[{"data":1,"prerenderedAt":535},["ShallowReactive",2],{"/en-us/the-source/authors/george-kichukov/":3,"footer-en-us":33,"the-source-navigation-en-us":341,"the-source-newsletter-en-us":368,"george-kichukov-articles-list-authors-en-us":380,"george-kichukov-articles-list-en-us":411,"george-kichukov-page-categories-en-us":534},{"_path":4,"_dir":5,"_draft":6,"_partial":6,"_locale":7,"config":8,"seo":10,"content":12,"type":25,"slug":26,"_id":27,"_type":28,"title":11,"_source":29,"_file":30,"_stem":31,"_extension":32},"/en-us/the-source/authors/george-kichukov","authors",false,"",{"layout":9},"the-source",{"title":11},"George Kichukov",[13,23],{"componentName":14,"type":14,"componentContent":15},"TheSourceAuthorHero",{"config":16,"name":11,"role":18,"bio":19,"headshot":20},{"gitlabHandle":17},"gkichukov","Field CTO","George Kichukov brings over two decades of expertise in software development, enterprise architecture, and technology leadership to his role as Financial Services Field CTO for GitLab. His career began in the startup ecosystem, where he spent five years developing name-matching technologies deployed across government, defense, and financial services. George transitioned into solution architecture, where he guided financial institutions in modernizing their application development practices. Prior to GitLab, George spent 12 years at a large financial services organization leading developer services, application security programs and DevOps infrastructure automation platforms. In his current role at GitLab, George partners with financial services organizations, helping them achieve their strategic objectives in DevOps, DevSecOps, Developer Experience, SDLC compliance, and using AI across software development.",{"altText":11,"config":21},{"src":22},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1751463366/dk2knfancgsxocjkmyoa.jpg",{"componentName":24,"type":24},"TheSourceArticlesList","author","george-kichukov","content:en-us:the-source:authors:george-kichukov.yml","yaml","content","en-us/the-source/authors/george-kichukov.yml","en-us/the-source/authors/george-kichukov","yml",{"_path":34,"_dir":35,"_draft":6,"_partial":6,"_locale":7,"data":36,"_id":337,"_type":28,"title":338,"_source":29,"_file":339,"_stem":340,"_extension":32},"/shared/en-us/main-footer","en-us",{"text":37,"source":38,"edit":44,"contribute":49,"config":54,"items":59,"minimal":329},"Git is a trademark of Software Freedom Conservancy and our use of 'GitLab' is under 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newsletter.",{"config":374},{"formId":375,"formName":376,"hideRequiredLabel":328},1077,"thesourcenewsletter","content:shared:en-us:the-source:newsletter.yml","shared/en-us/the-source/newsletter.yml","shared/en-us/the-source/newsletter",{"amanda-rueda":381,"andre-michael-braun":382,"andrew-haschka":383,"ayoub-fandi":384,"bob-stevens":385,"brian-wald":386,"bryan-ross":387,"chandler-gibbons":388,"dave-steer":389,"ddesanto":390,"derek-debellis":391,"emilio-salvador":392,"erika-feldman":393,"george-kichukov":11,"gitlab":394,"grant-hickman":395,"haim-snir":396,"iganbaruch":397,"jlongo":398,"joel-krooswyk":399,"josh-lemos":400,"julie-griffin":401,"kristina-weis":402,"lee-faus":403,"ncregan":404,"rschulman":405,"sabrina-farmer":406,"sandra-gittlen":407,"sharon-gaudin":408,"stephen-walters":409,"taylor-mccaslin":410},"Amanda Rueda","Andre Michael Braun","Andrew Haschka","Ayoub Fandi","Bob Stevens","Brian Wald","Bryan Ross","Chandler Gibbons","Dave Steer","David DeSanto","Derek DeBellis","Emilio 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McCaslin",{"allArticles":412,"visibleArticles":533,"showAllBtn":328},[413,457,498],{"_path":414,"_dir":415,"_draft":6,"_partial":6,"_locale":7,"config":416,"seo":420,"content":425,"type":452,"slug":453,"category":415,"_id":454,"_type":28,"title":421,"_source":29,"_file":455,"_stem":456,"_extension":32,"date":426,"description":422,"timeToRead":427,"heroImage":423,"keyTakeaways":428,"articleBody":432,"faq":433},"/en-us/the-source/ai/how-the-insurance-industrys-data-rich-ecosystem-powers-ai-success","ai",{"layout":9,"template":417,"articleType":418,"author":26,"featured":6,"gatedAsset":419,"isHighlighted":6,"authorName":11},"TheSourceArticle","Regular","source-lp-ai-guide-for-enterprise-leaders-building-the-right-approach",{"title":421,"description":422,"ogImage":423,"config":424},"How the insurance industry's data-rich ecosystem powers AI success","Learn how insurers can build successful AI foundations that turn legacy challenges into operational efficiency and enhanced customer experiences.","https://res.cloudinary.com/about-gitlab-com/image/upload/v1751463750/s7wlgtnijdqmlqrsjwx7.png",{"ignoreTitleCharLimit":328},{"title":421,"date":426,"description":422,"timeToRead":427,"heroImage":423,"keyTakeaways":428,"articleBody":432,"faq":433},"2025-04-24","3 min read",[429,430,431],"Insurance companies face unique challenges with AI implementation due to complex system landscapes, strict regulatory requirements, and data silos. Successful adopters take a domain- and use case-specific approach.","When implemented effectively, AI delivers transformative benefits across the insurance value chain: operational efficiency, accelerated innovation in product development, and enhanced personalized customer experiences.","Successful AI implementation requires more than technology — it demands process simplification, strategic system consolidation, and embedded compliance controls to bridge complex workflows with modern customer expectations.","Insurance companies have an incredible opportunity for AI transformation. Few industries combine such extensive repositories of customer data, complex actuarial models, intricate claims workflows, and stringent regulatory requirements. This unique combination creates the perfect environment for intelligent automation and advanced decision-support systems.