The AI industry is witnessing a paradigm shift. While large-scale players like OpenAI, Google DeepMind, and Anthropic are building foundational models—Large Language Models (LLMs) and Small Language Models (SLMs)—the real opportunity for entrepreneurs lies in creating Value-Added Services (VAS) on top of these models.
The path to wealth in AI isn’t in competing with these giants but in leveraging their infrastructure to solve specific problems at scale.
The VAS Opportunity in AI
Foundational AI models provide raw intelligence, but they lack contextual specialization, domain expertise, and user-friendly workflows. Entrepreneurs can unlock massive value by building AI-driven solutions that tailor LLMs and SLMs to specific industries, workflows, and consumer needs.
This approach has parallels with the early days of the internet. Amazon didn’t invent the internet, but it built an e-commerce empire on top of it. Similarly, Uber leveraged GPS and smartphones, but its real value came from streamlining ride-sharing.
In AI, the winning formula is applying foundational models to niche problems with high-value solutions.
Examples of Value-Added Services in AI
1. Jasper AI – AI-Powered Content Creation
Jasper AI built an AI-powered writing assistant by fine-tuning GPT models for marketing and copywriting. Instead of competing with OpenAI, they packaged AI-generated content as a service, focusing on ad copy, blog writing, and sales emails. Result? A $1.5 billion valuation within two years.
2. Replit – AI Coding Assistant
Replit took AI-assisted coding to another level by integrating AI into their online coding environment. By offering instant code completions, debugging, and collaborative features, they created a VAS that enhances software development workflows, making coding faster and more accessible.
3. Harvey AI – AI for Legal Services
Harvey AI built an AI legal assistant using GPT models, focusing on contract analysis, due diligence, and legal research. Instead of developing a new AI model, they optimized existing LLMs to understand legal terminology and nuances, securing partnerships with top law firms.
4. Runway – AI for Video Editing
Runway applied AI to video content creation by leveraging LLMs for scriptwriting and computer vision for AI-powered video editing and special effects. Their platform is now used by filmmakers, marketers, and content creators worldwide, showing how AI can disrupt creative industries.
How to Build a VAS Business in AI
1. Find a Niche with a Pain Point
- Identify industries where AI can drastically improve productivity or reduce costs.
- Example: Customer support automation, legal document analysis, or AI-driven medical diagnostics.
2. Leverage Existing LLMs & SLMs
- Don’t reinvent the wheel. Use APIs from OpenAI, Anthropic, Mistral, or Meta to build AI-powered applications.
- Example: Notion AI integrates AI-generated writing directly into their productivity tool, rather than building their own model.
3. Build Workflow-Specific AI Solutions
- AI alone isn’t enough; users need seamless workflows.
- Example: Zapier AI integrates LLMs into automation workflows, helping businesses streamline tasks effortlessly.
4. Focus on UX & Trust
- AI models are powerful, but without good UX and reliability, they won’t get adopted.
- Example: Grammarly transformed language models into a simple, trustworthy writing assistant.
5. Monetize via SaaS, API, or Enterprise Sales
- Subscription Models: Charge for AI-powered tools as SaaS (e.g., Jasper AI, Runway AI).
- API Access: Offer AI-driven capabilities via APIs for developers (e.g., ElevenLabs for AI-generated voices).
- Enterprise Customization: Provide AI solutions tailored for businesses (e.g., Harvey AI for law firms).
The Future of AI Entrepreneurship
The AI revolution is still in its early stages. Foundational models will continue to improve, but the real impact will come from entrepreneurs who build specialized AI-driven services. Those who can combine domain expertise, user experience, and AI capabilities will create the next wave of billion-dollar businesses.
If you’re an entrepreneur, the message is clear: You don’t need to build the AI model—you need to build on top of it.
Shunya AI 