{"id":67670,"date":"2024-02-08T08:48:40","date_gmt":"2024-02-08T05:48:40","guid":{"rendered":"https:\/\/www.altoros.com\/blog\/?p=67670"},"modified":"2024-04-05T09:19:13","modified_gmt":"2024-04-05T06:19:13","slug":"generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to","status":"publish","type":"post","link":"https:\/\/www.altoros.com\/blog\/generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to\/","title":{"rendered":"Generative AI for SDLC: Top Areas for a CTO\/VPE to Pay Attention To"},"content":{"rendered":"<p><center><small>(<a href=\"https:\/\/arxiv.org\/pdf\/2308.04736.pdf\" rel=\"noopener\" target=\"_blank\">Featured image credit<\/a>)<\/small><\/center><\/p>\n<p>&nbsp;<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_79_2 counter-hierarchy ez-toc-counter ez-toc-transparent ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.altoros.com\/blog\/generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to\/#We_still_lack_enough_data_on_AI\" >We still lack enough data on AI<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.altoros.com\/blog\/generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to\/#The_promise_of_AI_for_coding\" >The promise of AI for coding<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.altoros.com\/blog\/generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to\/#Wait_but_what_are_the_real_productivity_gains\" >Wait, but what are the real productivity gains?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.altoros.com\/blog\/generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to\/#Generative_AI_across_SDLC\" >Generative AI across SDLC<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.altoros.com\/blog\/generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to\/#AI_in_DevOps_and_security\" >AI in DevOps and security<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.altoros.com\/blog\/generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to\/#A_developers_view_on_AI\" >A developer\u2019s view on AI<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.altoros.com\/blog\/generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to\/#GenAI_in_QA_and_testing\" >GenAI in QA and testing<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.altoros.com\/blog\/generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to\/#Budgets_vs_ongoing_learning\" >Budgets vs. ongoing learning<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.altoros.com\/blog\/generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to\/#Frequently_asked_questions_FAQ\" >Frequently asked questions (FAQ)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.altoros.com\/blog\/generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to\/#Further_reading\" >Further reading<\/a><\/li><\/ul><\/nav><\/div>\n<h3><span class=\"ez-toc-section\" id=\"We_still_lack_enough_data_on_AI\"><\/span>We still lack enough data on AI<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Since the launch of <a href=\"https:\/\/en.wikipedia.org\/wiki\/ChatGPT\" rel=\"noopener\" target=\"_blank\">ChatGPT<\/a> and code generation tools like <a href=\"https:\/\/docs.github.com\/en\/copilot\" rel=\"noopener\" target=\"_blank\">GitHub Copilot<\/a>, a lot of predictions have been made regarding productivity improvements in software engineering. Some analysts and vendors expect that the AI revolution will cut time on development by 2x, while others believe that engineers might be replaced completely\u2014sooner or later.<\/p>\n<p>Anyway, most reports give readers only a fragmented view on the use of\u00a0 generative AI throughout the stages of the software development life cycle (SDLC). From a CTO\/VPE perspective, there are still many uncertainties about where to automate and how.<\/p>\n<p>With all the potential that the <a href=\"https:\/\/en.wikipedia.org\/wiki\/Generative_artificial_intelligence\" rel=\"noopener\" target=\"_blank\">generative AI<\/a> (GenAI) brings in, what are the real productivity gains across different types of engineering activities? How much, indeed, engineers save with code generation assistants? What areas of the software delivery process are already being gradually automated by AI? What would engineers delegate to GenAI and what are the concerns for QA, DevOps, cybersecurity, etc.?<\/p>\n<p>Let\u2019s figure it out.