\n\nThe most successful insurance transformations I have witnessed share a common catalyst: the strategic implementation of AI built on a strong foundation. This approach revolutionizes how industry leaders bridge complex technology ecosystems with evolving customer expectations.\n\nWhen implemented effectively, AI delivers [transformative benefits](https://about.gitlab.com/the-source/ai/reducing-software-development-complexity-with-ai/) across the insurance value chain:\n- **Operational efficiency**: Automating complex underwriting decisions that traditionally required multiple manual reviews, and significantly reducing claims processing times through intelligent document analysis and automatic fraud detection\n- **Accelerated innovation**: Enabling insurance products with real-time risk modeling, and developing usage-based policies that adjust premiums dynamically based on behavioral data\n- **Enhanced customer experiences**: Transforming high-friction moments like FNOL (First Notice of Loss) into seamless digital experiences with predictive damage assessment and transparent claims tracking\n\nPerhaps most critically, AI can bridge the gap between legacy systems and modern cloud-native applications, preserving valuable business logic while enabling future innovation.\n\n## Where most insurers stumble\nDespite these benefits, implementing AI in insurance operations isn't straightforward. The primary obstacle isn't the technology but the fragmented technology ecosystem within which it must operate.\n\nContext fragmentation is particularly severe in the insurance industry, where critical data is typically stored across more than ten different systems, ranging from legacy policy administration platforms to modern CRM systems, rating engines, claims management software, and third-party data providers.\n\nProcess complexity compounds this challenge. Consider a typical policy renewal workflow that involves quoting systems, underwriting platforms, document management tools, payment processors, and customer communications systems. Each transition between these systems represents a potential point of failure or loss of context, making it impossible for AI to deliver on its promise.\n\nThe heavily regulated nature of insurance adds yet another layer of complexity. Strict requirements around [data privacy](https://content.naic.org/insurance-topics/data-privacy-and-insurance), model explainability, and [anti-discrimination laws](https://consumerfed.org/press_release/important-insurance-anti-discrimination-bill-becomes-law/) governing insurance rating factors all impact how [organizations can deploy AI](https://content.naic.org/insurance-topics/artificial-intelligence). Meanwhile, many insurers continue to operate with legacy systems that are decades old, creating significant barriers to data integration and the implementation of modern AI.\n\n## Addressing the fundamentals\nThe path to successful AI implementation is not solely in deploying new technology. It requires strengthening fundamental elements throughout the organization. Let’s take software development as an example, highlighting a domain-centric strategy:\n\n### Unified platform approach\n[Tool consolidation throughout the software development lifecycle](https://about.gitlab.com/the-source/platform/from-toolchain-chaos-to-business-roi-a-5-step-roadmap/) creates an ideal environment for AI implementation in insurance. When technology and business teams collaborate on a unified platform, AI assistants can access code, requirements, security scanning, software build, environment deployment, and testing data across traditionally siloed tools. This cross-functional visibility enables models to benefit from additional context, which isn’t possible in fragmented environments. In addition, security and release teams can benefit from [AI-powered vulnerability explanation and remediation](https://about.gitlab.com/the-source/ai/understand-and-resolve-vulnerabilities-with-ai-powered-gitlab-duo/), and root cause analysis, all within the same interface.