In the debate on IT innovation, attention is often focused on technology: new tools in constant evolution, increasingly sophisticated algorithms, automation solutions, artificial intelligence. All fundamental.
However, too often, a crucial element is overlooked. Probably the most important one. People.
There is no innovation without the human factor. And today, in a hyper-technological era, this truth remains even more solid.
More specifically, the adoption of Artificial Intelligence systems in IT operations is an unprecedented organizational and cultural challenge, requiring teams that are ready, trained, not fossilized, capable of collaborating with new tools and adapting to rapidly evolving processes.
This is why IT team readiness – preparation, continuous training, adaptability – is the cornerstone for successfully implementing AI-powered support operations.
In this article, therefore, we will explore how IT and HR leaders can collaborate to build solid teams, suited to the present and the future. And how they can (and must) do so by combining skills, strategic vision, and cutting-edge technological solutions.
AI and Automation in IT Support: A Rapidly Evolving Scenario
In recent years, the adoption of technologies based on artificial intelligence has profoundly transformed the way all IT processes are managed, particularly support activities. We know this well and the examples are numerous. From automatic ticket classification to the use of 24/7 active chatbots, to predictive systems capable of anticipating incidents before they occur, AI is progressively modifying the logic of Help Desk and IT Service Management.
Be careful, though! These tools are not limited to “speeding up” what already existed. Rather, they introduce new possibilities, redefining roles, processes, and relationships between human teams and digital technologies. The decisive shift is from a reactive logic to a predictive and proactive logic. It’s not just a technological shift; it’s a shift in business mentality.
A true revolution that cannot be addressed with traditional approaches. A profound change in skills, organizational culture, and the ability of IT teams to interpret their role in a new way is needed.
To truly exploit the potential of AI, in short, it is necessary to invest in the human factor: knowledge, collaboration, adaptability, continuous training. And below we see how to do this, concretely. And where to start.
The Starting Point: Assessing IT Team Readiness
First of all, it’s about being clear-sighted. Having a broad and “ruthless” awareness of the starting point. How ready is your team to interface with automated systems? What skills are missing? What cultural or organizational barriers could slow down adoption?
Here are some decisive aspects to consider in order to best assess IT team readiness:
- Digital skills: basic knowledge of AI applications, Machine Learning, and automation technologies. You don’t need to be a data scientist, but it’s essential to master the key concepts, operating logic, and possibilities offered by these tools.
- Soft skills: Artificial Intelligence does not replace the human capacity to adapt, solve problems, and work as a team. On the contrary, it increases its value. Adaptability to change, critical thinking, and the ability to communicate in interdisciplinary contexts are skills that today are even more decisive than in the past.
- Previous experience: familiarity with tools such as ITSM software, RPA systems, or corporate chatbots represents an important foundation for accelerating the transition. It’s not just a technical matter, but also one of awareness of the operational context in which the new AI solutions are inserted.
- Mindset: finally, the broadest and most important point. A team that welcomes change with a constructive spirit is a team ready for the future. Curiosity, desire to learn, initiative, and willingness to experiment are essential traits of all this. AI is not the end of human work, but its evolution: mindset makes all the difference.
Training and Upskilling: From Traditional IT to AI-Augmented Support
So, first you assess IT team readiness. Then you move on to AI training.
Translation: it’s about putting in place team training that must be based on the starting situation; and that must be – above all – continuous…because updates on the technological front are continuous. How to do this, concretely? What topics to focus on?
- Basic concepts of AI and automation.
Let’s start with something that is too often taken for granted. We often tell ourselves that the future is Artificial Intelligence, but do we really know what we’re talking about? It’s not about becoming specialists, but a basic knowledge of how the algorithms that govern AI work and what its practical applications are in the IT field is essential. Without excluding an always fruitful reflection on ethical and operational limits. - Tool usage.
Naturally, training cannot stop at theory. You need to practice concretely on real platforms, test scenarios, learn to configure automated flows, intervene in case of error. Familiarity with the interfaces of different tools and the ability to solve practical problems independently is a crucial point for operational efficiency. - Data analysis and decision making.
Knowing how to read dashboards, reports, predictive signals: here’s another absolutely crucial aspect. AI produces a large amount of data that can guide decisions, but only if the team is able to interpret it. It is therefore important to also train in basic statistical logic, comparative analysis, and data visualization techniques. - Human-machine collaboration.
Chatbots and virtual agents are not simple substitutes, but extensions of human work. Teams must learn to dialogue with these systems, understand when to rely on them and when to intervene.
The final result? Optimization of the user experience, thanks to a fluid integration between artificial intelligence and human intelligence. And it is from here that a virtuous spiral is triggered, which from the improvement of the quality of the work experience, expands to customer satisfaction and, ultimately, to the increase in the loyalty rate for the company.
Pay attention to a very important aspect. It is important to integrate these contents into internal training programs, with personalized paths according to roles (first-level operators, specialists, managers). The support of external technology partners can be crucial at this stage.
Redefining Roles: From Managers to Orchestrators
Assessment. Training. Then: re-definition of structure. With the shift to Artificial Intelligence, in fact, roles within the IT team change.
The most repetitive activities are absorbed by intelligent systems, and IT professionals find themselves managing more analytical, decisional, and strategic tasks. This is right. And it’s better for everyone, once normal initial resistance is overcome.
However, even in this case, let’s not limit ourselves to slogans and look at some scenarios that are already very common today.
- From Help desk agent to Automation supervisor: the traditional first-level operator now assumes a more strategic role. In addition to monitoring automated flows, they must intervene promptly in case of errors or deviations, report inefficiencies, and contribute to the continuous improvement of workflows. Consequently, it is important to acquire operational knowledge of automation tools and a strong ability to identify different types of errors and incidents.
- From Incident manager to Data-driven problem solver. What until yesterday was the person responsible for incident management, today becomes a key figure in predictive analysis. It’s about using intelligent dashboards and AI tools to prevent problems before they occur, analyzing patterns, correlations, and anomalies. Their work, in short, is increasingly oriented toward prevention rather than just response.
- From Service manager to Orchestrator of digital ecosystems. We come to the last step. The overall vision is fundamental. It is therefore crucial to have (and train) people capable of coordinating the interaction between different AI systems, business processes, and the teams involved. Not only that. It’s about defining policies, governing compliance, optimizing flows, and ensuring that technology is truly at the service of IT service quality.
These are just three examples among many possible ones. Three transformations within a macro-transformation in constant evolution.
And it is natural, in such a scenario, that there is also a need to update the identification of objectives and KPIs…with the related measurement systems.
A key point, this, to close the circle of IT team readiness. Or, even better, to trigger the virtuous circle of a readiness that is not achieved once and for all, but adapts to evolutions as quickly and elastically as possible.
Conclusion
IT team readiness for AI-powered operations is not built in a day, but represents a long-term strategic investment. The technologies are there – and they are ready to make a difference – but prepared, trained, and motivated human capital is needed.
Collaboration between CIO, HR, operational teams, and technology partners is the true lever that allows us to fully seize the opportunities offered by AI.
The most powerful means are not enough to win market challenges. We need people capable of interpreting their role with flexibility, with the awareness of being part of an organism in constant evolution.
FAQ
What are the main advantages of adopting AI in IT support? Reduction of response times and operational costs. Improvement of user experience. Automation of repetitive and low-value processes.
What is meant by “IT team readiness”? It is the measure of the IT team’s preparation to adopt and integrate AI and automation tools into their daily processes.
How can you start a readiness journey in a company? Starting from an internal skills assessment, followed by a targeted training plan, with continuous support for transformation. Up to the identification of new objectives and KPIs.