Guide to Building an Offshore Team for AI Development

Artificial Intelligence (AI) isn’t just buzz; it’s a business imperative. A July 2024 McKinsey survey shows 78% of companies now use AI in at least one business function, with 71% deploying generative AI (Source). Meanwhile, Bloomberg Intelligence forecasts the generative AI market to swell to $1.3 trillion by 2032, expanding at an annual rate of over 40% .

This surge in adoption underscores AI’s power to accelerate automation, enhance decision-making, and drive operational efficiency. Yet building in-house AI capabilities remains costly and complex. That’s why more businesses are turning to offshore AI development teams to scale fast, cut costs, and tap into global expertise.

Why opt for an offshore team

When looking to achieve peak efficiency and faster business growth, AI development comes to mind, and building or acquiring custom AI solutions seems to be the best and most technologically relevant route.

Building an AI product or solution in-house can turn out to be incredibly expensive and inefficient in the long term, and is something viable only for large corporations due to the enormous costs of hiring developers, buying equipment, and running a project.

Offshore development teams offer flexibility, cost-efficiency, and access to global talent, making them ideal for AI-driven innovation. If you're evaluating external vendors, consider this expert-curated selection of trusted software engineering partners who have experience with large-scale AI and digital projects.

Opting to outsource AI development to an offshore firm is one of the most financially feasible and effective methods of software development. Building your offshore AI team through several means of outsourcing allows you to bypass unnecessary costs and achieve a competitive advantage in your field. If you're also exploring outsourcing for complementary technologies like Python, you can find a full breakdown here.

Pros and cons of using an offshore team for AI

The development process with an offshore AI team

Discovering and Planning Your Project

Conduct market research and assessment to determine the feasibility of the AI project. Lay out the expectations, requirements, and functionality of the AI product you are looking to develop.

Setting up the Offshore Team and Communication

Identify a suitable location for building an offshore team. Recruit members for your team by hiring freelancers or directly contracting an offshore firm for the development. Next, establish communication channels to efficiently collaborate with your offshore team and establish roles in the team.

Developing the AI Model

This is the core of your entire AI project. Design and develop Artificial Intelligence models as per project requirements. Your offshore team will work and develop the back-end of the AI model and front-end integrations of the AI models with other software.

Testing and Validating

This is the final step in the development before your AI product is released. The developers rigorously test the AI model to identify flaws and inconsistencies hindering the performance and functionality of the AI product, which is then fixed.

Project Completion and Deployment

Once the development is finished, deploy the final product to the world through distribution channels like the Internet or the AppStore. Once deployed, the AI solution will have to constantly be monitored and have maintenance carried out on it.

Setting up an offshore AI team requires not just technical alignment but also a clear understanding of your overall AI goals. If you’re still defining your approach, you can find more insights in this guide on building an AI program from scratch.

Types of AI solutions you can develop with an offshore team

1. Natural Language Processing
2. Chatbots and Virtual Assistants
3. Generative AI
4. Machine Learning
5. Computer Vision
6. Advanced-Data Analytics
7. Information Extraction
8. Text Mining and Analysis

Steps to building an offshore team for AI

Define project requirements

Begin by clearly defining the scope, objectives, and requirements for the AI development project. Determine the specific skills, expertise, and resources required to complete the project goals. Consider project complexity, timeline, and budget constraints when setting realistic expectations.

Identify offshore locations

Investigate and evaluate potential offshore locations using criteria such as cost-effectiveness, talent availability, cultural compatibility, and geopolitical stability. Consider countries known for their strong IT industries, skilled workforces, and favorable business environments. Examine the legal and regulatory landscape, infrastructure, and connectivity options to ensure suitability for offshore operations.

Select an offshore partner

Identify and vet potential offshore partners, such as outsourcing companies, development agencies, and freelancers, based on their AI expertise, experience, and track record. Conduct thorough due diligence, review client testimonials, and request case studies or references to determine credibility, dependability, and suitability for your project requirements.

Define roles and responsibilities

Determine the roles, responsibilities, and skill requirements for each member of the offshore team. Determine the team composition, which should include data scientists, machine learning engineers, software developers, project managers, and domain experts, based on project requirements and available resources. Create reporting structures, communication channels, and performance metrics to ensure accountability and consistency.

Develop a project management framework

Implement a strong project management framework, such as Agile or Scrum, to manage the development process effectively. Define project milestones, deliverables, and timelines, then allocate resources accordingly. Hold regular meetings, stand-ups, and progress reviews to keep track of project progress, identify risks, and address issues before they arise. Monitor performance, track tasks, and keep stakeholders informed using project management tools and dashboards.

Manage performance and quality

Implement performance management systems and quality assurance processes to track and evaluate the performance of offshore team members. Establish key performance indicators (KPIs), metrics, and benchmarks to assess productivity, efficiency, and work quality. Regular performance reviews, 360-degree feedback sessions, and skill assessments can help identify areas for improvement and provide targeted support and training as needed.