\n\n### Common data foundation\nA common data model is the critical backbone for effective AI. In addition to standardizing processes, insurance carriers must unify how data is structured, stored, and accessed across policy administration, claims, and customer systems. This consolidated data foundation enables AI tools to work with consistent information, providing meaningful insights at every stage of the software development lifecycle, from requirements gathering through deployment and monitoring. When [all applications share standardized data definitions and relationships](https://about.gitlab.com/blog/gitlab-duo-workflow-enterprise-visibility-and-control-for-agentic-ai/), AI can make connections across traditionally siloed systems, identify patterns, and deliver analytics that would be impossible with fragmented data architectures. This approach ensures that AI enhancements aren't just technical novelties, but deliver measurable business value while maintaining regulatory compliance.\n\n### Guardrails through collaboration\nThe collaborative aspects of modern software delivery provide natural insertion points for controls and [guardrails across the software development pipeline](https://about.gitlab.com/the-source/ai/4-ways-ai-can-help-devops-teams-improve-security/). When enforcing manual or AI-supported review processes, such as code review, AI tools can supplement human expertise by automatically validating that code changes conform to technical standards. From requirements gathering to deployment, these guardrails verify that workflows maintain required separation of duties - all while accelerating the development process rather than creating bottlenecks. This collaborative approach ensures AI becomes a trusted partner in each development phase while maintaining the human oversight essential in regulated environments.\n\nAs you embark on your AI journey, ensure you address these fundamentals alongside your technology implementation. Insurance carriers that approach AI strategically, focusing on specific high-value domains while simultaneously strengthening their operational foundations, will realize the greatest competitive advantages in the years ahead.",[434,437,440,443,446,449],{"header":435,"content":436},"Why is the insurance industry well-suited for AI transformation? ","The insurance industry combines vast amounts of structured data, complex workflows, actuarial modeling, and strict regulatory requirements, making it an ideal environment for AI to drive operational efficiency, decision support, and customer experience enhancements.",{"header":438,"content":439},"What are the main challenges insurers face when implementing AI? ","Insurers often struggle with fragmented systems, disconnected workflows, legacy technologies, and strict compliance requirements that make it difficult to integrate AI effectively across the value chain.",{"header":441,"content":442},"How can a unified platform approach improve AI outcomes in insurance?","A unified platform consolidates tools across the development lifecycle, giving AI systems the full context they need to analyze code, monitor workflows, identify vulnerabilities, and suggest improvements without silo-induced blind spots.",{"header":444,"content":445},"Why is a common data foundation important for AI in insurance? ","A standardized data model ensures AI tools can access consistent, clean data across systems like policy admin, claims, and CRM, enabling pattern recognition, analytics, and compliance without being hindered by fragmented data architectures.",{"header":447,"content":448},"How do AI guardrails enhance trust and compliance in insurance development?","Guardrails built into collaborative software development workflows help ensure that AI tools validate code changes, enforce security and compliance standards, and support human oversight, crucial in regulated environments like insurance.",{"header":450,"content":451},"What’s the most effective strategy for adopting AI in insurance? ","Successful insurers focus on high-value, domain-specific AI applications while modernizing foundational systems and processes, enabling scalable innovation and measurable business value without compromising compliance or stability.","article","how-the-insurance-industrys-data-rich-ecosystem-powers-ai-success","content:en-us:the-source:ai:how-the-insurance-industrys-data-rich-ecosystem-powers-ai-success:index.yml","en-us/the-source/ai/how-the-insurance-industrys-data-rich-ecosystem-powers-ai-success/index.yml","en-us/the-source/ai/how-the-insurance-industrys-data-rich-ecosystem-powers-ai-success/index",{"_path":458,"_dir":459,"_draft":6,"_partial":6,"_locale":7,"config":460,"seo":462,"content":467,"type":452,"slug":494,"category":459,"_id":495,"_type":28,"title":463,"_source":29,"_file":496,"_stem":497,"_extension":32,"date":468,"description":464,"timeToRead":469,"heroImage":465,"keyTakeaways":470,"articleBody":474,"faq":475},"/en-us/the-source/platform/3-steps-to-modernizing-software-delivery-in-financial-services","platform",{"layout":9,"template":417,"articleType":418,"author":26,"featured":328,"gatedAsset":461,"isHighlighted":6,"authorName":11},"source-lp-whats-next-in-devsecops-for-financial-services",{"title":463,"description":464,"ogImage":465,"config":466},"3 steps to modernizing software delivery in financial services","Discover why financial institutions must modernize their software delivery to maintain a competitive advantage in today’s rapidly evolving