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"The_promise_of_AI_for_coding\"><\/span>The promise of AI for coding<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>In July 2023, a group of experts from IBM introduced a <a href=\"https:\/\/medium.com\/@JerryCuomo\/quantifying-the-productivity-gains-of-generative-ai-for-developers-86fa3a76b63c\" rel=\"noopener\" target=\"_blank\">study<\/a> quantifying possible productivity gains for engineers of different seniority (from juniors to architects). In brief, the research forecasts that, by the 5th year, total team\u2019s productivity can increase by 58%, with all members surpassing 50% gains.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-engineering-productivity-gains-ibm-predictions-2023.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-engineering-productivity-gains-ibm-predictions-2023-1024x401.png\" width=\"720\" class=\"aligncenter size-large wp-image-67675\" \/><\/a><small>(source: <a href=\"https:\/\/medium.com\/@JerryCuomo\/quantifying-the-productivity-gains-of-generative-ai-for-developers-86fa3a76b63c\" rel=\"noopener\" target=\"_blank\">IBM<\/a>)<\/small><\/center><\/p>\n<p>Improved productivity will eventually have an impact on the final outcomes\u2014including products, processes, and timelines.<\/p>\n<div id=\"attachment_67711\" style=\"width: 120px\" class=\"wp-caption alignright\"><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/jerry-cuomo-2024.jpeg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-67711\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/jerry-cuomo-2024-150x150.jpeg\" width=\"110\" height=\"110\" class=\"size-thumbnail wp-image-67711\" \/><\/a><p id=\"caption-attachment-67711\" class=\"wp-caption-text\"><small>Jerry Cuomo<\/small><\/p><\/div>\n<blockquote><p>\u201cWe estimate that generative AI can lead to a 15\u201320% increase in the number of new products or features developed, a 10\u201315% reduction in the number of bugs found in production, a 5\u201310% increase in customer retention and loyalty, and a 10\u201315% reduction in time-to-market for new products or features.\u201d<\/p>\n<p>\u2014<a href=\"https:\/\/www.linkedin.com\/in\/jerry-cuomo\/\" rel=\"noopener\" target=\"_blank\">Jerry Cuomo<\/a>, IBM Fellow, VP\/CTO of Technology\u00a0<\/p><\/blockquote>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-5-year-engineering-productivity-gains-by-role-ibm-predictions-2023.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-5-year-engineering-productivity-gains-by-role-ibm-predictions-2023-1024x674.png\" width=\"720\" class=\"aligncenter size-large wp-image-67681\" \/><\/a><small>(source: <a href=\"https:\/\/medium.com\/@JerryCuomo\/quantifying-the-productivity-gains-of-generative-ai-for-developers-86fa3a76b63c\" rel=\"noopener\" target=\"_blank\">IBM<\/a>)<\/small><\/center><\/p>\n<div id=\"attachment_67716\" style=\"width: 160px\" class=\"wp-caption alignright\"><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/chris-gardner.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-67716\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/chris-gardner-150x150.jpg\" width=\"150\" height=\"150\" class=\"size-thumbnail wp-image-67716\" \/><\/a><p id=\"caption-attachment-67716\" class=\"wp-caption-text\"><small>Chris Gardner<\/small><\/p><\/div>\n<p>Similarly, Forrester <a href=\"https:\/\/www.forrester.com\/blogs\/predictions-2024-software-development\/\" rel=\"noopener\" target=\"_blank\">estimates<\/a> that developers\/coders can gain 20\u201350% productivity by adopting GenAI, while testers can become more efficient by 15\u201320% (October 2023). According to the prediction, \u201c<i>all members of product teams will gain above 10% efficiency<\/i>\u201d by using assistive AI tools for planning and delivery.<\/p>\n<blockquote><p>\u201cSome have seen productivity rise to 200% and more when experienced engineers use genAI to work with languages or libraries outside their normal zone of development.\u201c \u2014<a href=\"https:\/\/www.linkedin.com\/in\/chrismichaelgardner\/\" rel=\"noopener\" target=\"_blank\">Chris Gardner<\/a>, VP and Research Director, Forrester<\/p><\/blockquote>\n<p>Other industry reports provided estimates similar to the forecasts described in this section. However, after having AI tools deployed and adopted, real figures may differ, more or less. During 2022\u20132023, some reports confirmed predictions, while other evaluations were a bit more modest.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Wait_but_what_are_the_real_productivity_gains\"><\/span>Wait, but what are the real productivity gains?