AI can do the work. Who will earn the money?

At Webiano Digital & Marketing Agency, we use artificial intelligence every day. It helps us with research, content, marketing, technical problems and assignments that would have taken considerably longer only a few years ago. We enjoy working with it, and we are genuinely grateful for what it allows us to accomplish. For a smaller agency, having access to these capabilities is an enormous advantage. We can tackle more demanding projects without needing the resources of a much larger organisation.

But the more we use AI, the more we find ourselves thinking about its consequences beyond our own business. We hear endless discussions about new models, faster systems and companies competing for technological leadership. Meanwhile, a question that could affect almost everyone receives surprisingly little attention. If businesses eventually need substantially fewer people to produce goods and services, how will those people earn the money needed to buy them? We believe AI can make life better. We are far less convinced that society is preparing seriously enough for the changes it may bring.

A morning at Webiano looks different now

We can start the day by giving AI a complicated assignment involving research, analysis and several stages of work across different tools. Depending on the task, it may continue for two or three hours while we concentrate on something else. When we return, a substantial amount of work can already be ready for review. Even now, we are sometimes surprised by how much gets done. We remember very well how long some of those assignments used to take.

Of course, we check the results. AI can misunderstand instructions, overlook important details or confidently recommend something that turns out to be wrong. That matters particularly when working with websites, servers and technical infrastructure, where a poor decision can create problems for clients. Human experience and responsibility remain essential. Still, we cannot ignore how much the process has changed. We are increasingly reviewing work that someone would previously have spent hours producing. And that naturally changes how we think about the value and organisation of human labour.

We can give AI work in the morning that once would have occupied someone for hours. We’re delighted to have that help. But we keep wondering what happens to the people who earned their living doing that work when every business starts making the same calculation. — Jan Bielik, CEO & Founder, Webiano Digital & Marketing Agency

We can barely keep up with the updates

Anyone working with digital technology knows how quickly things are changing. AI systems receive new features, models improve, familiar tools change their behaviour and capabilities that seemed extraordinary a few months ago become part of an ordinary working day. We barely have time to explore one improvement before another arrives. Keeping up requires constant learning, and even when technology is your profession, that can become exhausting.

We experience similar pressure when managing websites, hosting environments and servers. Software updates, security advisories, newly discovered vulnerabilities and compatibility issues require regular attention. We may spend part of a morning checking whether a security warning affects a server, whether a patch is available and whether applying it could interfere with something else. Sometimes the conclusion is that no immediate action is necessary. Reaching that conclusion still takes time and careful checking.

Cybersecurity makes the situation even more demanding. Automated attacks have existed for years, and AI may help attackers operate faster or more effectively in certain circumstances. We have to follow developments, understand the actual risks and avoid making hurried decisions based on alarming headlines. Smaller businesses often face the same categories of threats as large organisations, without having dedicated security teams to investigate every warning or manage every update.

If professionals who work with technology every day already struggle to keep pace with developments, why are we so confident that entire labour markets, education systems and governments will adapt without serious difficulties? Learning a new AI tool is one thing. Restructuring an education system, helping displaced workers or changing how public services are financed is something else entirely. Those processes take years, while the technology can change significantly in a matter of months.

What if companies simply stop hiring?

When people discuss AI replacing workers, they usually imagine companies announcing large-scale layoffs. Those stories attract attention because the consequences are immediate and visible. But we suspect some of the biggest changes will happen much more quietly. Imagine a company employing twenty people whose business is growing. Under normal circumstances, it might recruit another three employees to handle the additional workload. Instead, management introduces AI tools and discovers that the existing team can manage the growth.

A year later, another employee leaves. The company decides not to fill the vacancy because automation can now handle much of the work. Revenue continues to increase, productivity improves and nobody has been dismissed. From the company’s perspective, everything looks healthy. Yet four employment opportunities that might otherwise have existed have disappeared. We may eventually discover that one of AI’s biggest effects on employment was the number of people companies never hired.

This is a possibility that deserves attention before it becomes visible in national employment statistics. A business can grow without creating many new jobs, and thousands of individual decisions can gradually change the labour market. Some companies will use AI to expand into new areas and recruit additional employees. Others will discover that they can achieve their commercial objectives with relatively small teams. Both responses make sense from a business perspective, but their consequences for employment could be very different.

Where will young people get their first experience?

