Case study: GitLab

GitLab: The devsecops platform successful the AIGitLab paradox

The shift to Generative AI has created a strong paradox in software program improvement: whereas coding is quicker than ever due to AI assistants, the complexity of managing safety, governance, and compliance throughout fragmented toolchains has created new bottlenecks. Global companies now lose over seven hours per week per group member to those inefficiencies.

GitLab, the great DevSecOps Platform, is tackling this head-on. By unifying all the software program improvement lifecycle (SDLC) right into a single, clever utility powered by AI Agents, GitLab is not only accelerating coding – it is industrializing safe, compliant software program supply.

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What GitLabUK has accomplished for the UK in 2025

The UK’s enterprise and public sectors are grappling with the way to undertake AI whereas assembly strict monetary and regulatory compliance calls for. GitLab’s work in 2025 has been crucial in demonstrating a path ahead, significantly in extremely regulated industries.

Key 2025 milestones within the UK:

1. High-profile enterprise adoption: UK monetary leaders, resembling NatWest, publicly highlighted their deep adoption of GitLab Duo, GitLab’s suite of AI brokers. This demonstrated how a significant financial institution makes use of the platform to combine AI immediately into their code assessment, check era, and compliance workflows – an enormous win for enterprise belief.
2. Unlocking financial worth: GitLab’s personal analysis revealed that AI-enhanced software program innovation has the potential to unlock over £5 billion in annual financial worth throughout the UK by saving builders an estimated £11,000 per yr by way of productiveness positive factors. This knowledge offers an important financial mandate for UK management to spend money on unified DevSecOps platforms.
3. DevSecOps management: For the third consecutive yr, GitLab was named a Leader within the 2025 Gartner Magic Quadrant for DevOps Platforms, emphasizing its built-in method over fragmented toolchains. Critically for the UK’s regulated supply sectors, GitLab ranked #1 in 4 out of six Gartner Critical Capabilities use circumstances, together with Regulated Delivery.

This adoption alerts a significant pattern: UK enterprises are shifting away from managing a sprawl of separate instruments (GitHub for code, Jira for planning, separate instruments for safety) towards a single platform that embeds governance and safety from the primary line of AI-generated code.

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Global deployment technique: Unified platform and brokers

GitLab’s technique is constructed totally round consolidating the fragmented DevSecOps market by way of two core pillars:

• The single platform benefit: Unlike rivals that depend on a number of integrations (e.g., Atlassian’s Jira, Confluence, and Bitbucket stack), GitLab gives a single utility for all the SDLC – from planning, supply code administration, CI/CD, safety, and monitoring. This dramatically reduces integration overhead, context switching, and, crucially, safety gaps.
• Agentic AI orchestration: The core deployment focus in 2025 was the discharge of the GitLab Duo Agent Platform. This strikes AI past easy code completion (like GitHub Copilot) to multi-step, autonomous brokers that act proactively inside the platform’s context. These brokers can routinely triage vulnerabilities, generate full check suites, and carry out compliance checks earlier than code is merged.

This method targets the “AI Paradox,” guaranteeing that the velocity gained from AI code era is not misplaced to friction in safety and deployment pipelines.

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Technical benefits over rivals in 2025

GitLab’s main benefit is its unified knowledge mannequin and AI Agents’ contextual consciousness throughout all the software program improvement lifecycle (SDLC), differentiating it sharply from its essential rivals:

Feature	GitLab (Unified DevSecOps)	GitHub (code-centric)	Atlassian (project-centric)
Core providing	Single, built-in platform for total SDLC (Dev, Sec, Ops).	Primarily a Source Code Management (SCM) and code-hosting platform.	Suite of specialised instruments (Jira for points, Bitbucket for Git).
AI technique	Agentic AI: Duo brokers work throughout planning, safety, and CI/CD with full challenge context.	AI assistant: GitHub Copilot focuses predominantly on code era inside the repository.	AI options are fragmented throughout merchandise (e.g., Jira Product Discovery).
Deployment flexibility	High: Offers SaaS, self-managed, and air-gapped deployments, crucial for regulated and authorities entities.	Primarily SaaS; self-hosting choices are complicated or restricted.	Hybrid, relying closely on integrating a number of instruments.
Built-in safety	Security is native: SAST, DAST, Secret Detection embedded and automatic in each pipeline.	Security typically requires separate, bolted-on instruments or market add-ons.	Distributed throughout Jira and different instruments, growing configuration burden.

GitLab’s dedication to constructing safety and compliance into the code itself utilizing its unified knowledge construction permits it to supply the next stage of automation and danger discount than options that require separate instruments to implement coverage.

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What’s subsequent for GitLab in 2026: Building compliance into code

For 2026, GitLab will deal with conquering the ultimate frontiers of the AI paradox: compliance and full agentic autonomy.

• AI-native compliance: GitLab predicts that by 2027, 82% of compliance might be constructed into code and routinely utilized. GitLab’s roadmap is concentrated on delivering the automated governance options wanted to realize this, permitting builders to scale their use of AI-generated code with out risking catastrophic regulatory failure.
• Agent-to-agent collaboration: The Duo Agent Platform will evolve towards enabling subtle agent-to-agent workflows. Instead of a human asking an agent a query, brokers will collaborate to resolve bugs, generate documentation, and handle safety updates autonomously, with human oversight constructed into the ultimate assessment stage.
• The platform engineering answer: The firm will leverage its management in Platform Engineering – the apply of constructing reusable, inner improvement infrastructure – to offer blueprints that assist enterprises orchestrate complicated AI workflows safely, turning the platform engineering group into the inner provider of AI agility.

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Must-attend: The AI-native enterprise: Moving from pilot to manufacturing

How do you transition from utilizing fragmented AI assistants to constructing a unified, scalable AI-native software program supply course of? GitLab’s professional is coming to Generative AI Summit London to share the architectural and strategic insights wanted to industrialize DevSecOps with AI.

Event Details	Generative AI Summit London
Speaker	Louise Fellows, VP of UK, GitLab
Topic Focus	The AI Paradox: how platform engineering resolves the productiveness vs. governance battle
Date	December 2

Why you need to attend:

This session is essential for engineering executives in regulated industries:

• Solve the AI paradox: Understand the way to reclaim the seven hours per week misplaced to toolchain fragmentation by adopting an built-in platform method, maximizing the ROI of your AI investments.
• Security by design: Learn the way to embed AI governance and safety checks immediately into your CI/CD pipelines utilizing GitLab Duo brokers, guaranteeing compliance is automated reasonably than dealt with as a pricey afterthought.
• Strategic roadmap: Get direct insights into the way forward for Agentic AI and the way to upskill your groups to evolve from builders into platform engineers who orchestrate the AI-native DevSecOps world.

Don’t miss out on the blueprint for safe, high-velocity software program supply within the age of AI. Register for the Generative AI Summit London at this time.