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>A <a href=\"https:\/\/www.mckinsey.com\/capabilities\/mckinsey-digital\/our-insights\/unleashing-developer-productivity-with-generative-ai\" rel=\"noopener\" target=\"_blank\">study<\/a> among 40 <strong>McKinsey<\/strong> developers published in June 2023 revealed tremendous productivity gains when using AI tools. Still, the exact figures varied across types of tasks, as it was observed by other similar research papers. For instance, automation of delivering documentation was done by 2x faster, with 20\u201345% improvements tracked for code generation and refactoring.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-developer-productivity-gains-mckinsey-forecact-2023.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-developer-productivity-gains-mckinsey-forecact-2023-1024x613.png\" width=\"720\" class=\"aligncenter size-large wp-image-67683\" \/><\/a><small>(source: <a href=\"https:\/\/www.mckinsey.com\/capabilities\/mckinsey-digital\/our-insights\/unleashing-developer-productivity-with-generative-ai\" rel=\"noopener\" target=\"_blank\">McKinsey<\/a>)<\/small><\/center><\/p>\n<p>Experts at McKinsey also noted that \u201c<i>in some cases, tasks took junior developers 7\u201310% longer with the tools than without them<\/i>.\u201d Nevertheless, developers with AI tools were 25\u201330% more likely to complete those tasks, rather than engineers without assistance.<\/p>\n<p>In some scenarios, developers used more than a single AI tool. In this case, they gained additional time improvements of 1.5\u20132.5x.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-developer-productivity-task-completion-rate-mckinsey-study-2023.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-developer-productivity-task-completion-rate-mckinsey-study-2023-1024x601.png\" width=\"720\" class=\"aligncenter size-large wp-image-67689\" \/><\/a><small>(source: <a href=\"https:\/\/www.mckinsey.com\/capabilities\/mckinsey-digital\/our-insights\/unleashing-developer-productivity-with-generative-ai\" rel=\"noopener\" target=\"_blank\">McKinsey<\/a>)<\/small><\/center><\/p>\n<p>It should be noted that, during McKinsey\u2019s study, generative AI tools occasionally provided incorrect recommendations and introduced code errors. The authors of the report also admitted the existing AI tools are not able to know the specific context, which may influence integrability or security requirements to the code. \u201c<i>Combining multiple frameworks with disparate code logic<\/i>\u201d may be an issue.<\/p>\n<p>In its turn, <strong>GitHub<\/strong>\u2014which is behind one of the top AI assistance tools for engineers\u2014regularly conducts its own evaluations of developers\u2019 productivity. In October 2023, GitHub <a href=\"https:\/\/github.blog\/2023-10-10-research-quantifying-github-copilots-impact-on-code-quality\/\" rel=\"noopener\" target=\"_blank\">measured<\/a> that code reviews with its Copilot Chat were completed by engineers 15% faster. (The <a href=\"https:\/\/docs.github.com\/en\/copilot\/github-copilot-chat\/about-github-copilot-chat\" rel=\"noopener\" target=\"_blank\">tool<\/a> provides answers about the code and its quality right from an IDE.)<\/p>\n<p>At the same time, developers do not accept anything AI suggests. Another <a href=\"https:\/\/github.blog\/2023-06-27-the-economic-impact-of-the-ai-powered-developer-lifecycle-and-lessons-from-github-copilot\/\" rel=\"noopener\" target=\"_blank\">study<\/a> by GitHub held in March\/June 2023 found that an average acceptance rate was ~30%. The rate increased as an expert became more familiar with Copilot.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-developer-productivity-github-research-2023.jpg\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-developer-productivity-github-research-2023-1024x585.jpg\" width=\"720\" class=\"aligncenter size-large wp-image-67693\" \/><\/a><small>(source: <a href=\"https:\/\/github.blog\/2023-06-27-the-economic-impact-of-the-ai-powered-developer-lifecycle-and-lessons-from-github-copilot\/\" rel=\"noopener\" target=\"_blank\">GitHub<\/a>)<\/small><\/center><\/p>\n<p>The study by GitHub also revealed that junior developers were more likely to accept AI-based recommendations, while the rate among senior engineers was lower.