We are particularly concerned about people entering the labour market. Every experienced professional started somewhere. Junior employees learn by completing ordinary assignments, asking questions, making mistakes and gradually taking responsibility for more demanding work. In digital agencies, those assignments often involve research, preparing content, organising information and performing routine technical tasks. Many are precisely the activities that AI is becoming increasingly capable of handling.

We understand why employers would automate repetitive work. We do the same when it makes sense. But we also know that professional judgment develops through experience. A young person cannot arrive at their first interview with five years of practical knowledge. If businesses begin reducing entry-level opportunities while continuing to demand experienced employees, we could create a serious problem for the next generation. We cannot expect people to become experienced professionals without giving them somewhere to begin.

Your job may be safe. Your customers may not be.

We often hear reassuring arguments that certain professions are relatively protected from AI. Electricians will still install wiring, plumbers will repair pipes, mechanics will maintain vehicles and builders will renovate homes. Much of that is true. But having a skill that AI cannot easily replace does not guarantee that customers will always have enough money to pay for it. Economic security depends on demand as well as the ability to perform useful work.

Imagine a family planning a home renovation. They have contacted a contractor, discussed the price and started choosing materials. Then one family member loses their job because their employer has automated part of its operations. The renovation is postponed. Nothing has changed about the builder’s abilities, and the work still needs to be done. The customer simply cannot afford it anymore. The same effect could reach restaurants, hotels, local shops and countless small service providers.

We understand this connection particularly well at Webiano because marketing depends on customers having both the desire and the means to spend money. We can improve a website, develop an advertising campaign and help a company communicate its services more effectively. What we cannot do is create purchasing power when households are struggling to cover their expenses. A restaurant may serve excellent food and still lose customers who can no longer afford to eat out. That has very little to do with the restaurant’s own use of technology.

Who will buy what the economy produces?

For generations, technological progress has helped businesses produce more efficiently. New technology has created industries, reduced costs and contributed to higher living standards. AI may bring similar benefits, potentially on a remarkable scale. Companies could develop services that were previously too expensive, smaller businesses could compete more effectively and consumers could gain access to products that once required substantial financial resources. We see good reasons to be optimistic about those possibilities.

But productivity gains can reach people in different ways. A company that doubles its output without doubling its workforce might lower prices, increase wages, invest in expansion or distribute larger profits to its owners. Each outcome has different consequences for household income and consumer spending. We cannot assume in advance how those gains will be shared, or whether new employment opportunities will appear quickly enough to compensate for jobs that disappear.

It is entirely possible that AI will stimulate new industries and create demand for occupations we cannot yet imagine. History gives us reasons to consider that possibility seriously. What concerns us is the speed of the transition and the tendency to assume that every economic disruption will eventually resolve itself. A more productive economy does not automatically mean that every household becomes financially more secure. The distribution of income remains important, particularly when most people still depend on employment to pay their bills.

Cheaper products will help, but there are limits to what lower prices can accomplish. A family still needs housing, food, energy and transport. Someone who loses a substantial part of their income may struggle to cover those costs even if certain digital services become almost free. And businesses will eventually feel the consequences if enough households begin reducing their spending. We understand why individual companies want to become more productive. We are less certain how the wider economy will function if income fails to keep pace.

What worries us is a future where companies can produce more than ever, but fewer people have the money to buy what they’re selling. Who are we expecting to buy everything? We don’t see how that would be good for anyone, including the businesses benefiting from automation. — Jan Bielik, CEO & Founder, Webiano Digital & Marketing Agency

What running Webiano has taught us

Running a digital agency means dealing with technological change as part of everyday business. Our work involves marketing, content, search optimisation, websites and technical infrastructure. The problems we encounter rarely fit neatly into one category, and clients expect us to understand how different systems affect one another. AI has become extremely useful in that environment. It helps us investigate problems, organise information, compare approaches and reduce the time spent on routine work.

We also understand the financial side of these decisions. A business needs to remain competitive, manage its costs and make sensible use of available resources. When new technology allows us to complete an assignment more efficiently, we have every reason to use it. The advantage for smaller agencies can be particularly significant because we do not have the same budgets or specialist departments as large corporations. AI can make certain capabilities accessible without requiring a major expansion of the business.

At the same time, our experience has shown us why human judgment still matters. Technical work involves responsibility, especially when an incorrect decision could affect a client’s website or server. Marketing requires an understanding of the business behind the campaign. We have to question results, recognise limitations and take responsibility for what we deliver. AI can complete a surprising amount of work, but our clients still need someone who knows whether that work is actually right for them.

