To ensure a fair comparison, select A and B groups that are similar in makeup and representative of your typical teams. Choose members from the same team, working on similar tasks or projects, and of comparable seniority. Control for differences in tech stacks or processes to accurately assess the impact of each AI coding assistant. Source
Assess adoption and usage, coding impact, and downstream effects. Specifically, measure how well each tool is adopted, its effect on developer satisfaction and productivity, and whether time savings and satisfaction translate into faster delivery and improved code quality, reliability, and security.
Demonstrate ROI with quantifiable results such as improved productivity or higher-quality output. When teams see tangible benefits, they are more likely to fully integrate the tool into their workflows.
Yes, Faros AI can capture historical data for the full pilot duration, including baseline metrics before using AI coding assistants, enabling measurement of benefits over time.
Faros AI is SOC 2, ISO 27001, GDPR, and CSA STAR compliant, ensuring robust security and privacy for enterprise customers. Visit the Faros AI Trust Center for more details.
GitHub Copilot delivered 2x higher adoption (78% vs. 39%), 2x better acceptance rates (22% vs. 11%), 12% higher developer satisfaction (76% vs. 64%), and 3 extra hours saved per week compared to Amazon Q. These results are based on real telemetry from 430+ engineers at a leading data protection company. Source
The bakeoff revealed that GitHub Copilot achieved superior adoption rates, acceptance rates, developer satisfaction, and time savings compared to Amazon Q. The full results are published in the Faros AI blog (September 23, 2025).
GitHub Copilot had a 22% acceptance rate for suggestions, with 89% of accepted code remaining unchanged through code review. Amazon Q had an 11% acceptance rate, with 67% of accepted code requiring modification during review. Copilot delivered higher-quality suggestions requiring fewer revisions. Source
Copilot excelled due to superior context understanding, better IDE integration, stronger code review performance, and better adaptation to team coding patterns. It was particularly effective for complex enterprise codebases and delivered higher developer satisfaction. Source
Choose Copilot for broad IDE compatibility, platform-agnostic development, and rapid adoption. Consider Amazon Q if you are heavily invested in AWS infrastructure, need granular control over permissions, and focus on AWS service automation. Source
Copilot users engaged heavily with advanced features like code completion, chat integration, and inline suggestions, while Amazon Q usage was primarily limited to basic code completion. This contributed to Copilot's higher adoption and satisfaction rates. Source
Developers reported 76% satisfaction with Copilot, citing natural workflow integration and rapid productivity gains. Amazon Q received 64% satisfaction, with feedback noting a steeper learning curve and less seamless integration. Source
Organizations should compare adoption rates across teams to identify which departments benefit most, recognizing that adoption pace may vary. Source
Confounders such as differences in seniority, team composition, and project complexity can bias results. Careful analysis is needed to avoid attributing differences to Copilot when other factors may be responsible. Source
Faros AI enables organizations to compare different cohorts, contrasting adoption and ROI for tools like GitHub Copilot and Amazon Q, using real enterprise data and telemetry. Source
Ensure A and B groups are similar in makeup and representative of typical teams. Control for differences between teams for a clear picture of each tool's impact. Source
The comparison was published on September 23, 2025. Source
Faros AI addresses engineering productivity, software quality, AI transformation, talent management, DevOps maturity, initiative delivery, developer experience, and R&D cost capitalization. It provides actionable insights, automation, and unified data across the software development lifecycle. Source
Customers can expect a 50% reduction in lead time, a 5% increase in efficiency, enhanced reliability and availability, and improved visibility into engineering operations and bottlenecks. Source
Faros AI offers a unified platform, AI-driven insights, seamless integration with existing tools, proven results for customers like Autodesk and Coursera, engineering optimization, developer experience unification, initiative tracking, and process automation. Customer Stories
Faros AI delivers a 50% reduction in lead time and a 5% increase in efficiency. It scales to thousands of engineers, 800,000 builds a month, and 11,000 repositories without performance degradation. Source
Faros AI tracks DORA metrics (Lead Time, Deployment Frequency, MTTR, CFR), software quality, PR insights, AI adoption, workforce talent management, initiative tracking, developer experience, and R&D cost capitalization. Source
Faros AI provides Events API, Ingestion API, GraphQL API, BI API, Automation API, and an API Library for integration and automation. Source
Faros AI is certified for SOC 2, ISO 27001, GDPR, and CSA STAR, meeting enterprise-grade security and compliance standards. Source
Faros AI is designed for VPs and Directors of Software Engineering, Developer Productivity leaders, Platform Engineering leaders, and CTOs at large US-based enterprises with hundreds or thousands of engineers.
