Best AI strategy playbook.
To build a winning AI product, you need to study the best in the game — but more importantly, study the right layer of the stack.
Here’s how the top 25 AI companies are playing it:
LAYER 1: FOUNDATION MODEL PROVIDERS
Powering the entire AI ecosystem
- OpenAI — Tiered access model with Pro upgrade path
- Anthropic — Constitutional AI with enterprise-grade guardrails
- Google — Distribution advantage via deep ecosystem integration
- Meta — Open-sourcing Llama to enable a long-term platform play
- Cohere — Focused document intelligence with a clear ROI story
Key Strategy:
Specialize your capabilities. Version clearly. Find the right open vs. closed balance.
LAYER 2: AI DEVELOPMENT PLATFORMS
Tools for building AI applications
- Hugging Face — Community-led hub with strong network effects
- Weights & Biases — Workflow-centric experiment tracking for teams
- Databricks — Unified stack from data to models for enterprise ML
- Anyscale — Simplified distributed compute for scalable workloads
- Labelbox — End-to-end data labeling for model training quality
Key Strategy:
Solve specific developer pain points while creating network effects between data and models.
LAYER 3: AI INFRASTRUCTURE & OPTIMIZATION
Making deployment faster and more efficient
- NVIDIA — Ecosystem lock-in via CUDA across hardware and software
- AMD — Open-source alternative with ROCm for broader access
- Snowflake — Smart adjacency, embedding AI into the data stack
- Pinecone — Vector databases making embeddings developer-friendly
- Together AI — Optimized inference for multi-model workflows
Key Strategy:
Target performance bottlenecks. Balance proprietary infrastructure with general-purpose usability.
LAYER 4: VERTICAL AI SOLUTIONS
Industry-specific value delivery
- Jasper — Templates for marketers driving $125M ARR
- Harvey — Legal workflows backed by $400M valuation
- Viable — CX insight engine turning unstructured data into action
- Runway — AI video editing tools at a $1.5B valuation
- Rendered.ai — Synthetic data generation for niche use cases
Key Strategy:
Deeply understand domain-specific workflows. Balance automation with human oversight.
LAYER 5: ENTERPRISE AI INTEGRATION
Operationalizing AI at scale
- Microsoft — Embedding AI where users already work (Office, Teams)
- Salesforce — Role-based AI workflows across CRM functions
- Palantir — Human-in-the-loop AI in government and defense
- Workday — Structured data ontologies for HR and finance AI
- ServiceNow — IT workflow automation with strong governance
Key Strategy:
Integrate AI into high-value workflows. Make adoption feel like a natural extension, not a new tool.
Final Takeaway:
Your AI strategy must be layer-specific.
What works for OpenAI won’t work for a niche vertical solution.
What works for Hugging Face won’t translate to enterprise AI integration.
But one principle cuts across everything:
Start narrow. Focus on a clear use case.
Prove value. Then scale.