market.","https://res.cloudinary.com/about-gitlab-com/image/upload/v1751464105/b0sltyrnkzt8yzgikqgl.jpg",{"ignoreTitleCharLimit":328},{"title":463,"date":468,"description":464,"timeToRead":469,"heroImage":465,"keyTakeaways":470,"articleBody":474,"faq":475},"2025-03-25","5 min read",[471,472,473],"Traditional DevSecOps implementations in financial services face critical gaps that reduce speed and increase risk: manual governance, limited visibility, fragmented developer experience, and integration complexity.","Modern integrated platforms deliver measurable business impact and strategic advantages in the form of agility, efficiency, and talent retention.","Begin your DevSecOps transformation journey with three strategic steps: assess current capabilities, define the target architecture, and create an implementation roadmap to unlock innovation, security, and efficiency.","Through my 20 years of experience in financial services, most recently at Citi and now as Financial Services Field CTO at GitLab, I’ve gained a unique perspective on software delivery in the industry. My conversations with leaders at global financial services organizations reveal a consistent truth: software is a critical driver of competitive differentiation. However, mature software delivery practices and integrated developer experience are still an elusive goal.\n\nThis comes against the backdrop of rapid change in financial services, driven by intense competition from digital-first players who can deploy new features and products at remarkable speed. Meanwhile, many established organizations struggle with disconnected tools, manual processes, and poor developer experience - obstacles that organizations can no longer ignore.\n\nThe most forward-thinking financial institutions see software delivery - and DevSecOps - as a core business capability that directly affects their market position. However, to realize the full benefits of DevSecOps, organizations need to move from disconnected tools to integrated platforms that seamlessly unite teams and processes as customer demands evolve and digital transformation accelerates.\n\n## The implementation gap in financial services\nDespite significant investments in DevSecOps, I’ve observed a clear gap between promise and reality at many banks and financial services providers:\n- **Manual governance**: Security and compliance validation still involves significant manual processes, creating bottlenecks.\n- **Limited visibility**: Decision makers lack comprehensive insight into the software development lifecycle, making identifying constraints and optimizing processes difficult.\n- **Fragmented developer experience**: Developers must navigate a complex maze of disconnected tools that hamper productivity and innovation.\n- **Integration complexity**: DevSecOps implementations that rely on dozens of tools cobbled together with custom integrations result in less efficient development processes.\n\nThese challenges reflect the limitations of tools available when institutions began their DevSecOps journeys. The best way for organizations to catch up is to adopt a single DevSecOps platform, bringing built-in security, compliance controls, and end-to-end metrics into a unified developer experience.\n\n## The modern platform advantage\n[Modern DevSecOps platforms](https://about.gitlab.com/platform/) provide a comprehensive approach to software delivery that further advances traditional implementations. The core advantages can be seen in three critical areas:\n\n**Integrated security and compliance**: Unified platforms embed security directly into delivery infrastructure through automated policy enforcement. Teams benefit from [real-time vulnerability detection during development rather than after release](https://about.gitlab.com/the-source/security/strengthen-your-cybersecurity-strategy-with-secure-by-design/). Continuous compliance validation eliminates manual steps and helps to ensure supply chain security, reducing risk across the organization.\n\n**Unified developer experience**: Where developers once navigated disconnected tools, modern platforms provide consistent interfaces that [minimize context switching](https://about.gitlab.com/the-source/ai/devops-leaders-fix-this-productivity-blocker-before-adding-ai/). Self-service capabilities eliminate provisioning delays, while standardized workflows enforce best practices by default, improving quality and consistency.\n\n**Comprehensive operational intelligence**: End-to-end metrics connect technical activities to business outcomes, and predictive analytics identify potential issues before they impact customers. Modern platforms also automate compliance reporting - eliminating tedious manual documentation - and provide [value stream visualization](https://about.gitlab.com/the-source/platform/optimize-value-stream-efficiency-to-do-more-with-less-faster/) to help teams quickly identify and resolve bottlenecks.