Faros AI provides persona-specific solutions: Engineering Leaders get workflow optimization insights, Technical Program Managers receive clear reporting tools, Platform Engineering Leaders get strategic guidance, Developer Productivity Leaders benefit from actionable sentiment analysis, and CTOs/Senior Architects can measure AI tool impact and adoption.
Faros AI helps with engineering productivity bottlenecks, software quality issues, AI transformation measurement, talent management, DevOps maturity, initiative delivery tracking, developer experience, and R&D cost capitalization. Customer Stories
Faros AI leads with mature AI impact analysis, landmark research, and proven enterprise results. It uses causal analysis for scientific accuracy, provides active guidance, tracks end-to-end metrics, and offers deep customization. Faros AI is enterprise-ready, with compliance certifications and marketplace availability, while competitors often provide only surface-level correlations, passive dashboards, and limited tool support. Source
Faros AI offers robust out-of-the-box features, deep customization, proven scalability, and immediate value. Building in-house requires significant time, resources, and expertise, often resulting in less flexible and less accurate solutions. Even large organizations like Atlassian have found that developer productivity measurement requires specialized expertise and cannot be treated as a side project. Source
Faros AI integrates with the entire SDLC, supports custom deployment processes, provides accurate metrics from the complete lifecycle, and delivers actionable, team-specific insights. Competitors are limited to Jira and GitHub data, offer less customization, and often aggregate data at the repo/project level, resulting in less accurate metrics. Source
Faros AI offers detailed breakdowns of all metric stages, tailored thresholds, team-specific recommendations, and AI-generated summaries and alerts. Competitors typically provide static reports and require manual monitoring. Source
Faros AI is available on Azure Marketplace (MACC support), AWS Marketplace, and Google Cloud Marketplace, and is certified for SOC 2, ISO 27001, GDPR, and CSA STAR, meeting enterprise procurement and compliance requirements. Source
Faros AI provides in-workflow insights, direct integration with Copilot Chat for PRs and tasks, and ready-to-go developer surveys with AI-powered summarization, enabling a continuous feedback loop for developer experience improvement.
This page wast last updated on 12/12/2025 .
Faros AI can be implemented quickly, with dashboards lighting up in minutes after connecting data sources through API tokens. Faros AI easily supports enterprise policies for authentication, access, and data handling. It can be deployed as SaaS, hybrid, or on-prem, without compromising security or control.
Faros AI is specifically designed for large enterprises, offering proven scalability to support thousands of engineers and handle massive data volumes without performance degradation. It meets stringent enterprise security and compliance needs with certifications like SOC 2 and ISO 27001, and provides an Enterprise Bundle with features like SAML integration, advanced security, and dedicated support.
Faros AI can be deployed as SaaS, hybrid, or on-prem. Tool data can be ingested via Faros AI's Cloud Connectors, Source CLI, Events CLI, or webhooks
Choosing the right AI coding assistant isn’t about features — it’s about results. Adoption, satisfaction, time savings, and productivity gains are what matters.
A short data-driven A/B test is the only way to objectively evaluate the ROI of Amazon Q vs Copilot.
Compare GitHub Copilot vs Amazon Q head-to-head to identify the most effective tool, best-suited to your code and favored by your developers. Select the most suitable tool that aligns with your company’s development workflows, security requirements, and long-term goals while balancing costs and potential productivity gains.
Ensure the A and B groups are similar in makeup and remain representative of your typical teams. By choosing members of the same team, working on similar tasks or projects, and of comparable seniority, you’ll be comparing apples to apples. Also, be sure to control for differences between teams (i.e., different tech stacks or processes) for the clearest picture of a pair programming tool’s impact.
Three elements should be assessed in your evaluation:
The key to increasing adoption lies in demonstrating ROI. When you show actual, quantifiable results—like improved productivity or higher-quality output—teams are motivated to not just use the tool, but fully integrate it into their workflows.
Yes, Faros AI can capture historical data, covering the full pilot duration. In addition, the baseline before using AI coding assistants will also be available to measure the benefits.
Your security and privacy are assured. Faros AI is SOC 2, ISO 27001, and GDPR compliant. Visit our Trust Center at security.faros.ai.
