As a member of a UK academic committee focused on digital technologies and their societal impact, I frequently encounter public debates shaped far more by speculation than by evidence. Among all emerging technologies provoking both enthusiasm and anxiety, artificial intelligence—particularly large language models like ChatGPT—stands at the heart of contemporary conversation. While public discourse often centres on AI’s effects on jobs, education, and privacy, less attention is paid to the quieter but profoundly consequential transformations happening inside Britain’s software development workforce. One such transformation is occurring in the domain of code review, a routine yet foundational practice determining the reliability, safety, and security of digital systems.
From banking systems and NHS software to transport networks, retail platforms, and local council services, the UK’s digital infrastructure depends on code written daily by developers, contractors, and teams dispersed across the country. Code review ensures that this software is not only functional but robust, maintainable, and aligned with industry best practices. It is a process that requires precision, experience, and patience. Now, ChatGPT is changing how this work is carried out, offering speed, breadth of knowledge, and fatigue-free consistency that complements human judgement.
In this essay, I explore how ChatGPT is being applied to code review in a variety of UK contexts, what benefits and risks it introduces, how developers and organisations are adapting, and what this means for the future of Britain’s digital economy. My aim is to provide a clear and balanced overview for the general public: not a technical treatise, but a well-grounded explanation of why this shift matters and how the UK might respond wisely as the technology continues to advance.
Before examining ChatGPT’s role, it is important to understand the significance of code review itself. While the public often imagines software as a finished product delivered in polished apps, websites, or backend systems, the reality is that software is organic and constantly evolving. Code is written by humans, and like any human endeavour, it is prone to mistakes. Even the most experienced developers can introduce bugs, security vulnerabilities, or inefficient patterns without realising it. These errors are often subtle: a misplaced comma, a misunderstanding about how a library function works, or a piece of logic that functions correctly 99 per cent of the time but fails catastrophically under rare conditions.
Code review acts as a second line of defence. Typically, one developer writes a piece of code, then another—often a colleague—examines it for technical correctness, style, security implications, and compatibility with the broader system. In high-stakes environments such as defence, healthcare, or finance, multiple reviewers may be required.
However, code review can be time-consuming. It requires the careful allocation of skilled developer hours, and teams often face competing pressures between reviewing code thoroughly and delivering features on schedule. This tension has only intensified as the UK’s demand for digital services expands faster than the supply of experienced developers.
Enter ChatGPT. When trained on appropriate datasets and integrated responsibly into development workflows, ChatGPT can analyse code rapidly, comment on potential issues, and offer explanations or alternatives that assist human reviewers. It does not replace them—nor should it—but it provides an additional layer of insight that can improve both speed and quality. Its ability to scan large sections of code, notice patterns, and identify anomalies makes it particularly suited for early detection of issues that would otherwise appear only after costly debugging cycles.
While ChatGPT is known publicly for its conversational abilities—answering questions, drafting essays, or generating summaries—its technical capabilities extend into understanding programming languages. These include Python, JavaScript, Java, C++, TypeScript, Go, and many more. What differentiates ChatGPT from typical static analysis tools is its flexibility: it can read code in natural language context, reason about architecture, and critique logic in ways that resemble a human reviewer.
Developers currently apply ChatGPT in three primary ways:
Instead of sending code directly to colleagues, developers first ask ChatGPT to perform an initial review. It may flag:
Typographical errors
Inefficient algorithms
Deprecated functions
Suspicious logic
Missing test cases
Potential security vulnerabilities
This stage often reduces the “noise” in later human reviews, freeing developers to focus on more nuanced architectural or business-logic concerns.
During a traditional review, a colleague might leave a vague comment—“this function is too complex” or “this block needs refactoring.” ChatGPT can assist by explaining why the comment might have been made, offering a rewritten version of the code, or breaking down best practices.
Junior developers and career changers—an increasingly important demographic in the UK’s tech ecosystem—use ChatGPT as a mentor-like tool. When they struggle to understand why certain code fails a review, ChatGPT can walk them through reasoning step by step.
This educational dimension is often overlooked but particularly important for a country seeking to broaden participation in its digital workforce.
From government departments to startups, from universities to multinational corporations operating across the UK, ChatGPT is already affecting software development practices. Its benefits manifest across several dimensions.
Code review bottlenecks are a real issue in software teams. If one developer is unavailable—illness, leave, or workload—the entire process may stall. ChatGPT’s instant availability and consistency help smooth daily workflows, shortening development cycles and accelerating delivery timelines without sacrificing rigour.
ChatGPT’s breadth of training gives it awareness of programming patterns, common pitfalls, and historical issues encountered in many real-world systems. When used sensibly, this leads to cleaner, more reliable code. In areas such as cybersecurity, where the cost of failure is especially high, even small improvements can be invaluable.