We have no difficulty explaining why businesses will continue investing in automation. The commercial advantages are obvious. But we can only speak from our own experience, and that experience has made us increasingly aware of how quickly the amount of human time needed for certain tasks can change. Multiply those improvements across thousands of businesses and the consequences become much harder to predict. We would like to see those consequences discussed with the same enthusiasm currently devoted to developing the technology itself.

Why aren’t governments discussing this every month?

Frankly, we don’t understand why artificial intelligence is not already a standing priority on government agendas. If we were responsible for national policy, we would want serious monthly meetings dedicated to its economic consequences. We would bring together economists, employers, educators, technology specialists, employee representatives and people responsible for public finances. The purpose would be to examine what is happening in the real economy and decide where preparations are needed.

Are companies hiring fewer junior employees? Are wages changing in industries where automation is spreading? Which professions are experiencing the greatest disruption? Are schools preparing students for the work that employers will actually need? And what happens to public finances if a growing share of economic output is generated with proportionally less human labour? These are practical questions with consequences for employment, taxation, pensions, healthcare and the long-term stability of public services.

We don’t need to know when artificial general intelligence will arrive to start discussing these issues. Nobody can honestly predict how many jobs AI will create or eliminate over the next decade. The outcome will depend on technological capabilities, business decisions, economic growth and public policy. But governments routinely prepare for uncertain events, including economic crises, energy shortages and demographic changes. We would rather see them prepare for employment problems that never materialise than discover too late that they underestimated the pace of change.

This seems particularly important in Europe, where businesses must remain competitive while governments maintain extensive public services. Technological progress could strengthen our economies, but that will require careful decisions about education, investment and the future of employment. We cannot expect every organisation to respond at the same speed. A software company may reorganise its operations in a few months. An education system or public institution may need years to introduce meaningful changes.

We need to talk about the difficult options

Universal basic income is one idea worth examining. So is a shorter working week, particularly if productivity increases enough for people to maintain their income while spending less time at work. Changes to taxation and broader ownership of productive assets may also become relevant if automated systems generate an increasing share of economic value. None of these proposals is simple, and each raises serious questions about financing, incentives and long-term consequences.

We should be equally realistic about education and retraining. Learning new skills will certainly help many people adapt, and businesses have a role in supporting that process. But someone who has spent twenty-five years in one profession, supports a family and has a mortgage cannot always afford to begin an entirely new career. Nor can we reasonably expect every displaced employee to become a programmer, AI engineer or entrepreneur. People’s lives do not always fit the solutions proposed in economic discussions.

We need policies that work for people with real responsibilities, financial commitments and different abilities to adapt. Some workers will move into new professions relatively easily. Others will need considerably more support, and some may find that the opportunities available to them have become less attractive or less secure. We have no complete solution to offer, but we would much rather see these questions debated seriously now than postponed until the consequences become difficult to manage.

Tomorrow morning, we’ll use AI again

We are enthusiastic about artificial intelligence, and we expect it to become an even more important part of our work at Webiano. We appreciate the opportunities it creates for smaller businesses, the time it saves and the problems it helps us solve. We would be delighted to see technology allow people to spend fewer hours doing exhausting, repetitive work. If greater productivity eventually gives more people additional freedom and financial security, that would be an extraordinary achievement.

We also recognise that the future may unfold very differently across industries and countries. AI could create substantial new demand, improve living standards and open professional opportunities that do not exist today. Some people will benefit enormously. Others may struggle to adapt, particularly if employment changes faster than education systems and social protections can respond. We cannot predict exactly how those developments will balance out, and we see little value in pretending otherwise.

Tomorrow morning, we will open the same AI tools, assign new tasks and appreciate how much easier they make our work. We will continue exploring new possibilities and using technology to improve the services we provide. But we would like governments, businesses and economic institutions to devote just as much attention to what these changes mean for people’s livelihoods.

We know how much AI can save a business. We should be just as interested in what it will mean for the people who depend on that business for a living.

Author:
Jan Bielik
CEO & Founder of Webiano Digital & Marketing Agency

This article was prepared with the assistance of artificial intelligence tools. The content underwent expert human review, and Webiano Digital & Marketing Agency assumes editorial responsibility for its final version and publication.