In a context where artificial intelligence in business becomes an integral driver of competitiveness, and international markets impose increasingly complex registration requirements, licensing and AML compliance, choosing a scaling strategy is not just a matter of efficiency, but a guarantee of survival and growth.
In this article I, Nikita Veremeev, founder of COREDO, share practical insights accumulated by our team over years of supporting AI companies in the EU, Asia and the CIS.
If you want not just to keep up with trends but to build an AI company growth strategy based on the best international practices — read carefully. Here you will find not theory, but practical solutions tested in a wide range of jurisdictions and industries.
AI company development strategies: Oil Wells and Pipelines
Some companies dig into core processes, creating a unique accounting system (“oil well”), others build platforms that connect and automate disparate workflows (“pipeline”). Understanding the differences between these strategies is important for choosing the optimal growth path in a specific market situation.
The Oil Wells strategy in AI business: what is it?
The Oil Wells strategy is an approach focused on rapid market capture through intensive acquisition of large clients and implementation of high-margin projects. This path is characteristic of AI companies that bet on exclusive solutions, custom implementations and one-off deals requiring significant resources and expert support.
In COREDO’s practice this strategy is often applied in projects for the oil and gas sector and the financial sector, where implementing AI solutions (for example, predictive analytics, intelligent analysis of big data, automation of business processes with AI) produces an immediate effect and high revenues, but requires large investments in the team, infrastructure and legal support.
The Pipelines strategy for AI companies — what is it and why?
The Pipelines strategy is building a stable, predictable stream of clients and projects with optimized costs for acquisition and servicing. This approach involves creating standardized AI products, automating sales processes, implementing digital platforms and forming an AI ecosystem capable of scaling without proportional cost growth.
The COREDO team has implemented a number of projects where the shift to Pipelines allowed AI companies in Europe and Asia not only to reduce the cost of acquiring new clients, but also to ensure compliance transparency, effective risk management and adherence to AML requirements. This is especially relevant for companies operating with SaaS models, AI marketplaces and legal support automation services.
Comparison of Oil Wells and Pipelines strategies for AI companies
| Parameter | Oil Wells | Pipelines |
|---|---|---|
| Costs | High at the start, unstable | Optimized, predictable |
| ROI | High in individual projects | Stable, growing |
| Risks | Dependence on large clients, regulatory complexities | Distributed, manageable |
| Scalability | Limited by resources | High, thanks to automation |
| Stability | Medium, depends on new deals | High, due to repeatability |
The choice of strategy depends on the stage of development of the AI company, market specifics, requirements for legal support and the maturity level of business processes. At early stages, when rapid monetization is critical, Oil Wells can provide the necessary impulse. Still, for long-term growth and entry into international markets, the Pipelines strategy shows better results, especially given modern AML and compliance requirements.
Applying Oil Wells and Pipelines strategies in the development of AI companies
Applying the Oil Wells and Pipelines strategies opens fundamentally different but complementary paths for AI companies to grow and scale. The choice between deep integration into a key workflow (Oil Well) or building a platform that connects different systems and automates processes (Pipeline) is determined by the market character and business objectives.
Next, let’s look at how these strategic approaches are applied when scaling AI companies in Europe and Asia.
Scaling AI companies in Europe and Asia
Registration of legal entities in the EU, Asia or Africa is accompanied by unique requirements for disclosing beneficiaries, licensing financial and AI services, and complying with AML standards.
COREDO’s practice confirms: for AI companies entering the markets of the Czech Republic, Slovakia, Cyprus, Estonia, the United Kingdom, Singapore or Dubai, it is critically important to build a legal support strategy in advance, integrate AI tools to automate KYC/AML processes and ensure compliance with local and international regulatory requirements.
Investing in AI and risk management during scaling
Investments in artificial intelligence are becoming increasingly structured: investors and corporate clients demand transparency, predictability and demonstrable ROI from implementing AI solutions. In practice, COREDO uses metrics such as customer LTV, CAC, speed of solution scaling and the level of business process automation to assess the effectiveness of AI investments.
Such solutions are especially in demand in the financial sector, e-commerce and international trade.
AI integration into business and supply chain optimization
AI for supply chain optimization: one of the fastest-growing segments. Solutions developed by COREDO for clients in the EU and Asia have shown that AI integration not only enables demand forecasting and inventory management, but also minimizes logistical and regulatory risks, increases supply transparency and compliance with ESG standards.
In the oil and gas sector, implementing AI for predictive analytics and intelligent big data analysis reduces downtime, optimizes costs and increases the environmental sustainability of the business. International cases confirm: automating business processes with AI is becoming the standard for companies striving for digital transformation and sustainable development.