Roles you need to successfully build an offshore AI team

Models for building an offshore AI development team

These roles might differ in priority depending on the complexity of the AI project but many strategies to outsource development can be utilized in hiring or filling the roles:

Offshore Development Centers (ODCs)

A dedicated crew of developers, data scientists, and machine learning experts situated in a less expensive tech hub, such as Eastern Europe, Vietnam, or India, is known as an offshore development center. These teams are led by your internal leads or a third-party partner, and they only work on your projects. For businesses preparing long-term AI projects that need for flexible capacity, strong subject knowledge, and constant cooperation, ODCs are perfect. They work similarly to your own team but provide significant cost reductions (usually 40–60%) without compromising the quality of the staff.

You can explore some of the top-performing offshore companies for AI development in this list of leading AI development companies.

Remote teams

With this technique, AI experts from various regions are hired to work remotely, either alone or in small groups. Remote teams may produce outstanding outcomes and provide you access to a larger global talent pool if you have the proper communication and project management tools. Startups and lean product teams that desire flexibility and speedy onboarding may find remote hiring particularly helpful. However, effective collaboration practices and well-defined deliverables are essential for success.

Staff augmentation

By using contract-based AI specialists, such as data engineers, ML operations specialists, or NLP developers, to support a particular project phase, staff augmentation enables you to temporarily fill skill gaps. Scaling your workforce only when necessary allows you to keep control over the workflow. Without the commitment of full-time hiring, this model is ideal for businesses with an existing tech team that require temporary assistance with tasks like model testing, algorithm improvement, or deployment optimization.

Outsourcing advisory services

An outsourcing consultancy service can help you if you're contemplating a major AI transition or are new to offshore development. These specialists assist you with goal-setting, vendor selection, legal pitfalls, and efficient offshore contract management. They are particularly useful in situations involving several vendors, sensitive data, regulatory compliance, or extremely specialized AI requirements.

Best Countries to Build Offshore Teams In

India

India remains a global leader in offshore AI development thanks to its large talent pool, affordable labor rates, and mature outsourcing ecosystem. With over 5 million people employed in the IT sector (Statista), the country offers deep expertise in AI, machine learning, and data science.

Cities like Bangalore, Hyderabad, and Pune host major AI R&D centers, tech startups, and global capability hubs. India’s strengths also include strong English proficiency, a pro-business environment, and a wide range of offshore service providers. You can explore a firsthand perspective on outsourcing to India right here.

Typical hourly rates range from $20 to $40, making it one of the most cost-effective options globally, without compromising on technical quality.

Philippines

Because of its large pool of English-speaking workers and close cultural ties to Western clients, the Philippines is becoming a popular location for offshore AI development. Government-backed tech incentives and an expanding pool of AI-ready experts are available in cities like Manila, Cebu, and Davao. The nation is well-positioned for AI outsourcing because of its established BPO sector and growing pool of qualified data scientists and software developers. Strong communication and workforce availability are advantageous to enterprises, and hourly prices are quite reasonable, usually ranging from $25 to $40.

Vietnam

Vietnam is a fast-rising offshore AI hub, thanks to its young, tech-savvy talent pool, growing startup scene, and government-backed tech incentives. Cities like Ho Chi Minh City, Hanoi, and Da Nang are emerging as innovation centers with strong AI research and development activity.

With competitive hourly rates averaging $20 to $35, Vietnam is highly cost-effective while offering solid engineering skills, especially in Python, TensorFlow, and machine learning frameworks. Its cultural compatibility, English proficiency, and strategic Southeast Asian location make it ideal for companies targeting the ASEAN market or seeking regional expansion.

Brazil

Brazil is an emerging offshore AI hub in Latin America, offering a diverse talent pool of software engineers, data scientists, and AI specialists. Cities like São Paulo, Rio de Janeiro, and Belo Horizonte are known for strong academic institutions and a growing tech ecosystem.

With increasing government support for innovation, Brazil is gaining popularity for AI outsourcing. Additionally, it provides time zone and cultural alignment with North American clients, which facilitates real-time engagement.

Hourly rates range from $30 to $50, offering a balance between affordability and quality in the region.

The Road Ahead in Offshore AI Development

AI software development has a bright future ahead of it thanks to constant improvements in technology, approaches, and applications:

• Technological Advancements: As AI algorithms, frameworks, and platforms continue to advance, the creation of intelligent systems that can handle a wide range of difficult possibilities and challenges in a variety of industries and disciplines will be accelerated.

• Industry Adoption: The use of AI is predicted to pick up steam across a variety of industries, boosting the need for specialized knowledge, abilities, and solutions to fully realize the transformative potential of AI in fostering innovation, boosting competitiveness, and providing value to clients.

• Offshore Development: With access to worldwide talent pools, specific capabilities, and affordable solutions to meet changing market dynamics and consumer expectations, offshore teams will become more and more important in satisfying the expanding demand for AI talent.

Conclusion

Offshore AI development teams are becoming a strategic option for businesses looking to cut expenses, boost innovation, and maintain their standing in a quickly changing digital market. Although there are obvious advantages, such better delivery efficiency and access to specialized worldwide talent, success hinges on resolving significant issues with data protection, communication, quality control, and regulatory compliance.

By establishing clear processes, investing in the right tools, and forming strong partnerships, businesses can navigate the complexities of offshore collaboration. With a well-structured team and strategy, organizations can fully leverage offshore capabilities to drive impactful AI initiatives and long-term growth. In fact, a recent Deloitte Global Outsourcing Survey found that 70% of organizations report cost reduction as their main reason for outsourcing, while 40% highlight greater flexibility and speed to market as key benefits.