If until a few years ago companies were asking "should we implement AI?", today the question has become "how do we strategically position ourselves in AI ecosystems?"

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By 2025, the enterprise AI market has reached a maturity where five distinct business archetypes can be identified, each with specific strategies and different performance metrics.

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The Evolution from the Tool to the AI Ecosystem

According to PwC's latest report on AI 2025 predictions, "companies can no longer afford to approach AI governance in an inconsistent or compartmentalized manner." The focus has shifted from implementing individual AI tools to orchestrating complex AI ecosystems.

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As highlighted by Sequoia Capital, "if 2024 was the year of the primordial soup for AI, now the fundamental building blocks are firmly in place." This consolidation has resulted in five distinctive company types.

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1. The AI Ecosystem Orchestrators: The New Giants of Platforms.

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Who I Am

AI Ecosystem Orchestrators are the companies that control the central platforms and define the rules of the game. They coordinate the entire AI ecosystem through vertical integrations that bring together hardware, software, data and services.

Examples of Success

• Microsoft: With Azure AI Foundry supports over 1,900 partner models and has implemented full support for the Model Context Protocol (MCP)
• Adobe: Launched theAdobe Experience Platform Agent Orchestrator, which manages AI agents across Adobe and third-party ecosystems
• Google Cloud: Continues to expand AI integration across cloud services, workspace and consumer products
• Amazon Web Services: AWS Bedrock serves as central hub for enterprise AI services

Winning Strategy

These giants create a "gravitational effect" around their platforms, facilitating connections between developers, data, and AI capabilities. Their strength lies in their ability to reduce coordination costs and accelerate innovation through network effects.

Competitive advantages:

• Control of critical infrastructure
• Exponential network effects
• Ability to set industry standards

Main challenges:

• Antitrust risks and regulatory control
• Balancing between openness and proprietary control
• Maintaining innovation during scalability

2. Native AI Specialists: Pioneers of the New Era

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Who I Am

Specialized AI Natives are companies built from the ground up to leverage artificial intelligence. They develop proprietary foundational models and have rapid iteration cycles that enable faster innovation speeds.

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Examples of Success

According to GlobalX ETFs, these players are seeing extraordinary growth:

• OpenAI: Projected to finish 2024 with $5 billion in net revenue, a 225% increase year-over-year
• Anthropic: Growth from $100 million to $1 billion in one year
• Perplexity: Has reached 10 million monthly active users as an AI search engine
• Mistral AI: European leader with strong open-source presence

Winning Strategy

Obsessive focus on model performance, AI-optimized user experience, and ability to move quickly to capture new use cases. They monetize through APIs and consumer/enterprise applications.

Competitive advantages:

• Superior speed of innovation
• Complete control of the technology stack
• Ability to set new standards

Main challenges:

• Capital intensity for training and compute
• Fierce competition over foundational models
• Need for differentiation beyond performance

3. Sector Transformers: AI Meets Domain Expertise.

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Who I Am

Sector Transformers combine deep vertical knowledge with AI capabilities. They integrate into existing industry processes and are compliance-ready to address specific regulatory requirements.

Examples of Success

• Tesla: Integrated auto-energy ecosystem with native AI and more than 36,500 Supercharger ports in the U.S.
• Palantir: Has recently won contracts for AI services in the defense and government sectors
• Salesforce: Agentforce platform for CRM and sales automation
• ServiceNow: IT service management enhanced by AI agents

Winning Strategy

They transform traditional industries by applying AI to domain-specific problems. Their strength lies in their deep understanding of existing workflows and ability to demonstrate tangible ROI.

Competitive advantages:

• Irreplaceable domain expertise
• Established relationships in the industry
• Ability to demonstrate concrete ROI

Main challenges:

• Resistance to change in traditional sectors
• Long enterprise sales cycles
• Need for continuing market education

4. The Intelligent Aggregators: The Masters of Orchestration

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Who I Am

Smart Aggregators integrate capabilities from multiple sources, excel at orchestration, and optimize costs through smart routing between different AI services.

