The question is not whether training is needed to digitize a company, but how much and for whom. Many organizations make the mistake of measuring digitalization by the number of tools purchased, when the real result depends on people using them with judgment. An excellent software package, poorly adopted, generates cost and friction; the same software, supported by a suitable training plan, multiplies productivity.
There is no single answer. It depends on the scope of the project, the digital maturity of the team, the sector, the number of processes affected and the organization's capacity for change. An online store that digitalizes its invoicing does not need the same training as a hospital implementing an integrated management system. Therefore, before setting training hours, it is necessary to define which processes will be digitized and what concrete skills each position requires.
When a company invests in custom software, training becomes more natural. The screens, flows and messages are designed to fit the way each team works. It is not about learning to use a generic product, but about internalizing a tool that already understands the operation. Even so, it is advisable to spend time simulating real cases, resolving questions about exceptions and practicing with non-production data.
In addition, initial training must go hand in hand with a communication strategy. Teams need to understand why their way of working is changing, what benefits the change brings and what is expected of them. When transformation is explained with transparency, resistance decreases and adoption accelerates. This often ignored aspect has more impact on the outcome than the number of courses scheduled.
It is also worth distinguishing between initial training and continuous training. The former makes it possible to start; the latter ensures that digitalization does not stop. People change roles, processes are updated, customers present new scenarios. A well-designed training program includes reinforcement sessions, quick-reference materials and spaces where users can ask questions confidently.
By profile, the minimum training is unevenly distributed. Operational staff need to understand daily tasks: entering data, validating states, consulting information. A team leader must be able to read indicators, detect bottlenecks and decide when to escalate. The system administrator, for its part, needs a deeper technical view: permission management, integrations, backups, monitoring. And management does not need to handle every button, but it does need to interpret the dashboard to make decisions.
Many companies underestimate the learning time of middle managers. A supervisor who does not understand the new flow cannot help the team, and their own insecurity becomes an obstacle. Leaders must be trained before the rest, so that they can act as references during implementation.
If digitalization includes migration to cloud infrastructure, the level of demand increases. Working with AWS/Azure cloud involves understanding concepts such as regions, identities, budgets and access policies. It is not enough for the technical department to know this; area managers must also understand how information is protected and what implications sharing data with an external provider has. The cloud is not only a technological decision; it is also an organizational competency.
This is where cybersecurity comes in as a training pillar. Every time a company digitizes a process, it expands its exposure surface. A phishing email, a weak password or a shared account can turn a competitive advantage into a serious incident. Training must explain, with familiar examples, how to recognize fraud attempts, why not to reuse passwords and what the correct channel is for reporting an anomaly. Security is not only the responsibility of the technical area.
Moreover, cybersecurity must be worked on from day one and updated regularly. Threats evolve, and training cannot remain anchored in an annual session. It is advisable to include phishing simulations, real incident examples and brief reminders within the workflow itself.
Another training dimension is data analysis. A company that decides to take advantage of its information with BI/Power BI tools needs more than courses on how to create charts. It needs to develop criteria for knowing which metric matters, how to read trends and when a variation is relevant. Business intelligence training must connect reports with company objectives; otherwise, the dashboard becomes a theoretical exercise.
The arrival of artificial intelligence and AI agents adds a new layer. These systems can automate tasks, classify documents, answer questions or recommend actions. But they require supervision, judgment and the definition of limits. Users must know what kind of instructions they can give, when to review the result and what data can be used to train models. AI training is not only technical; it is above all cultural and ethical.
To take full advantage of AI, it is also a good idea to appoint internal references. A small team of advanced users can resolve doubts, propose new use cases and help maintain consistency of criteria. These references need specific training and time to support the rest without neglecting their usual responsibilities.
In practice, a reasonable plan can combine synchronous sessions, asynchronous micro-lessons, test-environment labs and certifications for advanced users. The goal is not to accumulate hours, but to guarantee minimum competencies. Some organizations achieve excellent adoption with fewer than ten hours per person, spread over several weeks. Others need a longer itinerary because the transformation affects many departments or because staff turnover is high.
Q2BSTUDIO, a software and technology development company, understands training as part of the project, not as a later addition. When designing a solution, user profiles, critical flows and recurring decisions are defined. That information makes it possible to build a tailored training program, including manuals, videos, workshops and support sessions. Guides are also prepared for internal trainers, making it easier to scale knowledge without always relying on external consultants.
Another aspect to anticipate is the arrival of new people. Sustainable digitalization includes a clear onboarding process so that a new employee can reach the necessary level without blocking the team. Short videos, visual guides and a practice environment are resources that make this stage much easier. Documentation must stay up to date, close to the tool, and be written in the language of the business, not in technical jargon.
There is also a need to talk about unlearning. Some analog habits, such as asking for confirmation on paper or duplicating records in a spreadsheet, can survive digitalization and hinder the process. Users need to understand why the old practice is abandoned and what the new correct path is. That conceptual change is not achieved with a manual; it requires communication, leadership and examples of internal success.
In short, how much training is needed to digitize a company has no magic number. It depends on the complexity of the change, the profiles and the organizational culture. Without training, technology remains underused; with too much generic training, time and motivation are lost. The balance lies in designing practical itineraries oriented to real work and based on usage data. Technology is the vehicle, but people are the ones driving it.