\n\n## The results: Measurable business impact\nFor financial services providers, the benefits of modernizing software delivery platforms extend far beyond technical improvements. According to [Forrester's Total Economic Impact study of GitLab Ultimate](https://about.gitlab.com/resources/study-forrester-tei-gitlab-ultimate/), a composite organization representative of interviewed customers with experience using GitLab Ultimate achieved:\n- 483% ROI over three years\n- 50% more feature deliveries\n- 75% faster developer onboarding\n- 535 hours saved per developer annually\n\nBeyond operational metrics, modernization also creates strategic advantages, such as:\n- **Innovation velocity**: Financial institutions with modernized delivery platforms can [rapidly develop and launch](https://about.gitlab.com/customers/goldman-sachs/) customer-centric features, significantly reducing time-to-market and enabling personalized experiences.\n- **Talent retention**: Leading financial institutions report [47% higher retention rates for technical talent](https://www.mckinsey.com/~/media/mckinsey/industries/technology%20media%20and%20telecommunications/high%20tech/our%20insights/developer%20velocity%20how%20software%20excellence%20fuels%20business%20performance/developer-velocity-how-software-excellence-fuels-business-performance-v4.pdf?shouldIndex=false) after modernizing their delivery platforms.\n- **Regulatory agility**: Financial services institutions with modern delivery platforms [adapt to regulatory changes faster than those with legacy approaches](https://www.mckinsey.com/industries/financial-services/our-insights/unlocking-value-from-technology-in-banking-an-investor-lens), transforming compliance from a burden to a potential advantage.\n- **More efficient mergers and acquisitions**: Modern platforms reduce technology integration timelines, [significantly increasing the success rate of acquisitions and partnerships](https://www.deloitte.com/uk/en/services/financial-advisory/perspectives/realising-deal-value-through-digital-transformation.html).\n- **Geographic expansion**: Standardized delivery capabilities [enable faster adaptation of core digital services to local requirements without compromising global standards](https://aws.amazon.com/isv/resources/why-software-companies-must-prioritize-international-expansion/).\n\nEach of these outcomes directly contributes to shareholder value and competitive positioning.\n\n## Taking action: The path forward\nFor those setting the strategy, the path to modernizing software delivery requires strategic vision and pragmatic execution. Here are three steps you can take to begin your transformation journey:\n\n### Assess current state and build organizational alignment\nBegin with an objective assessment of your current delivery capabilities and develop a comprehensive vision for where you need to go:\n- Map existing tools and workflows across the entire software development lifecycle\n- Identify integration gaps and manual handoffs that create bottlenecks\n- Measure current performance using industry-standard metrics\n- Establish security and compliance requirements for automated enforcement\n\n### Define the target architecture\nDevelop a comprehensive vision for modern software delivery that addresses your specific needs:\n- Design a unified platform strategy that eliminates fragmentation\n- Establish security and compliance requirements for automated enforcement\n- Define role-based experiences for developers, operators, and business stakeholders\n- Create clear governance models that balance innovation with control\n- Set measurable performance targets aligned with business objectives\n- Establish executive sponsors and organizational alignment\n\n### Create an implementation roadmap\nBuild a pragmatic approach to transformation that delivers continuous value:\n- Identify high-impact areas for initial implementation\n- Design a phased approach with clear milestones\n- Develop evolution strategies for existing applications and workloads\n- Define success metrics for each phase\n- Create feedback mechanisms to refine the approach based on results\n\n## The natural evolution of your DevSecOps journey\nToday’s tools offer capabilities that simply didn’t exist five years ago, directly addressing the financial services sector’s most pressing challenges. Modern DevSecOps tools enable secure software releases while providing the agility to meet evolving market demands.\n\nSuccessful financial services firms approach this as an evolution of targeted enhancements that compound over time, building on existing foundations to unlock new possibilities for innovation, application security, and efficiency.