Choosing and implementing an AI company growth strategy
Choosing and implementing an AI company growth strategy becomes a key factor for effective growth and long-term success in the fast-changing artificial intelligence industry. In today’s market it is important to understand which strategic approaches, such as Oil Wells or Pipelines, best match your company’s goals and product specifics. Below we will consider how to correctly determine the type of strategy and what to take into account when implementing it.
How to choose an Oil Wells or Pipelines strategy for AI?
The choice of strategy is determined by several key criteria:
- Financial capacity: Oil Wells requires significant initial investments, Pipelines allows cost optimization.
- Growth objectives: If the priority is rapid market entry and monetization, Oil Wells may be justified; for sustainable growth and scaling, Pipelines is preferable.
- Market and regulatory constraints: In regions with strict regulation (EU, Singapore) Pipelines provides greater flexibility and risk manageability.
- Degree of business process maturity: Pipelines requires developed infrastructure, automation and standardization.
To make a decision, the COREDO team recommends using evaluation methodologies that include unit-economics analysis, ROI scenario modeling, assessment of regulatory and legal risks, and an audit of current business processes for automation potential.
Scaling AI companies with two strategies
- Building AI sales pipelines: automating lead generation, implementing CRM systems with AI analytics, standardizing product solutions.
- Monetizing AI products: developing SaaS models, Licensing AI services, forming partner ecosystems.
- Data governance and digital transformation: implementing machine learning tools for business analytics, integrating AI into corporate governance, building an AI ecosystem for international business.
COREDO projects implemented to scale AI companies in Europe and Asia show: combining Oil Wells at the start and transitioning to Pipelines as you grow provides an optimal balance between speed to market and long-term resilience.
Legal aspects of business scaling
- Minimizing regulatory risks: conducting preliminary compliance audits, integrating AI tools to monitor legislative changes, automating AML processes.
- Optimizing legal support costs: using AI to automate document workflow and contract management, deploying NLP technologies to analyze legal documents.
- Compliance with international standards: when registering AI companies in the EU, Asia and Africa it is important to consider requirements for beneficiary disclosure, licensing of AI and financial services, and data protection (GDPR, PDPA, DPA, etc.).
Long-term prospects for AI companies under the Oil Wells and Pipelines strategies
The long-term prospects for AI companies under the Oil Wells and Pipelines strategies are linked to how artificial intelligence transforms extraction, transportation and resource management processes in the energy sector, setting new standards of efficiency and competition. Let’s consider how different strategies, from targeted «Oil Wells» to infrastructural «Pipelines» – affect the competitiveness and resilience of AI-compain the industry.
Delving into the specifics of the Oil Wells strategy, let’s now consider how the infrastructural approaches of Pipelines shape the long-term resilience of AI companies in the energy sector.
Oil Wells Strategy and Competitiveness of AI Companies
The Oil Wells strategy provides rapid growth and high margins at the start, but is associated with risks of dependence on large clients, scaling difficulties, and high legal support costs. For AI companies oriented toward international markets, the long-term consequences may include reduced flexibility, compliance challenges, and constrained opportunities for sustainable development.
Pipelines for Long-term Business Growth
This approach contributes to the formation of an AI ecosystem, the integration of AI into corporate governance, and increased transparency of business processes.
Scaling AI Business and New Technologies
technology development in IoT, NLP, deep learning and advanced analytics of big data opens new opportunities for scaling AI companies. The adoption of AI in intellectual property management, failure prediction, AML automation and the digital transformation of legal support is becoming standard for market leaders.
The Impact of AI on Governance and Digital Ethics
AI technologies are changing approaches to corporate governance, increasing transparency, accountability and business resilience. Issues of digital ethics, data protection and intellectual property become key when entering international markets.
Key Findings and Advice for Entrepreneurs and Executives
| When to apply | Oil Wells | Pipelines |
|---|---|---|
| Startup stage | Fast launch, custom projects, high margin | Building standard products, automation |
| Growth | Expansion through large deals | Scaling through repeatable processes |
| International expansion | Requires complex legal support | Focus on compliance, AML, standardization |
COREDO Recommendations for AI Companies
- Minimize risks: Conduct regular compliance audits, integrate AI tools to monitor legislative changes and automate AML.
- Maximize ROI: Use performance metrics for AI projects (LTV, CAC, scaling speed, level of automation), implement predictive analytics and intelligent big data analysis.
- Optimize legal support: Automate document flow, use NLP technologies to analyze contracts, integrate AI into KYC/AML processes.
- Build an effective team and AI ecosystem: Form international project teams, invest in training and staff development, grow partner networks.
COREDO’s experience shows: a combination of the Oil Wells and Pipelines strategies, flexible risk management, and investments in digital transformation and legal resilience are the key to successful development of AI companies in international markets.