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title: 7 Lessons from the Enterprise AI Summit in Charlotte
description: Engineering is no longer the bottleneck in AI-driven software delivery, speakers at the Enterprise AI Summit in Charlotte argued. Randy Shoup and Michelle Gill...
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# 7 Lessons from the Enterprise AI Summit in Charlotte

**[IT Revolution](https://daily.dev/sources/itrevolution)** · 6 min read · 0 upvotes · 0 comments

## Summary

Engineering is no longer the bottleneck in AI-driven software delivery, speakers at the Enterprise AI Summit in Charlotte argued. Randy Shoup and Michelle Gill reported AI-generated code rose from 19% to 57% over three quarters. Planview data showed only 8% of delivery time was spent in teams, so faster teams alone will change little. At Vanguard, AI-generated tests increased the share of resiliency runs that met their intent by 50% within a few months. GitLab's six-person Orbit team took a graph serving 2,500+ customers from first commit to production in three months, and Rise8 fielded a military tool in six weeks with six people.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://itrevolution.com/articles/7-lessons-from-the-enterprise-ai-summit-in-charlotte>

## Questions this post answers

### How much did AI-generated code increase at companies tracked by Randy Shoup and Michelle Gill?

AI-generated code rose from 19% to 57% of total code output over three quarters, according to data presented by Randy Shoup and Michelle Gill in their talk on agentic AI and code reviews. They argue this pace makes it impossible to keep reviewing code at human speed, requiring new validation approaches to keep up with machine-speed production.

_Teams scaling AI code generation can track how review practices adapt by following coverage like this on daily.dev._

### What percentage of software delivery time is actually spent inside engineering teams versus the rest of the organization?

Only 8% of delivery time is spent inside engineering teams, according to Planview's value stream data presented by Dr. Mik Kersten. This implies that making engineering teams faster with AI tools has limited impact on overall delivery speed, since most time is consumed by handoffs, approvals, and other organizational processes outside the team.

_Anyone rethinking where delivery bottlenecks really sit can follow this kind of value-stream analysis on daily.dev._

### Did AI-generated tests improve resiliency testing outcomes at Vanguard?

Yes, AI-generated tests tuned to production data increased the share of resiliency test runs that fully met their intended goals by 50% within a few months. This came after resiliency test volume had grown from 20,000 to 50,000 runs per year, yet fewer than 5% of those runs were fully meeting their goals before the change.

_Engineers weighing AI-assisted testing approaches can track real deployment results like this on daily.dev._

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- [Redesign how your team ships software with AI agents](https://daily.dev/posts/redesign-how-your-team-ships-software-with-ai-agents-ax18dgs01) · GitLab · 0 upvotes · 0 comments
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---

Tags: [#devops](https://daily.dev/tags/devops), [#leadership](https://daily.dev/tags/leadership), [#ai-coding](https://daily.dev/tags/ai-coding)

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