\n\nThe next phase of your DevSecOps journey starts now.",[476,479,482,485,488,491],{"header":477,"content":478},"Why is modernizing software delivery essential for financial services organizations?","In a fast-evolving market, financial institutions must compete with digital-native companies that deploy updates rapidly. Modernizing software delivery allows traditional firms to accelerate product innovation, improve security, and enhance compliance agility, all of which are essential to maintaining a competitive edge.",{"header":480,"content":481},"What are the primary obstacles financial institutions face in DevSecOps adoption?","Common challenges include fragmented toolchains, manual compliance processes, limited visibility into development pipelines, and a disjointed developer experience. These issues slow down delivery cycles and reduce the impact of DevSecOps initiatives.",{"header":483,"content":484},"How does a unified DevSecOps platform improve the developer experience?","By replacing disconnected tools with an integrated platform, developers benefit from streamlined workflows, reduced context switching, and self-service capabilities. This improves productivity, fosters innovation, and contributes to better job satisfaction and retention.",{"header":486,"content":487},"Can modern DevSecOps platforms support regulatory compliance?","Yes. Automated compliance checks and real-time reporting allow institutions to embed policy enforcement into daily workflows. This transforms compliance from a reactive burden into a continuous, auditable process that aligns with regulatory expectations.",{"header":489,"content":490},"What kind of business impact can financial institutions expect from DevSecOps modernization?","Modernizing software delivery has measurable effects, including faster onboarding, greater development output, and higher ROI. Strategic advantages like increased innovation velocity, improved acquisition efficiency, and better global scalability also contribute to long-term value.",{"header":492,"content":493},"How should financial institutions begin the modernization journey?","The first step is to assess current software delivery capabilities and identify key pain points. From there, organizations can design a unified platform strategy and implement it in phases, focusing on continuous improvement and alignment with business goals.","3-steps-to-modernizing-software-delivery-in-financial-services","content:en-us:the-source:platform:3-steps-to-modernizing-software-delivery-in-financial-services:index.yml","en-us/the-source/platform/3-steps-to-modernizing-software-delivery-in-financial-services/index.yml","en-us/the-source/platform/3-steps-to-modernizing-software-delivery-in-financial-services/index",{"_path":499,"_dir":459,"_draft":6,"_partial":6,"_locale":7,"config":500,"seo":502,"content":506,"type":452,"slug":529,"category":459,"_id":530,"_type":28,"title":503,"_source":29,"_file":531,"_stem":532,"_extension":32,"date":507,"description":504,"timeToRead":469,"heroImage":505,"keyTakeaways":508,"articleBody":512,"faq":513},"/en-us/the-source/platform/how-to-accelerate-developer-onboarding-and-why-it-matters",{"layout":9,"template":417,"articleType":418,"author":26,"featured":6,"gatedAsset":501,"isHighlighted":6,"authorName":11},"source-lp-getting-started-with-ai-in-software-development-a-guide-for-leaders",{"title":503,"description":504,"ogImage":505},"How to accelerate developer onboarding (and why it matters)","Overcome common onboarding challenges, get to productivity faster, and drive long-term retention with these proven strategies.","https://res.cloudinary.com/about-gitlab-com/image/upload/v1751464587/ozatfyk9hr3hwl1ssfxv.png",{"title":503,"date":507,"description":504,"timeToRead":469,"heroImage":505,"keyTakeaways":508,"articleBody":512,"faq":513},"2025-01-30",[509,510,511],"Poor developer onboarding can lead to poor performance, disengagement, and low retention, so cutting corners when welcoming new employees is simply not a path leaders can afford to take.","Accelerating onboarding time takes a multifaceted approach that requires communication with your teams, assessing your current tools and processes, and an open mind for change.","Integrating AI, using built-in documentation, taking advantage of standardized environments, and using a single platform to centralize your workflows are just a few strategies that can help simplify the onboarding process.","You've hired a new developer for a crucial role on your team. You'd likely prefer not to wait months for that person to become productive - but [GitLab research](https://about.gitlab.com/developer-survey/) shows this is precisely the situation many leaders face today. Nearly half (44%) of organizations say onboarding new developers takes more than two months.\n\nOf course, getting a new developer up to speed requires more than just providing credentials.  They’ll need to learn about project goals, processes, how your applications integrate, and your collaboration culture.\n\nCutting corners with onboarding can negatively impact your business across the board. It can lead to poor performance, disengagement, and low retention - which means you'll have to start the whole process all over again.\n\nSo, how can leaders get it right the first time?\n\n## Why developer onboarding takes so long: A closer look\n### Setup time\nWhen a developer arrives on their first day, there’s a lot they’ll need to learn. Setup can include some or all of these processes:\n\n- Installing and configuring development environments\n- Getting user access to server-side tools, like version control, issue tracking, CI/CD, and security tools\n- Getting user access to relevant deployment targets and infrastructure resources, including dev, test, and production\n- Taking time to understand project goals, architecture, conventions, processes, and team culture\n\nDeveloper onboarding time is often called “time to first commit” - how quickly a developer can get up and running and start contributing valuable work. So, what are some of the reasons it’s taking more time for developers to get to their first commit?