AI-assisted reviews allow human reviewers to spend more time on conceptual discussions—architecture, design intent, system interactions—and less time on trivial formatting or stylistic issues. Many UK teams report better collaboration and more meaningful peer interactions as a result.
A notable advantage is that ChatGPT helps level the playing field for early-career developers, contract workers, and those who learned coding through alternative pathways such as bootcamps. When used as a supportive resource rather than a crutch, the technology gives more individuals access to guidance that historically depended heavily on the availability of senior colleagues.
Local councils, NHS trusts, and public agencies often operate with limited budgets and tight deadlines. AI-assisted code review provides them with a supplementary layer of quality assurance without requiring the hiring of large additional teams.
While the benefits are substantial, ChatGPT is not a panacea. There are important caveats that the British public, developers, and policymakers should understand.
ChatGPT may occasionally produce incorrect or misleading explanations. While it is extremely capable, it does not possess infallible logic. A human reviewer must always hold final responsibility.
Organisations must avoid pasting sensitive or proprietary code into public AI tools. Many teams now use self-hosted or enterprise versions of ChatGPT to ensure code remains secure. Clear guidance and policies are essential—especially in sectors involving critical national infrastructure.
Some inexperienced developers might accept AI suggestions without fully understanding them. This risks producing code that works but is poorly understood—a vulnerability when systems need maintenance later.
AI anxiety is real, particularly in industries that have already experienced automation-driven change. While ChatGPT does not replace developers, it does alter the skillset required. UK employers and educational institutions must ensure workers receive training to adapt rather than feeling displaced.
If future decisions rely heavily on AI-driven code changes and something goes wrong, who bears responsibility? Clear governance is essential, especially in regulated sectors like finance or healthcare.
In surveys conducted across British universities and industry partners, several trends are emerging:
Most developers see ChatGPT as a tool—similar to version control or automated testing—not as a colleague replacing their jobs. They want clear institutional guidelines and training.
Organisations are updating their internal code review documentation to specify:
What AI may be used for
When human approval is required
How AI-generated suggestions should be validated
Universities and coding bootcamps increasingly teach “AI-assisted development,” emphasising that future developers must be able to collaborate with AI tools responsibly.
The rise of AI-assisted code review has implications far beyond individual teams. It touches on national productivity, digital sovereignty, economic competitiveness, and the UK’s ability to innovate.
The more reliable our code, the more stable the systems we depend on daily—from NHS appointment software to HMRC digital tax platforms.
AI-assisted tools expand the capacity of junior developers, enabling faster onboarding and reducing barriers to entry for career changers, including those from underserved communities.
Better-reviewed code means fewer vulnerabilities. AI can detect patterns of weakness long before attackers do.
As the UK government continues to digitise services, AI-assisted code review offers a cost-effective means of improving quality without ballooning budgets.
Countries like the United States, Singapore, and South Korea are rapidly adopting AI-assisted development tools. The UK must keep pace to remain competitive.
For ChatGPT to be applied effectively and ethically in code review, several principles should guide UK organisations:
Humans must hold final accountability for code that enters production.
Public sector and private organisations should avoid exposing sensitive information to unsecured tools.
AI literacy—understanding both strengths and limitations—should become standard in British digital education.
If AI contributes to code changes, that contribution should be documented, traceable, and reviewable.
AI tools should help broaden participation in tech, not reinforce existing inequalities.
ChatGPT is likely only the first wave of advanced AI tools entering development workflows. Over the next decade, we may see:
AI systems that understand entire codebases, not just snippets
AI that collaborates in real time with multiple team members
Regulatory frameworks governing AI-generated code in public systems
New professional roles specialising in AI-assisted development
The emergence of “explainable AI reviewers” meeting audit-grade requirements
If adopted responsibly, AI can strengthen—not undermine—the UK’s digital ecosystem.
ChatGPT’s role in code review may seem like a niche technical change, invisible to most of the British public. But it represents a fundamental shift in how software—the backbone of modern society—is built and maintained.
This technology:
Enhances productivity
Improves software quality
Supports junior developers
Strengthens cybersecurity
Helps public services modernise
Contributes to national competitiveness
Yet it must be deployed carefully, with clear guidelines, ethical safeguards, and human oversight. The UK has an opportunity to lead globally in responsible AI adoption, ensuring that our digital systems remain resilient, secure, and efficient.
As we navigate this new era, our national conversation should shift away from fear and speculation and toward informed, evidence-based engagement. AI is not replacing British developers; it is empowering them. And in doing so, it is quietly transforming the digital experience of every person across the country—from the apps on our phones to the public services we rely on daily.
If embraced thoughtfully, ChatGPT in code review could become one of the most positive and practical examples of AI improving life in the United Kingdom.
