May 14, 2025 • by Delilah (Translated by Dennis T)
What is required of offshore development companies in the era of generative AI
Table of Contents
Generative AI: Evolving from a Cost Center to a Strategic Partner
In recent years, the rapid rise of generative AI technology has fundamentally shaken the development landscape. The conventional development model, which assumed that “humans code everything from scratch,” has been significantly transformed by AI’s capabilities in automatic code generation, requirement organization, and debugging support. As a result, the role of offshore development is also expected to evolve—from being merely a “provider of low-cost labor” to becoming a “partner that contributes to technical proposals and co-creation.”
Changes in the Development Model Brought About by the Evolution of Generative AI
The Reality of AI-Generated Code
AI assistants like GitHub Copilot and ChatGPT are already dramatically improving the speed and accuracy of many developers’ work. According to a 2023 GitHub survey, over 80% of developers using AI assistance felt they were “saving time,” and more than half reported that they were “able to write better code.”
Automation of the Development Process
AI’s support continues to expand beyond code generation to include automated test code generation, bug detection, documentation creation, and even drafting UI design proposals. As a result, the cycle from specifications to prototype creation has been drastically shortened, forcing a restructuring of the traditional segmented offshore development model.
Limitations of Traditional Offshore Development
The End of the “Wait-for-Instructions” Model
The once-dominant style of “working exactly as instructed” has become increasingly replaceable by AI. In this era, simple, routine tasks can be completed by generative AI in just seconds.
Increasingly Sophisticated Client Needs
Clients no longer seek just cost savings from offshore development. They now expect more advanced and strategic proposals from offshore companies, such as “how to optimize using generative AI” and “how business processes will change with AI adoption.”
What Capabilities Are Required of Offshore Companies in the Era of Generative AI?
AI Literacy and Engineer Re-Skilling
Offshore companies need to actively re-educate their employees—not only in traditional specialties such as front-end/back-end development but also in new AI-era fields like prompt engineering, model design, and data ethics.
Understanding Japanese and Grasping Context in Specifications
While generative AI enables high-precision translations, it cannot fully interpret vague Japanese specifications or the cultural context of “reading the air.” It is essential for offshore project managers and bridge system engineers to deepen their understanding of both the Japanese language and Japanese corporate culture.
Fusion of Automation and Human Judgment
AI is a powerful tool, but it is not perfect. Offshore companies must refine a “co-creation” development style that incorporates human judgment rather than accepting AI-generated suggestions at face value.
Development Methods and Tool Utilization that Leverage Generative AI
Prompt Quality Determines the Outcome of Generative AI
The core skill for mastering AI is “prompt engineering.” For example, instead of simply telling ChatGPT, “Make an e-commerce site,” a more specific prompt like “Generate a React-based UI proposal with login, cart, and payment functions in Figma” will yield better results.
Building DevOps Integrated with LLMs
AI is also being integrated into automated testing, code reviews, and error analysis within CI/CD. By adopting tools like GitHub Actions and Copilot Labs, AI can provide initial bug-fix suggestions, allowing engineers to focus on reviewing and refining the code.
Integration of No-Code/Low-Code
More small and medium-sized clients are combining AI with no-code tools. Offshore companies should build a framework to support platforms like Adalo, Bubble, and Outsystems, enabling them to go beyond just code delivery and also support business process automation.
Case Studies and Initiatives by Offshore Companies
Example: Establishment of an AI Lab in India
An Indian company set up an in-house AI-focused division and built a system in which 20% of development was supported by AI. As a result, they achieved shorter estimation times and improved customer satisfaction.
Vietnamese Company’s Japan-Focused AI Team
A Vietnamese company launched a Japanese-language AI team targeting the Japanese market. They secured projects such as proposing UI designs using generative AI and building FAQ chatbots, achieving a high client retention rate.
What Is Needed to Build Strategic Partnerships in this Generative AI era?
The Power to Collaborate from the Early Stages of a Project
Instead of a traditional “receive the specification → deliver the product” model, a shift is needed toward a style of “thinking together, proposing together, and improving together” from the planning stage. Especially with generative AI, the correct usage during the design phase is the key to a project’s success.
Utilizing AI for Knowledge Sharing and Avoiding Reliance on Individuals
By using generative AI to summarize and organize meeting minutes, key specification points, and development history, this information can be turned into a shared internal knowledge base. This helps prevent over-reliance on specific individuals and contributes to stabilizing quality.
Toward Becoming a “Chosen Offshore Partner” in the Generative AI Era
Offshore development going forward will be evaluated not by “low cost” but by the “value provided.” The wave of generative AI is unavoidable, and only companies that not only use it but strategically harness it will survive. The following elements will be essential:
Adoption of prompt engineering and AI skills
Ability to make upstream proposals to clients
Capability to work with no-code and low-code platforms
Project management methods that assume generative AI use
Deep understanding of Japanese culture and business practices
The future of offshore development will evolve into a “co-creative model” supported by a trinity of technical expertise, human understanding, and AI literacy.
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Glossary of Terms Used in This Article
Generative AI Artificial intelligence technology that automatically generates content such as text, images, and audio. Examples include ChatGPT, Midjourney, and GitHub Copilot.
Offshore Development The practice of outsourcing software development tasks to companies in other countries. This is often done to reduce labor costs or secure skilled human resources.
Prompt Engineering The technique of designing and adjusting prompts (instructions) to get optimal output from generative AI.
LLM (Large Language Model) AI models trained on massive amounts of text data. Examples include ChatGPT, Claude, and Gemini.
No-code / Low-code Tools that enable application development with minimal to no programming knowledge. No-code tools rely entirely on GUI operations, while low-code tools may require some coding.
Bridge System Engineer (Bridge SE) A technical professional who acts as a bridge between the client and the development team. They handle specification coordination and project management while navigating language and cultural differences.
CI/CD (Continuous Integration / Continuous Delivery) Core DevOps processes that automate the workflow from development to testing and release. Integrating AI into these workflows increases efficiency.
FAQ (Frequently Asked Questions)
Q1. Why is generative AI expertise important for offshore development now? A. Since generative AI can now handle basic tasks like boilerplate code generation, offshore firms are expected to offer higher value through AI utilization and strategic suggestions.
Q2. Why is prompt engineering so important? A. AI operates based on the given prompt. Vague instructions lead to poor results, so crafting precise and effective prompts is essential for achieving high-quality outputs.
Q3. How can offshore teams overcome cultural gaps with Japanese companies? A. In addition to understanding the Japanese language, it is crucial to grasp Japan-specific business etiquette and nuances. A skilled Bridge SE plays a key role in overcoming these challenges.
Q4. I’m worried AI will take over jobs. How should I think about this? A. AI is a tool — it can enhance productivity when used properly. The key is to know what tasks can be automated and which ones still require human judgment.
Q5. What should we look for when choosing an offshore partner? A. Rather than focusing on traditional metrics like price or man-months, it’s important to consider AI implementation experience, proposal capabilities, Japanese language proficiency, and ability to support no-code/low-code solutions.