\n\n### Process and systems hurdles\nFrom setting up an ever-growing number of tools to training, developer onboarding can waste significant time and resources, reducing your team’s productivity and output. What’s more, there are a lot of organization- and team-wide inefficiencies that can make this process even slower. If you’re looking to improve your onboarding time, these are the hurdles that may be standing in your way:\n\n- Too many tools to learn\n- Complex or difficult-to-follow processes\n- Limited visibility into applications and environments\n- Poor documentation of onboarding processes\n- Difficult-to-locate (or nonexistent) application documentation\n- Difficult-to-access deployment environments\n\nThese challenges can slow any team down and be especially problematic when ramping up a new employee.\n\n## The hidden costs of poor developer onboarding\nThe ripple effects of slow onboarding are often overlooked. Take security, for example. CISOs need to ensure new developers understand and can apply the organization’s security standards to their work so they don’t inadvertently release applications with vulnerabilities. Do these new hires know all the regulations? The ins and outs of your organization’s licensing? You’ll want to ensure your organization avoids any cybersecurity breach - even if it’s accidental.\n\nThis impact extends beyond technical concerns. According to _[Forbes](https://www.forbes.com/councils/forbesbusinesscouncil/2022/08/25/how-to-get-the-most-out-of-your-onboarding-process/#:~:text=The%20success%20and%20efficiency%20of,increased%20productivity%20and%20decreased%20turnover.)_, efficient onboarding directly influences a company’s growth and long-term viability through employee engagement, increased productivity, and decreased turnover. And the stakes are significant: [Gallup’s State of the Global Workplace: 2024 report estimates](https://www.gallup.com/workplace/349484/state-of-the-global-workplace.aspx?thank-you-report-form=1) that low employee engagement costs the global economy US$8.9 trillion, or 9% of global GDP.\n\nPoor onboarding doesn’t just delay productivity - it creates organizational vulnerabilities that can last long after a developer’s first commit.\n\n## How to accelerate onboarding\nImproving onboarding time takes a multifaceted approach that requires communication with your teams, assessing your tools and processes, and an open mind for change. While the initial time it takes to address these challenges might slow you down momentarily, the return of acceleration - the better retention, developer experience, productivity, and innovative ideas - will be worth it.\n\nHere’s where to start:\n\n### Identify the bottlenecks\nMany of the challenges mentioned above arise from complexities in tools and processes, so the first thing you’ll need to do is find them. Where are the bottlenecks? Meet with your team to ask where they’re feeling the pressure, or conduct a survey to understand what’s slowing them down. Consider mapping out the complete value stream from idea to production deployment.\n\n### Find a platform that simplifies your processes\nFinding [one integrated application for the entire software development lifecycle](https://about.gitlab.com/the-source/platform/driving-business-results-with-platform-engineering/) means developers don’t need to learn different user interfaces with different idiosyncrasies and data models. This standardization and tool consolidation significantly simplifies onboarding.\n\n### Adopt organization-level standards\nUsing a standards-based approach to engineering projects is beneficial for onboarding as well as when developers transition between teams and projects. Project and issue templates keep projects consistent, and [CI/CD catalogs](https://about.gitlab.com/blog/ci-cd-catalog-goes-ga-no-more-building-pipelines-from-scratch/) encourage developers to reuse approved and tested components.\n\nMany regulated industries have specific requirements for developer workstations that can make installing or customizing tools difficult. This can be even more challenging for third-party contractors and non-employees. A self-service approach to standardized environment creation and/or access to a pre-configured remote development environment makes it much easier to overcome this issue without compromising your security initiatives.\n\n### Establish quality and security guardrails\nFrom implementing code reviews from code owners to testing in lower dev environments, ensure code produced by new developers is free of issues or vulnerabilities before deploying to production.\n\n### Use built-in documentation\nIt’s easy for documentation to become outdated, especially with Wiki tools, since they’re often disconnected from the projects they support. By including Wiki and static pages as part of your projects - keeping documentation close to your code - you can ensure that team members have easy access to the latest information when needed.