<\/p>\n<p>Previous experiments by GitHub <a href=\"https:\/\/github.blog\/2022-09-07-research-quantifying-github-copilots-impact-on-developer-productivity-and-happiness\/\" rel=\"noopener\" target=\"_blank\">discovered<\/a> that engineers using Copilot had a higher rate of task completion (78% vs. 70%, September 2022). Besides, a <a href=\"https:\/\/arxiv.org\/pdf\/2302.06590.pdf\" rel=\"noopener\" target=\"_blank\">survey<\/a> held between May and June 2022 discovered a 55.8% reduction in task completion time, on average.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-developer-productivity-average-time-to-complete-the-task-github-research-2022.jpg\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-developer-productivity-average-time-to-complete-the-task-github-research-2022-1024x657.jpg\" width=\"720\" class=\"aligncenter size-large wp-image-67696\" \/><\/a><small>(source: <a href=\"https:\/\/github.blog\/2022-09-07-research-quantifying-github-copilots-impact-on-developer-productivity-and-happiness\/\" rel=\"noopener\" target=\"_blank\">GitHub<\/a>)<\/small><\/center><\/p>\n<p>In July 2022, <strong>Google<\/strong> also <a href=\"https:\/\/blog.research.google\/2022\/07\/ml-enhanced-code-completion-improves.html\" rel=\"noopener\" target=\"_blank\">revealed<\/a> that implementing ML-driven assistance for the company\u2019s engineers led to reducing coding iteration time by 6% (i.e., shrinking \u201c<i>time between builds and tests<\/i>\u201d).<\/p>\n<p>CI\/CD vendor <strong>Harness<\/strong> <a href=\"https:\/\/www.harness.io\/blog\/the-impact-of-github-copilot-on-developer-productivity-a-case-study\" rel=\"noopener\" target=\"_blank\">evaluated<\/a> that its customer\u2019s developers made 10.6% more pull requests when using GitHub Copilot, as well as spent 3.5 hours less on a task, iterating more often (September 2023).<\/p>\n<div id=\"attachment_67720\" style=\"width: 145px\" class=\"wp-caption alignright\"><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/david-walker.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-67720\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/david-walker-150x150.jpg\" width=\"135\" height=\"135\" class=\"size-thumbnail wp-image-67720\" \/><\/a><p id=\"caption-attachment-67720\" class=\"wp-caption-text\"><small>David Walker<\/small><\/p><\/div>\n<p>The <strong>Westpac<\/strong> bank operating in Australia achieved a 46% productivity gain when <a href=\"https:\/\/www.itnews.com.au\/news\/westpac-sees-46-percent-productivity-gain-from-ai-coding-experiment-596423\" rel=\"noopener\" target=\"_blank\">exploring<\/a> generative AI tools from Microsoft, Amazon, and OpenAI (June 2023).<\/p>\n<blockquote><p>\u201cWhen we looked at the time that it took the hand-coding team to actually complete their tasks, on average it was 3.5x longer than it took the other teams to do their tasks.\u201d \u2014<a href=\"https:\/\/www.linkedin.com\/in\/davidkwalker1\/\" rel=\"noopener\" target=\"_blank\">David Walker<\/a>, CTO, Westpac<\/p><\/blockquote>\n<p>In May\u2013June 2023, a mobile team of a <strong>software company located in Romania <\/strong><a href=\"https:\/\/arxiv.org\/pdf\/2308.04736.pdf\" rel=\"noopener\" target=\"_blank\">observed<\/a> a 35% improvement in technical onboarding task time. The engineers also spent more than 40% less time on moderate and complex tasks when using AI tools, such as ChatGPT 4.0 and GitHub Copilot.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-mobile-teams-technical-university-cluj-napoca-romania-study-2023.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-mobile-teams-technical-university-cluj-napoca-romania-study-2023-1024x605.png\" width=\"720\" class=\"aligncenter size-large wp-image-67686\" \/><\/a><small>(source: <a href=\"https:\/\/arxiv.org\/pdf\/2308.04736.pdf\" rel=\"noopener\" target=\"_blank\">Technical University of Cluj-Napoca, Romania<\/a>)<\/small><\/center><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Generative_AI_across_SDLC\"><\/span>Generative AI across SDLC<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Now that we know how much productivity AI is already helping to achieve, let\u2019s have a closer look at some of the specific stages of SDLC where this happens.