{"id":52432,"date":"2026-02-20T07:48:05","date_gmt":"2026-02-20T07:48:05","guid":{"rendered":"https:\/\/www.intelligentcio.com\/north-america\/?p=52432"},"modified":"2026-02-20T07:48:06","modified_gmt":"2026-02-20T07:48:06","slug":"the-tough-pill-for-enterprises-to-swallow-co-pilots-arent-enough","status":"publish","type":"post","link":"https:\/\/www.intelligentcio.com\/north-america\/2026\/02\/20\/the-tough-pill-for-enterprises-to-swallow-co-pilots-arent-enough\/","title":{"rendered":"The tough pill for enterprises to swallow: Co-pilots aren\u2019t enough"},"content":{"rendered":"\n

AI-powered coding co-pilots promise faster development and greater efficiency, but Derek Holt, CEO, Digital.ai, argues enterprises are discovering they do not address the biggest bottlenecks in software delivery.<\/em><\/p>\n\n\n\n

The hype around one specific part of next generation software development and delivery, AI-powered coding co-pilots, has reached new heights.<\/p>\n\n\n\n

In the past few years, we have seen offerings from traditional DevOps vendors like GitHub (GitHub Copilot), newer entrants like Cursor and even the foundational model companies like OpenAI (Codex), Anthropic (Claude Code) and more. These tools all promise faster code creation, less repetitive tasks and an economically sound approach to prior human-based pair programming approaches. At the same time, these tools are being positioned as the key to improving software development economics for the enterprise and driving innovation velocity.<\/p>\n\n\n\n

But here\u2019s the early and uncomfortable truth for enterprises: coding co-pilots rarely address the biggest bottlenecks and are not moving the needle on business outcomes as promised.<\/p>\n\n\n\n

I have zero doubt coding co-pilots are here to stay. They can and do accelerate local developer productivity. But the software development and delivery process at large scale enterprises is a complex and interconnected system spanning planning, coding, testing, securing and releasing applications into production, all while maintaining proper governance and compliance. Co-pilots alone only improve coding efficiency and miss the bigger opportunity: improving flow, security and quality across the entire software lifecycle.<\/p>\n\n\n\n

The shocking limitations of coding co-pilots in the enterprise<\/strong><\/p>\n\n\n\n

Coding co-pilots have been adopted faster than any other AI solution within development organisations. Recent estimates indicate in the last two years alone over 90% of enterprise R&D organisations have either fully adopted or piloted co-pilots. And yet the impact of both the change management and tooling cost have been mixed. Two specific reports in recent months have sent shockwaves of disappointment throughout the industry, including METRs findings that showed co-pilot adoption has actually made developers slower and the now infamous MIT study that showed 95% of all AI projects in the enterprise have \u201cfailed\u201d.<\/p>\n\n\n\n

The big question is \u2013 why are coding co-pilots not having the expected impact in the enterprise? The failures span various simple realities:<\/p>\n\n\n\n

\u2022 Code generation is just one step in a bigger process \u2013 coding co-pilots are visualised and engaged within an integrated developer environment. They are experts at suggesting code snippets, design patterns and boilerplate code, but are often blind to the broader context especially in more complex environments. They lack knowledge of business priorities, architectural standards, security requirements and compliance rules.<\/p>\n\n\n\n

\u2022 Coding co-pilots amplify bad planning practices upstream \u2013 In most enterprises the planning process is much more laborious than coding. Prioritisation, work break down efforts and task assignment is often measured in months not days or weeks. In fact, many of the customers we work with spend 5-10x more time in planning than coding. To make matters more challenging, if upstream planning is flawed (unclear requirements, misaligned priorities, disconnected roadmaps), co-pilots simply help developers build the wrong things more quickly. Speeding up and automating misdirection doesn\u2019t create value, it compounds waste.<\/p>\n\n\n\n

\u2022 Integration and delivery bottlenecks downstream \u2013 Code created by a human or a machine needs to be tested, secured, scanned and delivered. If downstream processes are slow, manual, brittle or fragmented, any gains in coding time are unlikely to translate to faster or more effective delivery. Coding co-pilots in the enterprise often do not address the true bottlenecks that exist downstream.<\/p>\n\n\n\n

\u2022 Enterprise scale and complexity \u2013 There is an old saying in software development \u2018code is read 10x more than it is written\u2019. This is even more true in the enterprise. Large enterprises wrestle with legacy systems, complex architecture, massive code bases, globally distributed teams and strict regulatory realities. Coding co-pilots don\u2019t understand these challenges and thus do not address them.<\/p>\n\n\n\n

