Using AI to build faster is no longer a differentiator. So, let’s start with taking that as a given. This blog isn’t a framework for AI-powered development either. Instead, we’re going to outline what we do as a company that develops software products for enterprise customers.
For us, speed and governance are not things to be traded against each other. Building fast with AI is not the future. The future is building faster (using AI and other tools) while maintaining strict governance standards throughout. That’s our first-hand experience gathered over decades in software development.
We Weren’t Waiting Around for AI
At the time of writing (summer 2026), we are in a crazy hype cycle around using AI to build, build, build. For us at Access IT Automation, we’ve been using AI in our development processes for several years now. So, we have practical expertise to call on, and real commercial products that have been developed.
Plus, we have experience building software products before AI technologies were useful. Rather than jumping onto the hype bandwagon, we methodically folded AI technologies into our existing processes, augmenting how our team works to deliver products relied on by some of the world’s largest corporations.
As a result, we’ve hit the friction points, limitations, and challenges of using AI that are only now starting to surface alongside the “AI is great” excitement. Examples include the wireframe-vs-production gap, operational overhead challenges, and governance questions. We used those experiences to create the pipeline described below. It isn’t theory – it was hard-earned in the real world of developing usable software applications.
We know that AI helps most with velocity. It’s unparalleled in that regard. We also know its boundaries in key areas like judgement and governance. And why those boundaries can’t be ignored.
Empowered, Not Replaced
Let’s expand on those last points further.
AI empowers our team by taking on the grunt work and accelerating iteration.
However, judgement, architecture decisions, and context analysis continue to remain with the people who know our areas of expertise from years of experience. Things like the real-world of enterprise IT infrastructure and enhancing the user experience.
AI can develop options fast, but it doesn’t know what will solve a real problem in a corporate IT environment. It helps us test ideas fast, throw away what doesn’t work without delay, and get to the right solution quicker than using traditional methods. But AI doesn’t own the decisions – our people do.
It’s the shift.
Shift: Built Fast, Shipped Governed
That last sentence was a bit of a play on words, but it’s also a concrete example of AI-accelerated development with rigorous governance (enterprise-grade testing, QA pipelines, etc).
Capture Shift is a new Access IT Automation product where we used AI-accelerated development for rapid iteration. That accounted for 20 percent of the work required to get the product ready for release to customers, but it was work that was completed on an astonishingly quick timescale.
The speed of build was exciting, but we didn’t compromise on any area of governance. Capture Shift went through the same governance protocols as the products in our portfolio developed using more traditional methods.
Two Speeds, One Pipeline
For us, Capture Shift proved our model of software development in the AI era works. It’s two speeds with one pipeline.
There is one speed for AI-accelerated development where iterations are fast, options can fail, and adjustments are made quickly.
Then there is another speed for the applications that will reach customers. Applications that get to this state go through fixed, rigorous, and proven testing and deployment processes.
Two speeds, one pipeline.
Everything that reaches our customers, from new features to new products, goes through this pipeline, regardless of how it was developed. This is because we believe good governance should never be an afterthought amid the AI hype. For us, good governance in software development is fundamental.
So, it’s AI for velocity and a fixed pipeline for trust and usability under real-world conditions.
Customer-Focused Solutions, Built to Last
The last point about usability under real-world conditions is worth focusing on in closing. You can build all sorts of applications at breakneck speed using AI, but the exercise is completely pointless if those applications can’t cope with the variations, unpredictability, and stresses of real-world conditions.
Using AI in software development is now a given. If you’re not doing it, you will rapidly fall behind. But it’s also essential to never lose focus on why the software is being developed in the first place. That means customer-focused solutions built to last and built to thrive in challenging real-world conditions.
Using AI to build faster isn’t even close to enough to achieve this goal. What you need is two speeds, one pipeline.