\n\n### Facilitate knowledge sharing, cross-team collaboration, and mentoring\nThere are many ways to integrate learning-friendly features into your processes. From code reviews to merge requests, these checkpoints keep your teams collaborating, learning from one another, and shipping high-quality code. Research proves that organizations that foster [psychological safety](https://www.forbes.com/councils/forbesbusinesscouncil/2022/10/12/psychological-safety-building-high-performing-teams/) have better-performing teams, so the more you trust you can build from the beginning, the better output you can expect.\n\n### Use AI\nGitLab research has shown that AI can [speed developer onboarding](https://about.gitlab.com/the-source/platform/3-surprising-findings-from-our-2024-global-devsecops-survey/). If AI can improve productivity and introduce efficiencies across the entire software development lifecycle, it follows that AI can help developers get up to speed faster. **In fact, survey respondents currently using AI for software development (43%) were much more likely than those not using AI (20%) to say that developer onboarding typically takes less than a month.**\n\nHere are just a few ways AI can help you get developers onboarded faster:\n\n- AI assistants can [process a lot of information easily](https://about.gitlab.com/blog/gitlab-duo-chat-now-generally-available/#get-up-to-speed-fast), helping new developers quickly find answers to common questions.\n- AI tools can [summarize long discussions in issues or code reviews](https://about.gitlab.com/blog/supercharge-productivity-with-gitlab-duo/#issue-comment-summary), helping new developers catch up on conversations and decisions that happened before they started.\n- AI can also [explain unfamiliar code snippets in natural language](https://about.gitlab.com/blog/supercharge-productivity-with-gitlab-duo/#code-explanations), helping new developers get used to working with a new code base.\n- AI can troubleshoot and explain errors, identify their root causes, and propose solutions, helping new developers better understand applications and systems.\n\n## Speed is only one piece of the puzzle\nTo build a team that collaborates well and easily welcomes new teammates as they come aboard, you need clear and efficient processes, easy-to-find process and application documentation, and a platform that centralizes your development tools. Put together, this forms a machine that turns ideas into innovative products - and an environment where developers (both new and veteran) will feel like they can do their best work.",[514,517,520,523,526],{"header":515,"content":516},"What steps can teams take to improve long-term retention after onboarding?","Organizations should foster knowledge-sharing through mentoring, cross-team collaboration, and continuous feedback loops. Investing in psychological safety, skill development, and AI-driven efficiency tools ensures developers remain engaged, productive, and committed long after onboarding.",{"header":518,"content":519},"How can organizations streamline developer onboarding without sacrificing security?","Companies can accelerate onboarding by adopting standardized workflows, consolidating tools into a single DevSecOps platform, and automating environment setup. Providing pre-configured access controls and enforcing security guardrails ensures compliance without slowing down productivity.",{"header":521,"content":522},"What are the hidden costs of inefficient developer onboarding?","Slow onboarding leads to reduced productivity, higher turnover rates, and potential security risks. Developers who struggle to get up to speed may become disengaged, increasing the likelihood of attrition. Additionally, without proper security training, new hires may inadvertently introduce vulnerabilities.",{"header":524,"content":525},"How does AI improve the onboarding process for developers?","AI-powered tools can summarize documentation, assist in code reviews, explain unfamiliar code, and troubleshoot errors. This allows new developers to find answers faster, understand project history, and ramp up without constant manual guidance from senior engineers.",{"header":527,"content":528},"Why does developer onboarding take longer than expected in many organizations?","Developer onboarding often takes longer due to complex setup processes, fragmented toolchains, poor documentation, and unclear security protocols. Many new hires struggle to navigate multiple systems, obtain necessary permissions, and understand project architectures before contributing meaningfully.","how-to-accelerate-developer-onboarding-and-why-it-matters","content:en-us:the-source:platform:how-to-accelerate-developer-onboarding-and-why-it-matters:index.yml","en-us/the-source/platform/how-to-accelerate-developer-onboarding-and-why-it-matters/index.yml","en-us/the-source/platform/how-to-accelerate-developer-onboarding-and-why-it-matters/index",[413,457,498],{"ai":354,"platform":361,"security":96},1754424543007]