Examples of Success

• Databricks: As highlighted by the Bain report, launched Databricks One for a unified experience on the Data Intelligence Platform
• Snowflake: data cloud with built-in AI capabilities
• UiPath: Agent automation orchestrating cross-platform processes
• LangChain: Open-source tools for orchestrating AI models.

Winning Strategy

They create value by aggregating and optimizing the use of multiple AI capabilities. They become indispensable as "coordination layers" between different AI technologies.

Competitive advantages:

• Multi-vendor flexibility
• Cost and performance optimization
• Reducing complexity for customers

Main challenges:

• Dependence on external vendors
• Increasing complexity in multi-vendor management
• Pressure on margins from commodity services

5. Strategic Consumers: AI to Empower Core Business.

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Who I Am

Strategic Consumers prefer a "buy vs. build" approach, using AI to enhance the core business through rapid implementation of tested solutions.

Examples of Success

• Retail chains: Grocery and fashion stores integrating AI for inventory and pricing
• Financial services: Regional banks adopting AI for risk management
• Manufacturing: Companies using AI for predictive maintenance
• Healthcare providers: Healthcare systems implementing AI diagnostic tools.

Winning Strategy

They leverage others' innovation to accelerate digital transformation. They focus on integration and change management rather than technology development.

Competitive advantages:

• Accelerated time-to-market
• Reduced R&D costs
• Focus on core business

Main challenges:

• Risks of vendor lock-in
• Limited competitive differentiation
• Dependence on external ecosystems

AI Market Trends 2025: Convergence and Collaboration

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The Shift toward "Buy vs. Build"

According to Andreessen Horowitz 's research of 100 enterprise CIOs, "we have seen a marked shift toward third-party app purchases over the past twelve months as the AI app ecosystem has begun to mature."

Democratization of AI

Declining costs and no-code platforms are also enabling SMEs to access advanced AI capabilities. As reported by Morgan Stanley, "companies in the data and cloud infrastructure ecosystem are building tools to help enterprises automate observability."

Governance as Differentiator

With AI becoming mission-critical, the ability to implement robust governance, compliance and risk management is becoming a key competitive advantage.

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How to Choose the Right AI Strategy for Your Company

Assess Your Resources and Skills

• Available Budget: Orchestrators require massive investments, Strategic Consumers can start with limited budgets
• Technical Expertise: AI Natives need deep tech skills, Domain Transformers need domain knowledge
• Strategic Goals: Do you want to control the ecosystem or participate effectively?

Consider Your Sector

Some areas are more mature for certain strategies:

• Tech and Software: Better suited for Native AI strategies or Orchestrators
• Traditional Sectors: Often best served by Transformers or Strategic Consumers.
• B2B Services: Opportunities for Smart Aggregators.

Think Long-Term

The categories are not fixed. Microsoft joining the Workday AI Agent Partner Network illustrates how even competitors collaborate to address multi-agent orchestration needs.

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Conclusions: The Future Belongs to Ecosystems.

In 2025, success in AI no longer depends on the choice of a single tool, but on the ability to strategically position oneself in AI ecosystems. As the research highlights, "companies in the top 20% in 2025 are 2.3 times more likely to derive 60%+ of their revenues from ecosystems."

Key takeaways for decision makers:

1. Identify your current category and assess whether it is aligned with your strategic goals
2. Develops orchestration skills regardless of the category chosen
3. Invest in AI governance as a competitive differentiator
4. Maintain flexibility to evolve between categories as the market matures

The key to success is not just choosing the right category, but evolving strategically as the AI ecosystem continues to transform.

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FAQ: The 5 Types of Companies in the Age of AI.

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1. How do I figure out which category my company falls into?

To identify your category, consider three key factors:

• Technological control: Do you develop your own AI models or use third-party ones?
• Position in the ecosystem: Are you at the center of a platform or do you participate in the ecosystem of others?
• Strategic Focus: Is AI your core business or a tool to empower other areas?