<\/p>\n<p>&nbsp;<\/p>\n<h4><span class=\"ez-toc-section\" id=\"AI_in_DevOps_and_security\"><\/span>AI in DevOps and security<span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p>In a <a href=\"https:\/\/www.dynatrace.com\/news\/blog\/state-of-ai-in-2024\/\" rel=\"noopener\" target=\"_blank\">recent study<\/a>, \u201c<i>The State of AI in 2024<\/i>,\u201d Dynatrace discovered that technology leaders adopting artificial intelligence expect it to become critical for the core DevOps activities, such as:<\/p>\n<ul class=\"custom-list custom-list-green\">\n<li>threat detection, investigation, and response (82%)<\/li>\n<li>automating complex operations (63%)<\/li>\n<li>eliminating false alerts and the manual effort of validating code deployments (58%)<\/li>\n<\/ul>\n<p>While increasing investments in AI-driven issue prevention\/remediation, 87% of IT operations\/DevOps leaders believe this effort is \u201c<i>critical to managing multicloud complexity<\/i>.\u201d<\/p>\n<p>Besides, 95% of the participants are concerned that generative AI could lead to data leakage and improper\/illegal use of intellectual property. (See the <a href=\"https:\/\/d1io3yog0oux5.cloudfront.net\/_dce896f78e35402e97f5962be5b452ab\/dynatrace\/news\/2023-12-12_Global_Report_Reveals_Composite_AI_Will_Be_319.pdf\" rel=\"noopener\" target=\"_blank\">press release<\/a> for details.) The opinions among developers are similar. More than a half (59%) have security concerns in this regard, according to a <a href=\"https:\/\/www.jetbrains.com\/lp\/devecosystem-2023\/\" rel=\"noopener\" target=\"_blank\">report<\/a> by JetBrains issued in November 2023.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-developer-concerns-jetbrains-2023.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-developer-concerns-jetbrains-2023-1024x639.png\" width=\"720\" class=\"aligncenter size-large wp-image-67702\" \/><\/a><small>(source: <a href=\"https:\/\/www.jetbrains.com\/lp\/devecosystem-2023\/\" rel=\"noopener\" target=\"_blank\">JetBrains<\/a>)<\/small><\/center><\/p>\n<p>At the same time, according to a recent Gartner&#8217;s <a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2023-10-03-gartner-poll-finds-55-percent-of-organizations-are-in-piloting-or-production-mode-with-generative-ai\" rel=\"noopener\" target=\"_blank\">poll<\/a> held in October 2023, 78% of executives \u201c<i>believe that the benefits of generative AI outweigh its risks<\/i>.\u201d<\/p>\n<p>&nbsp;<\/p>\n<h4><span class=\"ez-toc-section\" id=\"A_developers_view_on_AI\"><\/span>A developer\u2019s view on AI<span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p>In JetBrains&#8217;s report, the developers also shared their thoughts on the types of activities they\u2019d delegate to an AI assistant. <i>Comments\/documentation<\/i> and <i>testing <\/i>are the top things that most developers would entrust to a robot, while writing code is the core responsibility that engineers would prefer doing by themselves.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-developer-tasks-delegate-jetbrains-2023.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-developer-tasks-delegate-jetbrains-2023-1024x595.png\" width=\"720\" class=\"aligncenter size-large wp-image-67705\" \/><\/a><small>(source: <a href=\"https:\/\/www.jetbrains.com\/lp\/devecosystem-2023\/\" rel=\"noopener\" target=\"_blank\">JetBrains<\/a>)<\/small><\/center><\/p>\n<p>Still, 28% of developers in JetBrains&#8217;s <a href=\"https:\/\/www.jetbrains.com\/lp\/devecosystem-2023\/ai\/\" rel=\"noopener\" target=\"_blank\">survey<\/a> noted that their companies&#8217; policies limit the use of cloud-based AI tools.<\/p>\n<p>&nbsp;<\/p>\n<h4><span class=\"ez-toc-section\" id=\"GenAI_in_QA_and_testing\"><\/span>GenAI in QA and testing<span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p>A <a href=\"https:\/\/www.lambdatest.com\/future-of-quality-assurance-survey#AIMLinTesting\" rel=\"noopener\" target=\"_blank\">survey<\/a> by LambdaTest (held in July\u2013October 2023) revealed that the top three GenAI use cases in QA are as follows:<\/p>\n<ul class=\"custom-list custom-list-green\">\n<li>test data generation (50.5%)<\/li>\n<li>test case creation (45.9%)<\/li>\n<li>analytics and reporting (35.6%)<\/li>\n<\/ul>\n<p>At the same time, 25.6% of QA engineers believe that AI will \u201c<i>bridge the gap between manual and automated testing<\/i>.\u201d Besides, 60.3% of respondents see <i>the reliability of AI platforms<\/i> as the most significant concern for QA.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-ml-quality-assurance-qa-testing-lambdatest-survey-2023.