Can AI replace an employee: what tasks is artificial intelligence already performing

Short answer is: artificial intelligence is already taking over specific tasks, and does so better than humans in terms of speed and cost. But replacing an employee entirely is another matter. A call centre operator who spends all day answering the same questions – yes, AI is already handling that job today. A key account manager who conducts complex negotiations and builds relationships – no, AI isn’t doing that yet. In this article, we’ll break it down without beating about the bush: what AI is actually doing instead of people right now, and where the line is beyond which humans remain irreplaceable.

What tasks is AI already performing instead of employees?

We deliberately talk about tasks rather than professions, because most roles consist of different types of work, some of which AI is already handling today, and some of which it isn’t.

Processing incoming enquiries

AI answers standard customer queries via chat, email and messaging apps 24/7, without interruption, instantly. In projects that have been launched, AI has independently handled between 55% and 70% of incoming enquiries without passing them on to a manager. This is not a chatbot; it is an agent that understands open-ended questions, finds the answer in the knowledge base and responds in a human-like manner.

Initial lead qualification

The AI asks qualifying questions, assesses the customer’s intent, determines their budget and urgency, and forwards only those who are genuinely ready to buy to a manager. In business, this reduces the time managers spend on ‘cold’ calls from 40% of their working hours to 12%.

Drafting documents and letters

The AI generates commercial proposals based on templates, replies to incoming emails, standard-form contracts and reports based on CRM data in a matter of seconds. It’s not perfect, but it’s good enough for 80% of cases where a draft is needed rather than a masterpiece. The manager simply checks them and sends them off, rather than writing from scratch.

Classification and routing

Is an incoming email a complaint or a query? Is the enquiry urgent or can it wait? Who should it be forwarded to – sales or support? AI does this instantly and more accurately than a human who is tired by the end of the day. This is particularly valuable when dealing with a high volume of enquiries.

Data monitoring and analytics

AI continuously monitors metrics: sales, stock levels, customer behaviour, financial indicators, and flags any anomalies. An analyst who used to produce such a report once a week now receives a notification the moment something goes wrong.

Routine content

Product descriptions for catalogues, social media posts based on briefs, basic website copy – AI generates initial drafts quickly. The editor simply needs to refine the result. This isn’t a replacement for a copywriter on complex tasks, but the savings on high-volume routine content are significant.

In the projects we have implemented, AI has not ‘replaced’ a single person. However, in several companies, it has made it possible to avoid hiring additional staff despite an increase in workload, which in practice amounts to the same thing in terms of the wage bill.

How it works in practice: a technical perspective

Most text processing tasks are built on a combination of a language model (GPT-4o, Claude, Gemini) and the company’s knowledge base. The model doesn’t know your business; it searches the knowledge base for the relevant information with every query and generates a response. The quality of the response depends directly on the quality of the knowledge base. A poorly written FAQ yields poor answers, even with the most powerful model.

AI becomes truly useful when it can not only speak but also act: create deals in CRM, check balances in 1C, send emails, and set tasks. This is achieved through tools that the agent can call upon. The more integrations, the broader the agent’s capabilities.

Most operational systems use a human-in-the-loop model: the AI performs a task, and a human checks the result or confirms the action before it is executed. This architectural solution makes the system reliable and allows for the gradual expansion of autonomy as trust in the agent grows.

Where AI does not yet replace humans

Complex negotiations and sales to major clients.

Closing a €50,000 deal with a client who is hesitant, works with several suppliers and demands individual terms is a skill built on experience, intuition and the ability to read people. AI can prepare data for negotiations, remind you to follow up and draft a letter. But there must be a human being at the negotiating table.

Crisis communications

When something goes seriously wrong (a delay in a major delivery, an error with client data, a public scandal), you need a person who takes responsibility and speaks on behalf of the company. AI in this role destroys trust faster than it builds it.

High-calibre creative work

AI generates content quickly. But an advertising campaign that changes brand perception, a product design that becomes iconic, a strategy that opens up a new market – these are still the work of people. AI is good as a tool in the hands of a person with a vision, but not as a substitute for that vision.

Team management and motivation

Understanding why a good employee has started performing less well. Having a difficult conversation about a change in role. Creating an atmosphere in which people want to give their all. AI cannot do this, and is unlikely to learn to do so in the coming years in a way that matters to business.

Tasks with high stakes and legal liability

Legal opinions, medical decisions, financial recommendations with real-world liability – here, AI can be a tool to assist, but not a replacement. Not because it isn’t smart enough, but because responsibility cannot be delegated to a computer.

Practical advice: how to assess what should be handed over to AI

Ask yourself three questions about each task.

First: does this task recur more than five times a day? Second: can it be described using clear rules or examples? Third: is the cost of error not critical or easily rectifiable? If the answer is ‘yes’ to all three, the task is a candidate for delegation to AI. If the answer is ‘no’ to even one, it is worth thinking twice.

Don’t lay off staff until you’ve tested the hypothesis.

A common mistake: announcing automation, cutting staff, and then discovering that the AI performs worse than expected. The correct sequence: implement, measure, verify, and only then make staffing decisions. The best-case scenario for the business is not to let go of good, loyal employees, but to redistribute the workload. People should be doing more complex and valuable work.

Start with the tasks that annoy employees.

Monotonous, repetitive tasks wear people down and reduce the quality of work by the end of the day. When AI takes over precisely these tasks, employees see it not as a threat, but as a help. This changes attitudes towards implementation within the team.

Measure not only savings, but also quality.

AI may respond faster, but less accurately. Or correctly, but coldly, so that the customer leaves dissatisfied, even though the issue has been technically resolved. Metrics for task performance should include customer satisfaction, the percentage of escalations, and repeat enquiries on the same topic. These are essential alongside metrics for speed and cost.

Frequently asked questions

Will AI replace my profession?

It is more likely to change it than replace it. And this is already happening. An accountant who knows how to work with AI tools can do in a day what used to take a week. The profession isn’t disappearing, but what people are paid for within it is changing.

How reliable is AI when working with clients?

It depends on the architecture. AI can confidently say the wrong things; this is called hallucination. When working with clients, this needs to be controlled: a rigid knowledge base, a limited scope of responses, and mandatory escalation in case of uncertainty. A well-designed agent is reliable; a poorly designed one is dangerous for your reputation.

AI will continue to develop. Should we implement it now or wait?

Companies that started a year ago already have a year’s experience and know exactly what works in their business and what doesn’t, and how to train agents using real-world data. The technology is improving, but implementation experience is only gained through the process. The best time to start is now.

How do we explain to staff that we are implementing AI?

Be honest and specific: exactly what tasks the AI will take on, what this means for their work, and what will change. If the AI frees them from routine tasks, show them what they’ll have time for. If staff changes are inevitable, it’s better to say so directly and in advance than to cause anxiety through uncertainty.

Conclusion

AI is already taking over specific tasks, and does so effectively where work is repetitive, data is structured, and the cost of error is tolerable. Processing incoming data, qualifying leads, drafting documents, monitoring data – AI performs all of these tasks today, without days off and without tiring. Whether it can replace an employee entirely is another matter. Most roles involve a mix of tasks: some AI handles perfectly, others partially, and others it cannot do at all yet. The real benefit of AI comes not when it is pitted against people, but when work is organised so that everyone does what they do best.

 

Author of the article:

Anton Kucher, Managing Partner at Meta-Sistem

Experience: over 10 years in website and web system development

Specialisation: website and web application development, integration and business process automation

Author profile:

LinkedIn: https://www.linkedin.com/in/anton-cucer/

Meta-Sistem: https://meta-sistem.md