If you develop proprietary models and AI is your main business, you are probably an AI Native. If you orchestrate multiple technologies for customers, you might be an Aggregator. If you use AI to transform a specific industry, you are an Industry Transformer.

2. Is it possible to change categories over time?

Absolutely. The categories are not fixed, and many companies evolve strategically. For example:

• Tesla started as an Industry Transformer (automotive) and is moving toward Orchestrator (energy, AI, mobility)
• Microsoft moved from traditional software to AI Ecosystem Orchestrator
• Many traditional companies are evolving from Strategic Consumers to Sector Transformers.

The key is to plan this evolution according to your skills and resources.

3. Which category offers the greatest potential for growth?

Each category has different potentials:

• Orchestrators: Higher potential revenue but huge investment
• AI natives: Rapid growth (OpenAI +225% by 2024) but high competition
• Transformers: Sustainable growth with less risk
• Aggregators: Good margins if you develop proprietary IP
• Consumers: faster ROI but limitations in differentiation

The potential depends on your specific situation and industry.

4. How much budget does it take to implement an effective AI strategy?

Budgets vary dramatically by category:

• Orchestrators: Billions (AWS spends over $75 billion on capex)
• AI natives: Hundreds of millions for training and infrastructure
• Transformers: From millions to tens of millions for sectoral development
• Aggregators: From hundreds of thousands to millions per platform
• Consumers: From thousands to hundreds of thousands for existing solutions

Many SMEs can start as Strategic Consumers with limited budgets and grow progressively.

5. What are the main risks for each category?

Orchestrators:

• Antitrust and regulatory risks
• Need for continuous huge investment
• Complexities in managing global ecosystems

AI natives:

• Market bubble and overvaluation
• Extreme competitive intensity
• Dependence on scarce and expensive talent

Transformers:

• Resistance to change in traditional sectors
• Long adoption cycles
• Need for continuing market education

Aggregators:

• Commoditization of services
• Dependence on external vendors
• Pressure on margins

Consumers:

• Vendor lock-in
• Limited competitive differentiation
• Dependence on external roadmaps

6. How to avoid vendor lock-in if I am a Strategic Consumer?

Strategies for maintaining flexibility:

• Multi-vendor approach: Don't depend on a single vendor
• Standardized APIs: Choose solutions with open standards
• Data portability: Make sure you can export your data
• Flexible contracts: Avoid long contractual lock-ins
• Internal capability building: Develop internal skills gradually

7. Which category is most suitable for SMEs?

SMEs usually begin as Strategic Consumers because:

• Limited budgets
• Need for rapid ROI
• Focus on core business
• Limited technical skills

However, innovative SMEs can aim to become Sector Transformers by leveraging in-depth knowledge of specific niches.

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8. How to measure the success of my AI strategy?

Key KPIs by category:

Orchestrators: Number of partners in the ecosystem, volume of transactions on the platform, market share

Native AI: Model performance, user growth, revenue per user, speed of innovation

Transformers: sectoral ROI, adoption in target market, customer satisfaction, time-to-value

Aggregators: Number of integrations, reduced costs for customers, retention rate

Consumers: Improved KPI business core, time-to-implementation, cost savings

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9. What is the impact of the European AI Act on different categories?

TheEU AI Act has differentiated impacts:

Orchestrators: Increased compliance responsibilities for the entire ecosystemNativeAI: Stringent requirements for high-risk modelsTransformers: Need for industry-specific compliance (e.g., healthcare, finance)Aggregators: Due diligence responsibilities on vendorsConsumers: Audit duties on purchased systems

AI governance becomes a competitive differentiator for all categories.

10. What is the future of AI categories?

Emerging trends include:

• Convergence: Increasingly blurred boundaries between categories
• Vertical Specialization: Growth of Niche Transformers
• Democratization: More SMEs Become Strategic Consumers
• Consolidation: Mergers and acquisitions between Aggregators
• Regulation-driven differentiation: compliance as a competitive advantage