You’ll Stay – the Robot Will Replace You: How to Implement AI in Your Company

When the American company OpenAI released the ChatGPT chatbot for global use at the end of 2022, it quite literally changed the world. At the time, it was still a non-profit organization; today, it is a giant gradually heading toward a stock market listing. OpenAI was originally meant to be a non-profit that put ethics and safety first. However, in the pursuit of profit, its CEO Sam Altman pushed those original standards aside, a Vox analysis warned.

This more or less illustrates the path AI has taken over the past two years. What started as a tool for technology enthusiasts has become a powerful player reshaping business strategies across companies. Organizations are using AI to cut costs and accelerate their development.

However, a rushed implementation of artificial intelligence can cause chaos in the workplace. The process of introducing AI should therefore be systematic, ethical, and sustainable. Tereza Kundert Silbernáglová, an expert in AI and HR technologies, and sourcer Kristina Shershun share advice on how to approach it.

What to keep in mind when implementing AI?

First and foremost, it is important to realize that implementing artificial intelligence in companies is a serious task. Simply starting to use AI tools is not the same as installing a new piece of software on company computers. Employees will ask whether AI is meant to help them grow professionally – or replace them. Communication is therefore the foundation of any successful implementation.

Prepare employees for change

When introducing AI in companies, employees must be involved in the entire process. Presenting them with a fait accompli benefits neither workplace morale nor company growth.

“Proper communication with employees and preparing the work environment for this implementation is crucial. Employees should understand that AI tools are not meant to replace them, but to help them work more efficiently. Employees should be properly trained before implementation begins, ideally with the help of a specialized expert. In addition to active communication at the start of implementation, it is also necessary to communicate all changes throughout the process and to maintain employees’ interest and ongoing education,” Silbernáglová recommends.

Shershun also agrees that AI is here to replace processes, not employees. However, less qualified workers should be aware that if they are unwilling to adapt to the coming changes, workforce reductions may eventually affect them.

“Start with a process analysis to identify the areas where artificial intelligence will bring the most value. It usually makes sense to begin with routine administrative tasks that are relatively simple but time-consuming or require a lot of manual work – such as basic data handling, attendance tracking, or creating certain templates,” the sourcer advises.

“Proceed step by step, create a pilot project, monitor the results, and scale them accordingly. Ensure proper training. Choose an ‘AI champion’ – someone who understands internal processes well and can help coordinate the integration of AI with existing systems and workflows,” she adds.

Handle data responsibly

Developers of artificial intelligence tools are often criticized for training their applications unethically on stolen data. After all, the larger an AI product’s database, the more convincingly it can perform its tasks. When it comes to company data, however, no one wants it shared.

“When implementing AI, it’s essential to understand the rules for working with the data you input. If we’re talking about free tools, there is an almost 100% certainty that anyone else can access the data you enter – so confidential data should never be uploaded. We certainly don’t want the Excel spreadsheet we used to prepare data for an annual performance presentation to suddenly appear at a competitor’s,” warned Silbernáglová, an expert in AI and HR technologies.

According to Shershun, how companies will deal with the ethical aspects of AI in practice will only become clear over the coming years as appropriate regulation develops. Even now, however, managers can save themselves many future headaches.

“When discussing AI solutions with a vendor, don’t forget to examine their data protection policies. Ask where they obtain their training data and how they approach ethics in general. Continuously monitor AI systems and legislative developments to prevent discrimination or unethical practices,” the sourcer said.

Address cybersecurity and regulation

The regulatory framework is the third major area companies must consider when implementing AI. Artificial intelligence entered society at such speed that legislation is being adopted with significant delays. Last year, the European Union approved the first major regulatory package for AI – the AI Act – which addresses, among other things, discrimination and the responsible use of artificial intelligence with regard to the environment. It is therefore essential to monitor this regulation and incorporate it into the implementation process.

In terms of data protection, companies must also secure their own systems in which AI is used. Sensitive data transmitted over the internet can easily become a target for attackers.

“Once we have prepared the ground for AI implementation, trained our employees in its use, and ensured they know how to work with input data – and verify received information – it is also necessary to secure the system itself. AI systems can be vulnerable to cyberattacks or technical failures. That’s why ensuring their security and robustness is crucial. High-quality protection of AI technologies helps prevent potential attacks or data loss,” Silbernáglová explains.

How to find the right balance?

Companies that become enthusiastic about artificial intelligence sometimes tend to use AI in every area of work – even where it makes little sense. This can understandably alarm employees. Artificial intelligence is primarily effective for repetitive, predictive, and data-intensive tasks, while people remain essential for creativity, strategy, and decision-making in uncertain situations.

“To ensure a balance between AI efficiency and the human approach in communication, creativity, and empathetic problem-solving, it makes sense to identify which processes in the company are currently inefficient and explore whether they can be addressed through AI automation or by supplementing human skills that are currently missing in the team,” Shershun explained.

“Another good approach is to focus on the strengths of team members, let them do what they do best, and use AI for the rest where possible. In practice, however, this is not so easy. If we take recruitment as an example, we would let recruiters focus on building authentic relationships with candidates and hiring managers, while automating processes such as interview coordination, writing interview notes, or creating job ad content. Finding the right balance will require experimentation, trial, and error,” the expert concluded.

AI implementation should therefore not resemble a sprint. It is a complex and endurance-based endeavor, complicated by the constant emergence of new AI tools and fresh regulation. Only through thoughtful and measured implementation can companies ensure that employees buy into the process – and don’t leave long before any robotic tool could theoretically replace them.

^{Taken from Management News, 6.1. 2026}