their entire agency infrastructure in under 12 hours using AI tools. This included repositioning the agency, redesigning the website, and building a custom content and news-gathering system using Claude Code and custom MCP servers. This is a testament to the fact that the tools to execute such a pivot are readily accessible and affordable. The primary challenge is not technical implementation but strategic clarity: having a clear vision for what to build. The author is also making a strategic bet on LinkedIn for B2B marketing, building a "LinkedIn Operating System" with AI to create and curate content efficiently, aiming for authenticity and expertise in a sea of AI-generated noise.
Key takeaways:
- There is a significant difference between using AI for productivity and building AI agents into a core business model.
- The most valuable AI solutions solve a direct business pain (a "painkiller") rather than just offering an improvement (a "vitamin").
- Agencies and consultants can pivot from selling services to helping clients build revenue-generating AI products.
- The tools to rapidly build and deploy AI-powered systems are more accessible than ever.
- Strategic clarity and a willingness to commit to a direction are more critical than technical perfection.