The automation of intellectual work has entered a new phase. It no longer applies exclusively to repetitive back-office processes but increasingly supports analytical, communication, and decision-making tasks. In practice, this means a shift from simple workflow tools to “copilot”-type solutions that provide suggestions, generate content, organize data, and reduce task completion times across multiple departments simultaneously.

An analysis prepared by PMR Market Experts identifies the main areas of spending, barriers, and recommendations. For companies operating in Poland, the key question is no longer whether to automate, but where the pace of change is fastest and which organizational functions stand to gain the most from it. From a management perspective, this is important because different departments have distinct data profiles, varying levels of process maturity, and different implementation risks. That is precisely why it is worth viewing automation not as a technological fad, but as a tool that boosts productivity, decision quality, and operational predictability.

Why is Copilot Economy gaining momentum right now?

Solutions based on generative AI and digital work assistants are evolving faster than previous waves of automation because they address a very specific business need—reducing the time spent on routine tasks while increasing the scale of team operations. This is especially true for organizations that handle large volumes of documents, inquiries, reports, and data scattered across various systems.

This acceleration is also driven by the maturation of the tooling ecosystem. An increasing number of solutions can be implemented in phases, without a complete overhaul of the IT architecture. As a result, companies start with individual processes and only later expand their use to additional functions. This model reduces risk and makes it easier to assess the actual business value.

In Polish analyses, research conducted by, among others, independent research centers and analytical firms can be helpful. In market practice, however, it remains essential to combine quantitative data with observations of internal processes, since the pace of automation depends not only on technology but also on organizational culture and data quality.

Which departments are automating the fastest?

The pace of automation varies from department to department, so it’s worth taking a closer look at which areas are seeing the fastest tangible results from AI implementations.

Is customer service still the clear leader?

Customer service is one of the departments that is being automated the fastest, as it handles a high volume of repetitive interactions. AI assistants help classify inquiries, suggest responses, summarize the contact history, and help route cases to the appropriate teams. This is an area where the benefits are quickly apparent to both the organization and the customer.

The strength of this section lies in the relatively easy mapping of processes. Typical request scenarios can be described using rules, and the input data is usually partially structured. As a result, implementations can start with simple applications, such as consultant support, before moving on to more advanced automation.

Implementations yield the best results when clear boundaries of responsibility are established between humans and tools. A copilot should not replace human judgment in non-standard situations, but it can very effectively reduce response times and improve the consistency of communication.

Why are marketing and sales teams adopting copilot tools so quickly?

Marketing and sales are areas particularly well-suited for automation, as they require rapid content creation, audience segmentation, lead analysis, and personalized communication. AI assistants help prepare offers, meeting summaries, campaign proposals, and analyses of campaign effectiveness. For sales teams, this means the ability to shift resources from administrative tasks to working directly with clients.

This is also an area where implementation doesn’t have to start with deep system integration. Many applications can be launched using everyday work tools, which lowers the barrier to entry and accelerates adoption. As a result, marketing and sales often serve as a testing ground for further implementations in other departments.

Industry reports are helpful in assessing the potential of this area, as they allow for a comparison of trends in sales channels, customer behavior, and companies’ investment priorities across specific sectors.

Are finance and controlling really ready for widespread automation?

The finance sector is automating at a slightly more cautious pace than customer service or marketing, but the pace of change is clearly accelerating. This is due to the high value of data, the need for regulatory compliance, and strong pressure to ensure the quality and auditability of processes. Copilot-type tools support data reconciliation, variance analysis, adding comments to results, and working with financial documents.

The greatest potential lies in situations where the process is repeatable and the data comes from multiple sources. Under such conditions, a digital assistant can significantly speed up the preparation of management analyses and reduce the number of errors resulting from manual work on spreadsheets. However, robust access control and quality assurance for the model’s outputs remain essential.

In this area, it is particularly important to distinguish between the automation of data preparation and the automation of the decision itself. In finance, technology works best as a support for experts, not as a substitute for managerial responsibility.

How quickly are HR and administration changing?

HR and administration are among the departments that benefit from automation due to the large number of tasks involving documents, internal communication, and standardized procedures. AI assists with drafting job postings, organizing applications, preparing onboarding materials, answering employee questions, and creating summaries of policies and regulations.

