What will chanAt Evergo, we regularly talk with organizations navigating growing IT complexity and the expanding use of AI in everyday operations.ge in customer needs in 2026?
This conversation is an attempt to capture the challenges that most often come up in discussions with IT and operations leaders today — and how we look at them through the lens of operational maturity, governance, and long-term accountability for services rather than one-off implementations.
AI is one of the most talked-about topics in IT today. From your perspective, what do organizations most often miss when they start talking about AI?
Most often, they overlook the fact that AI does not operate in isolation.Additionally, siloed thinking limits the broader possibilities of new technologies.
Algorithms cannot compensate for unstable processes, unclear accountability, or immature service management models. Yet in many organizations, AI is still approached as just another project: a tool is selected, a pilot is run, something is “implemented,” and attention moves on.
In reality, AI delivers value only when IT is run as a service — with continuity, predictability, and clear operational responsibility at its core.To bring realvalue with IT solutionsit is necessary to have good collaborationwith business stakeholders.
You often refer to the idea of “Running IT as a Service.” What does this mean in practice — particularly in an environment where AI is becoming part of day-to-day operations?
Running IT as a service means moving away from project-centric thinking. IT is something that operates every dayto deliver IT services, regardless of whether a new technology is being introduced, the architecture is changing, or the organization is scaling.
In the context of AI, this becomes essential. Models, data, and automation require continuous oversight, data quality management, clear rules, and governance. When IT is treated as a collection of initiatives rather than a service, AI quickly loses credibility or creates operational instability instead of support.It is important to not miss end to endview how IT service is working for the business users,what business value they get from IT solutions.
In your writing, you emphasize that AIOps should not be treated as a one-time implementation. Why is this distinction so important for organizations today?
IT environments are not static. Infrastructure evolves, data changes, and organizational models shift over time. AIOps, like any operational capability, must evolve along with them.
When AIOps is treated as a project that can be “completed,” its value erodes quickly. Without continuous attention to data quality, source consistency, and regular model tuning, even the most advanced tools become ineffective. This is another reason why AI requires a service mindset rather than an implementation mindset.
Governance is often perceived as secondary or overly administrative. Why does it become critical once AI starts influencing operational decisions?
Governance is rarely associated with innovation, yet it is fundamental to scaling AI responsibly. It is not about bureaucracy, but about clarity — who owns the data, who makes decisions, how changes are introduced, and how outcomes are measured.
As AI begins to influence operational decisions, the absence of governance becomes a serious risk. Without it, accountability weakens, trust in systems declines, and auditability becomes increasingly difficult.
Looking ahead to 2026, what will become the minimum standard for organizations operating at the intersection of IT and AI?
The minimum will be the ability to run IT in a predictable, responsible, and continuous way, even as automation increases.
AI will no longer be an add-on or an experiment. It will be embedded in everyday operations. Organizations without a mature service management model will struggle to maintain quality, stability, and trust in technology.
Those who succeed will not be the ones who deploy the most AI, but those who combine automation with disciplined, service-oriented IT.
If you had to summarize this entire conversation in one sentence, what would be the key takeaway for business and technology leaders?
Implementation of new IT solutions requiresclose collaboration with business stakeholders and takessometime to get maturity. Additionally, siloed thinking limits the broader possibilities of new technologies.
It is not only installing tools, but alsohow organizations think about responsibility, stability, and long-term value for the business.
Marzena Burakowska
Partner