Four of the most surprising stats from the 2025 Process Optimization Report: IT Edition

Our annual Process Optimization Report gives us the opportunity to talk to business leaders across the globe about their priorities and preoccupations, as well as the direction their organizations are taking. And our department-specific editions go even deeper into the issues impacting individual functions.

For this year’s IT edition, we surveyed 411 senior IT leaders to find out how they’re using emerging tech like AI and automation, how they’re optimizing tech stacks for the modern age, and how they’re preparing for large-scale system transformations.

Here are four findings that really got us thinking.

1. 90% of IT leaders are concerned about enterprise AI

IT leaders identify implementing AI (along with automation and analytics) as their biggest strategic opportunity. But at the same time, 90% express concerns about the growing use of AI in their organization. The real surprise here is that this figure isn’t closer to 100%. We’d love to discover the secret behind the confidence of the 10% who aren’t concerned!

Among those who do have concerns about AI, IT leaders are most worried about its security implications, the skills gaps they’ll need to overcome to make the most of it, and whether or not they’ll be able to demonstrate ROI.

Interestingly, process shortcomings come low on the list of concerns, suggesting IT leaders don’t yet fully appreciate the importance of optimized processes to effective AI deployment.

2. 72% say system migrations always take longer than expected

Okay, so maybe it’s not such a surprise that almost 3/4 of IT leaders say system migrations always take longer than planned. More unexpected: when asked about their success criteria for system migrations, delivering the project on time came bottom of the list.

So have IT leaders accepted that delays are inevitable?

With major modernization projects like the migration to SAP S/4HANA or Oracle Fusion on the horizon, businesses really can’t afford the operational disruption that delays and excessive downtime can bring. If IT leaders use technologies like Process Intelligence to understand how the processes involved in migrations work, these projects can be delivered on time, with minimal disruption.

Encouragingly, IT leaders are aware of this potential, with 89% saying they need to understand how processes work to embark on a successful system transformation.

3. Cost matters less than value in SaaS tool choice

A massive 86% of IT leaders say consolidation to reduce the enterprise’s number of SaaS tools is a high priority. But how do they decide which tools to use?

The most important criteria for keeping or selecting a tool, according to the report, is the amount of value it can deliver against a specific need. This is followed closely by speed to ROI, how much the tool will simplify how teams work, and how secure it will be.

The three least important factors are how much the tool will be used, how others in the industry are using it, and how much it will cost – all of which non-IT people might expect to have a greater influence on purchase decisions for SaaS applications than they do.

4. 75% aren’t maximizing the potential of tech investments

We asked IT leaders to describe their current tech stack, and only 25% say it’s fully connected and working seamlessly.

The rest are likely struggling with tech-stack complexity, legacy technology, and siloed systems that don’t talk to one another — all of which make it difficult to effectively integrate new technologies like AI, and to prepare for those systems migration initiatives mentioned earlier. A huge 87% of IT leaders say they need to better understand how technologies are being used across their organization so they can make the right investment decisions.

For these IT leaders, the Celonis Process Intelligence Platform can be the missing piece of the tech stack. System agnostic and without bias, it provides a common language between systems and processes, and between IT and the business. It allows IT leaders to understand exactly how, when, and where systems are being used throughout the enterprise. And it maximizes IT investments without disrupting or replacing existing systems – layering on top of those systems to feed process insights to emerging technologies like AI.