Published by Sue Johns-Chapman
Published Date 30.06.2026 
by Jessica Leyshon, Chief Marketing Officer at AutomatePro
AI has changed the economics of enterprise change. Code, workflows and integrations that once took weeks to build can now be created in hours, giving organisations the ability to move faster than ever before.
But the hidden cost of that acceleration is starting to emerge. AI is no longer just helping teams create new things; it is increasing the volume of change flowing into the enterprise systems that organisations depend on to operate, serve customers, manage risk and prove compliance.
That creates a challenge that every business and technology leader should be thinking about now. The bottleneck is no longer simply how quickly change can be created, but whether organisations have the quality controls, governance processes and audit evidence needed to test, validate and release that change safely.
It is also the challenge behind AutomatePro’s recent shortlisting in the Digital Transformation category of the UK Business Tech Awards, which recognises our work with Barclays to bring greater speed, confidence and control to ServiceNow change.
The platforms running your business
At the centre of this challenge are the enterprise platforms that large organisations rely on every day.
ServiceNow is one of the world’s leading enterprise software platforms, used by many of the largest organisations to manage their internal operations, everything from IT helpdesks and HR workflows to financial approvals, incident management and regulatory controls. More than 85% of the Fortune 500 run it, making it, in effect, the operational backbone of many large enterprises.
But platforms like ServiceNow do not stand still. New features are released, customisations are built and integrations are added all the time, creating a constant cycle of change across systems that organisations depend on to operate safely, efficiently and compliantly.
Every change, however small, has the potential to disrupt another part of the platform. In regulated industries such as financial services, pharmaceutical and energy, those disruptions can quickly move beyond the IT team. They can create compliance failures, audit findings, operational disruption and exposure to significant financial penalties — turning platform change into a balance sheet risk.
That makes regression testing — the process of validating that existing workflows still perform as expected after a change — far more than a technical checkpoint. It is becoming one of the critical controls that determines whether organisations can release change safely.
The risk hiding in plain sight
Most business leaders are focused on the productivity gains from AI: faster development, greater output and lower costs. Fewer are focused on what happens when that productivity creates a volume of change that existing quality and governance processes cannot safely absorb.
For many organisations, regression testing is still heavily manual. Teams of engineers spend days or weeks methodically validating that workflows, integrations and controls still function correctly after each release. One global technology company required 15 testers working for more than three weeks, over 225 person-days, just to validate a single platform upgrade.
That model was always slow and expensive. In an AI-accelerated world, it becomes a critical vulnerability.
Yet most organisations still treat testing as a project activity, carried out at the end of a release cycle by teams working against tight deadlines, with documentation often produced after the fact. When AI is compressing development timelines from weeks to hours, that model does not hold.
In regulated industries, a failed deployment is not just a technical problem. It can trigger compliance failures, audit findings, enforcement action and operational disruption that far outweigh the cost of the original change. This is where enterprise change stops being an IT issue and starts becoming a material business risk.
When testing becomes the bottleneck
In practice, this often leads teams to delay releases and defer upgrades. Technical debt accumulates, and organisations that invested in AI to move faster find themselves moving at exactly the same speed as before, just with a larger backlog and greater underlying risk.
The problem is not simply that manual testing takes too long. It is that it forces organisations into a trade-off between speed and control. Move too quickly, and they risk releasing untested change into critical business systems. Move too slowly, and the value of AI-enabled development is lost before it reaches the business.
In many companies, the time saved in development is simply lost again in testing and governance.
From manual testing to automated validation
This is the problem AutomatePro was built to solve.
AutomatePro automates the ServiceNow release lifecycle, bringing planning, testing, deployments and documentation together in one connected platform so teams can run regression cycles at speed, maintain control from requirement through to release, and produce the compliance evidence auditors require without weeks of manual effort.
The results are not marginal. Across AutomatePro’s customer base, regression testing effort has been reduced by up to 99%, freeing teams to validate more change without adding more manual effort. A global pharmaceutical customer achieved a 76% increase in test coverage alongside a 73% reduction in defects. A major international investment bank increased developer productivity by 27% within three months of implementation, moving from fixed release schedules to a release-when-ready model while achieving 100% release success.
From balance sheet risk to business confidence
Enterprise release cycles are only going to become faster from here. The organisations that treat testing, validation and audit evidence as strategic risk management capabilities, rather than project costs, will be the ones able to manage that acceleration with confidence.
Those that do not will face a different kind of AI problem: not the cost of deploying AI, but the cost of deploying what AI produces without the controls needed to protect the business.
That is why enterprise change is becoming a balance sheet issue. Failed releases, delayed upgrades, compliance gaps and audit findings all carry financial consequences, whether through direct penalties, operational disruption, wasted engineering time or lost confidence in the platforms organisations depend on.
The winners in the AI era will not simply be the organisations that can generate new ideas, workflows or code the fastest. They will be the ones that can govern and release them with confidence.
That is the capability AutomatePro helps enterprises build: the ability to move faster without losing control.
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Author Bio
Jessica Leyshon is Chief Marketing Officer at AutomatePro, with over a decade of experience
driving growth in B2B SaaS. Previously a Marketing Director at Sage, she has also worked as a journalist at The Guardian, led digital at the UK Treasury, and recently completed an MBA after winning the Financial Times Women in Leadership competition.