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/generative-ai-ml-quality-assurance-qa-testing-lambdatest-survey-2023-1024x740.png\" width=\"720\" class=\"aligncenter size-large wp-image-67708\" \/><\/a><small>(source: <a href=\"https:\/\/www.lambdatest.com\/future-of-quality-assurance-survey\" rel=\"noopener\" target=\"_blank\">LambdaTest<\/a>)<\/small><\/center><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Budgets_vs_ongoing_learning\"><\/span>Budgets vs. ongoing learning<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>IDC <a href=\"https:\/\/www.idc.com\/getdoc.jsp?containerId=prUS51335823\" rel=\"noopener\" target=\"_blank\">expects<\/a> (October 2023) that G2000 companies will allocate more than 40% of their IT budgets to AI-related initiatives by 2025. At the same time, through 2026, 65% of enterprises may fail in unleashing the full potential of AI due to \u201cIT skills mismatch\u201d caused by underinvested training\/education.<\/p>\n<blockquote><p>&#8220;As the industry moves forward with this fundamental transition to AI embedded into every business and technology function in the enterprise, IDC believes that every CEO will need to have an AI strategy\u2014and generative AI is the trigger\u2026It is best to get started quickly.&#8221; \u2014<a href=\"https:\/\/www.linkedin.com\/in\/phcarter\/\" rel=\"noopener\" target=\"_blank\">Phil Carter<\/a>, IDC (<a href=\"https:\/\/www.idc.com\/getdoc.jsp?containerId=prUS51236823\" rel=\"noopener\" target=\"_blank\">source<\/a>)<\/p><\/blockquote>\n<div id=\"attachment_67727\" style=\"width: 150px\" class=\"wp-caption alignright\"><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/marci-maddox.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-67727\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2024\/02\/marci-maddox-150x150.jpg\" width=\"140\" height=\"140\" class=\"size-thumbnail wp-image-67727\" \/><\/a><p id=\"caption-attachment-67727\" class=\"wp-caption-text\"><small>Marci Maddox<\/small><\/p><\/div>\n<p>In addition to establishing an environment where engineers can learn and grow their skills, things like security and risk control should also matter.<\/p>\n<blockquote><p>\u201cAs industries transition to use GenAI to automate or augment every process, project, or interaction, the measure of success will be in improving productivity and reducing the level of effort to complete the task in a secure, compliant, and trustworthy manner.\u201d \u2014<a href=\"https:\/\/www.linkedin.com\/in\/marcimaddox\/\" rel=\"noopener\" target=\"_blank\">Marci Maddox<\/a>, IDC (<a href=\"https:\/\/www.idc.com\/getdoc.jsp?containerId=US51262223\" rel=\"noopener\" target=\"_blank\">source<\/a>)<\/p><\/blockquote>\n<p>McKinsey recommends fostering ongoing learning and practical knowledge sharing among engineers. The company\u2019s <a href=\"https:\/\/www.mckinsey.com\/capabilities\/mckinsey-digital\/our-insights\/unleashing-developer-productivity-with-generative-ai\" rel=\"noopener\" target=\"_blank\">report<\/a> noted that this approach helped to improve the quality of prompts among participants of the company&#8217;s study.<\/p>\n<p>At the same time, according to GitHub, more than a half of developers (57%) <a href=\"https:\/\/github.blog\/2023-06-13-survey-reveals-ais-impact-on-the-developer-experience\/\" rel=\"noopener\" target=\"_blank\">believe<\/a> that AI tools can help them acquire new coding skills (March\/June 2023). So, a company adopting AI needs to scale this by providing proper assistance, environment, culture, etc.<\/p>\n<p>Gartner <a href=\"https:\/\/www.gartner.com\/en\/topics\/generative-ai\" rel=\"noopener\" target=\"_blank\">predicts<\/a> that, by 2025, 30% of enterprises will have AI-assisted development and testing implemented. By 2026, the layouts\/interfaces\/etc. may be designed by generative AI for 60% of new websites and mobile apps. By 2027, ~15% of new software will be built solely by AI, the analysts expect.<\/p>\n<p>It is clear that the time for AI adoption for software engineering is now.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Frequently_asked_questions_FAQ\"><\/span>Frequently asked questions (FAQ)<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li style=\"margin-bottom: 12px;\">\n<p style=\"margin-bottom: 6px;\"><b>How can generative AI benefit different stages of the SDLC?