One advantage of this approach is the ability to quickly test solutions on processes with limited business risk. At the same time, HR must pay particular attention to issues of confidentiality, personal data, and the risk of replicating biases present in training data or historical decisions.

Organizations that view HR automation as a way to improve the employee experience—rather than merely as a means to reduce administrative workload—benefit the most. This approach increases acceptance of the changes and facilitates broader implementation of copilots throughout the company.

What determines the pace of automation in individual departments?

Not every department automates at the same pace, even if it uses similar tools. The pace of implementation is determined primarily by data quality, the degree of process standardization, the ease of measuring results, and the level of operational and regulatory risk. The more organized the work environment, the faster scalable results can be achieved.

The readiness of middle managers is also important. It is at this level that the decision is most often made as to whether a tool will provide real support for work or remain an accessory used only occasionally. Therefore, successful implementations combine technology with process redesign and a clear accountability model, which in practice translates into the following relationships:

• The easiest processes to automate are those that are frequent, repetitive, and based on text or tabular data,
• Quick results are achieved in areas where time savings or quality improvements can be easily measured,
• Areas involving high legal, reputational, or decision-making risks change more slowly,
• The barrier is not only technology, but also the lack of a process owner and poor data quality.

How can we determine where it makes the most sense to implement copilots today?

The most useful approach is to evaluate processes in terms of business value and feasibility. First, it’s a good idea to identify tasks that are time-consuming, amenable to standardization, and do not require the tool to operate fully autonomously. In practice, these are often areas related to content preparation, information analysis, and handling internal or external inquiries.

Before implementation, several questions need to be answered: What problem needs to be solved? Who will be using the tool? What data is needed? And how will the impact be measured? Without such an assessment, even a promising solution may not yield lasting results; therefore, before implementation, it is advisable to:

1. map out the process and identify the most time-consuming steps,
2. Choose one measurable use case to start with,
3. establish rules for oversight, data security, and acceptance of results,
4. test the solution in a short pilot program,
5. Compare the operational benefits with the implementation and maintenance costs.

Market forecasts can be useful when planning such initiatives, especially when the decision to automate involves restructuring the operational model, changes in staffing, or entering a new phase of technological competition.

What risks most often slow down implementations?

The most commonly cited risk is poor-quality input data. The tool may function smoothly from a technical standpoint, but if the organization works with inconsistent documents, scattered repositories, and outdated definitions, the results will not be sufficiently reliable. This is a particularly acute problem in companies that have not previously organized their information on an organization-wide basis.

The second barrier is the lack of a policy governing the use of AI. Without specifying which tasks can be automated, what data may be processed, and who approves the results, employees either avoid using the tools or use them in an uncontrolled manner. In both cases, the company loses potential value.

Organizational risks are also significant:

• overestimating the tool's capabilities and lacking realistic expectations,
• implementation without training and without changing the team's work methods,
• a lack of success metrics at the process level,
• resistance from managers who fear losing control over their tasks.

Key Findings

Today, the departments that are being automated the fastest are those that handle a large number of repetitive interactions, documents, and content—primarily customer service, marketing, sales, administration, and select financial processes. However, this does not mean that a single implementation model will work everywhere. The pace of change depends on data quality, process maturity, and risk level.

From a strategic perspective, the most important step is to move from experimentation to a structured selection of use cases. This is precisely where periodic sector analyses and benchmarking become crucial. PMR Market Experts publishes periodic reports that help assess the direction of change in various industries and better ground technology decisions in the realities of a specific market.

If you need to assess which functions within your organization currently have the greatest potential for implementing copilot-type tools, and how to align automation with business objectives, it’s worth considering consulting services tailored to the specifics of your industry and operational model. To prioritize automation efforts and prepare your company for the next wave of change, contact PMR Market Experts.

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Hume’s Institute stands for knowledge. PMR Market Experts stands for experience. When we join forces, you gain a competitive edge. See how we can support your business.

Hume’s Institute stands for knowledge. PMR Market Experts stands for experience. When we join forces, you gain a competitive edge. See how we can support your business.

Dariusz Śmiejkowski

Chief Executive Officer