\u2022 The math doesn\u2019t math \u2013 As the name suggests, coding co-pilots target developers. But on average, only 50% of the people in an enterprise development organisation are developers. They are joined by designers, architects and QA professionals. These 50%, on average, spend only 25% of their time writing code. Often, they are in meetings, doing research or whiteboarding new ideas. With the most positive early reviews of co-pilots showing a 10-30% developer gain \u2013 the maximum impact today is 50% x 25% x 20% which equals a 2.5% of maximum improvement on the overall process.<\/p>\n\n\n\n

The bigger unlocks lie upstream and downstream from coding<\/strong><\/p>\n\n\n\n

We are all marching towards a shared goal of improving and optimising the business process of building and delivering software. So, while we believe in coding co-pilots, our data and customers tell us the real flow unlocks happen when we improve the automation and connective tissue before and after coding.<\/p>\n\n\n\n

Upstream – Agentic Planning<\/strong><\/p>\n\n\n\n

Enterprise companies spend up to 50% of the total R&D time in planning. Leveraging AI to drive a more agentic approach to planning speeds time from idea to development while also improving decision making to avoid last-minute change and unexpected conflicts. When planning becomes more intelligent and adaptive, the impact of coding co-pilots delivers increased innovation and improved alignment with business objectives.<\/p>\n\n\n\n

Downstream- Agentic Testing, Agentic Security and Agentic Delivery<\/strong><\/p>\n\n\n\n

Adopting Agentic Planning upstream of coding is a major unlock – but the biggest opportunities lie downstream. Advances in Agentic Testing are helping ensure software quality across an ever-expanding range of devices and environments and Agentic Security is accelerating delivery while strengthening defenses, enabling apps to be hardened early in development and intelligently protected in production. Smarter delivery pipelines – blending agentic, automated and human tasks – are speeding value delivery without sacrificing control, compliance or governance. Together, these downstream innovations turn raw code into business value faster, safer and with less friction.<\/p>\n\n\n\n

Smarter delivery over coding<\/strong><\/p>\n\n\n\n

AI is powering a renaissance in the world of software development and delivery. Every organisation needs to be thinking differently in this 4th Wave. Real productivity gains come not from improving and optimising isolated tasks like coding, but from removing friction in the end-to-end flow of work. Co-pilots are just one part of that story.<\/p>\n\n\n\n

When enterprises invest and innovate upstream (Agentic Planning) and downstream (Agentic Testing, Security and Delivery), they can unlock the true exponential gains promised in this 4th wave of software development: more business value, faster time to market, reduced risk, increased security and more predictable outcomes.<\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

AI-powered coding co-pilots promise faster development and greater efficiency, but Derek Holt, CEO, Digital.ai, argues enterprises are discovering they do not address the biggest bottlenecks in software delivery. The hype around one specific part of next generation software development and delivery, AI-powered coding co-pilots, has reached new heights. In the past few years, we have […]<\/p>\n","protected":false},"author":58,"featured_media":52433,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[7925,43],"tags":[10830,10827,10832,10831,10829,151,221,1321,10828,10046],"class_list":["post-52432","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-expert-opinion","category-top-stories","tag-agentic-planning","tag-agentic-security","tag-agentic-testing","tag-ai-in-software-development","tag-ai-powered-coding-co-pilots","tag-devops","tag-digital-transformation","tag-digital-ai","tag-enterprise-software-development","tag-software-delivery"],"acf":[],"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.intelligentcio.com\/north-america\/wp-json\/wp\/v2\/posts\/52432","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.intelligentcio.com\/north-america\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.intelligentcio.com\/north-america\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/north-america\/wp-json\/wp\/v2\/users\/58"}],"replies":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/north-america\/wp-json\/wp\/v2\/comments?post=52432"}],"version-history":[{"count":1,"href":"https:\/\/www.intelligentcio.com\/north-america\/wp-json\/wp\/v2\/posts\/52432\/revisions"}],"predecessor-version":[{"id":52434,"href":"https:\/\/www.intelligentcio.com\/north-america\/wp-json\/wp\/v2\/posts\/52432\/revisions\/52434"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/north-america\/wp-json\/wp\/v2\/media\/52433"}],"wp:attachment":[{"href":"https:\/\/www.intelligentcio.com\/north-america\/wp-json\/wp\/v2\/media?parent=52432"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.intelligentcio.com\/north-america\/wp-json\/wp\/v2\/categories?post=52432"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.intelligentcio.com\/north-america\/wp-json\/wp\/v2\/tags?post=52432"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}