<\/b><\/p>\n<\/p>\n<p>Forrester estimates that developers\/coders can gain 20\u201350% productivity, while testers can become more efficient by 15\u201320% with GenAI. All members of product teams can improve their efficiency by 10% when using AI tools for planning and delivery, the analyst predicts. According to McKinsey, delivering documentation can be done by 2x faster, with 20\u201345% improvements tracked for code generation and refactoring. Developers using more than a single AI tool can gain additional time improvements of 1.5\u20132.5x. GitHub estimates that code reviews with its Copilot Chat are completed by 15% faster. In its turn, IBM forecasts that, by the 5th year, the total team\u2019s productivity can increase by 58%, with all the members surpassing 50% gains.<\/p>\n<\/li>\n<li style=\"margin-bottom: 12px;\">\n<p><b>What AI tools do developers use?<\/b><\/p>\n<p style=\"margin-top: 6px;\">According to a 2023 report by JetBrains, the top 10 AI tools used by engineers are ChatGPT, GitHub Copilot, Midjourney, Visual Studio IntelliCode, OpenAI DALL-E, Dream Studio (Stable Diffusion), Tabnine, Pictory, Synthesia, and Amazon CodeWhisperer.<\/p>\n<\/li>\n<li>\n<p><b>Will generative AI replace software developers?<\/b><\/p>\n<p style=\"margin-top: 6px;\">Engineers don&#8217;t think so. While comments, documentation, and testing are the top things that most developers would entrust to AI, writing code is the core responsibility that engineers would prefer doing by themselves. A study by GitHub held in 2023 found that an average acceptance rate was just ~30%, among senior engineers it was even lower, since the AI-driven recommendations were not valuable enough or simply wrong. Furthermore, 95% of the participants in a Dynatrace survey were concerned that generative AI could lead to data leakage and improper\/illegal use of intellectual property. That&#8217;s why 28% of developers in a survey from JetBrains noted that their companies\u2019 policies limit the use of cloud-based AI tools. Still, instead of replacing engineers, AI will help to acquire new development skills (57%, GitHub, 2023), deliver more products and make software more reliable (IBM, 2023), as well as excel at new expert roles and responsibilities.<\/p>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Further_reading\"><\/span>Further reading<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/klm-handles-2x-more-customer-requests-with-artificial-intelligence\/\" rel=\"noopener\" target=\"_blank\">KLM Handles 2x More Customer Requests with Artificial Intelligence<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/osaka-university-cuts-power-consumption-by-13-with-kubernetes-and-ai\/\" rel=\"noopener\" target=\"_blank\">Osaka University Cuts Power Consumption by 13% with Kubernetes and AI<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/zurich-insurance-group-incorporates-rpa-to-achieve-1b-of-savings\/\" rel=\"noopener\" target=\"_blank\">Zurich Insurance Group Incorporates RPA to Achieve $1B of Savings<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>(Featured image credit)<\/p>\n<p>&nbsp;<\/p>\n<p>We still lack enough data on AI<\/p>\n<p>Since the launch of ChatGPT and code generation tools like GitHub Copilot, a lot of predictions have been made regarding productivity improvements in software engineering. Some analysts and vendors expect that the AI revolution will cut time on development by 2x, while [&#8230;]<\/p>\n","protected":false},"author":5,"featured_media":67686,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[7],"tags":[748],"class_list":["post-67670","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-and-opinion","tag-machine-learning"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Generative AI for SDLC: Top Areas for a CTO\/VPE to Pay Attention To | Altoros<\/title>\n<meta name=\"description\" content=\"While analysts suggest artificial intelligence can speed up coding by 10\u201320\u201350%, real-life productivity gains vary among scenarios\/expertise\/etc., studies reveal.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.altoros.com\/blog\/generative-ai-for-sdlc-top-areas-for-a-cto-vpe-to-pay-attention-to\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Generative AI for SDLC: Top Areas for a CTO\/VPE to Pay Attention To | Altoros\" \/>\n<meta property=\"og:description\" content=\"(Featured image credit) &nbsp; We still lack enough data on AI Since the launch of ChatGPT and code generation tools like GitHub Copilot, a lot of predictions have been made regarding productivity improvements in software engineering. 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