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Black Duck:2026 AI 赋能软件开发领域现状报告:企业需完善治理体系 释放 AI 真实价值(英文版)(19页).pdf

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1、The State of AI-Powered Software DevelopmentOrganizations Need Governance to Unlock AIs True PotentialContentsExecutive summary .1Key findings .2AI coding assistant adoption drives major productivity gains .3Governance is the key to increased AI ROI .7The future of AI-powered development hinges on s

2、ecurity .10Conclusion:AI impact scales with discipline and governance .13Methodology and demographics .14About Black Duck .15About UserEvidence |1Executive summaryAI adoption alone no longer creates a competitive advantage.Instead,this edge increasingly comes from how development teams operationaliz

3、e AI.Many teams report extensive use of AI coding assistants,resulting in notable improvements in velocity and productivity.Yet a lack of governance and limited visibility lead to an array of bottlenecks further down the software development and review process that largely negate these efficiency ga

4、ins.Currently,AI simply redistributes development work rather than eliminating it altogether.The next phase of AI maturity must therefore focus on scaling,managing,and auditing AI-assisted code.In this report,we explore how organizations can benefit from more deliberate implementation of critical pr

5、ocesses,effective governance,and specialized tooling.Together,these efforts transform pipelines into the greatest force multiplier for a business,building on the efficiency-based foundation that AI coding assistants have established.We partnered with third-party research firm UserEvidence to conduct

6、 an independent market survey of 831 software engineers and development and operations(DevOps)professionals in March 2026.The research sample was vendor-neutral,but neither Black Duck nor UserEvidence customers were excluded from |2Key findingsAI provides major efficiency gains and a full day back p

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1. **AI编码助手普及带来效率提升**:97%开发者使用AI助手,92%团队认为提升了生产力和发布速度,平均每周节省8小时,53%团队代码量增长超25%。 2. **治理缺失抵消效率收益**:90%团队遇到AI代码问题(52%需手动审查,51%安全测试瓶颈),仅30%团队有完整治理,有治理的团队效率提升可能性高55%。 3. **安全担忧与治理需求**:64%团队担忧AI引入安全漏洞,68%开发者呼吁自动化AI代码追踪系统,但仅40%采用自动化标签。 4. **未来依赖安全与人工协同**:56%团队倾向专用AI安全代理评估代码,84%主张保留人工审查,开发者预计未来将更多时间用于代码验证和安全风险管理。
AI如何提效? 治理缺在哪? 安全怎么办?
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