Waste management has become an unlikely market winner, driven by tighter regulation and high barriers to entry. Photo: Donwilson Odhiambo/Getty Images
Landfills Instead of Chips? Why Waste Is a Safer Bet for the Future
Artificial intelligence promises a revolution, but it brings investment uncertainty. A tangible bet on the future is thus much more down-to-earth: the waste management business.
Investing now with a long-term perspective – whether for a year or several years – is more than a little tricky. The only certainty is that artificial intelligence will change the world. How it will do so remains a much bigger question.
AI is developing so rapidly that it has changed dramatically over the past two years, making it difficult to predict where it will go next. Paradoxically, this pace of change is itself a major obstacle. Companies may prefer to wait rather than rush to implement AI now, only to discover six months later that a new model has rendered their efforts and investments obsolete.
This complicates matters not only for company executives but also for investors. How can one invest when everything could be different in six months? And this uncertainty extends far beyond the technology sector to much of the economy. How AI will transform healthcare, for example, remains a wide-open question.
The Uncertainty of Obsolescence
It is hard to predict what kind of artificial intelligence model we will be using in 2030. It is much easier to estimate how much waste humanity will produce. In an investment environment dominated by technological uncertainty, that kind of predictable demand becomes particularly valuable. And in the case of waste, the numbers are surprisingly clear.
According to the World Bank’s latest edition of its report, What a Waste 3.0, the world produced approximately 2.56 billion metric tons of municipal waste in 2022. If current trends continue, that figure is projected to reach 3.86 billion metric tons by 2050. That represents an increase of more than 50% in less than 30 years.
Graph: Filip Staudinger/Statement
Perhaps even more importantly, waste generation is growing faster than expected just a few years ago. A previous edition of the World Bank study predicted that the 2.56 billion-metric-ton mark would not be reached until around 2030. In reality, the world reached it as early as 2022.
That is a major advantage for the waste management sector: volumes will continue to grow, driven by demographic and economic trends. While the economically developed West is stagnating – meaning waste volumes will remain broadly stable – demands for environmentally sound disposal will rise, bringing more money into waste processing.
In Africa and Asia, meanwhile, waste generation will increase as living standards rise. Waste management is therefore a sector in which artificial intelligence is unlikely to fundamentally disrupt underlying demand.
Artificial intelligence will nevertheless bring major changes to virtually every field. US Treasury Secretary Scott Bessent recently gave CNBC a simple example.
An architect who previously wanted to leave a large firm and start his own business might have needed 12 people just to reach the necessary scale. Thanks to artificial intelligence, Bessent says, three people may be enough today. AI therefore does not merely replace jobs; it can also dramatically reduce the cost of starting a new business. Could it create opportunities for new companies in this sector?
Dan Shipper, co-founder and chief executive of the tech company Every, shares this view. He drew on Jeff Bezos’s famous “two-pizza rule”. According to Shipper, even “two-pizza” teams are too large in the age of AI. Instead, he talks about a “two-slice team” – a team consisting of a single person equipped with artificial intelligence.
It is precisely from this perspective that the waste management sector becomes interesting. While AI can dramatically lower the barriers to entry in many industries, waste management remains rooted in the physical world. AI cannot build a landfill, replace a garbage truck or generate a waste processing permit in a matter of seconds. Similarly, at least until autonomous vehicles arrive, staffing on garbage trucks has already been extensively optimized.
The Advantage of Physical Infrastructure
To understand how these companies operate, consider the largest of them – Waste Management. At the end of 2025, the company owned or operated 257 landfills, 482 transfer stations and 162 facilities for recycling and processing organic waste.
Even more interesting is the lifespan of these assets. At the current rate of waste disposal, its landfills have an average remaining permitted capacity of approximately 38 years. This is infrastructure that a new competitor cannot create simply by using a better language model.
Artificial intelligence could play a more significant role in logistics management, equipment maintenance and waste sorting. Logistics, in fact, is one of the fields in which algorithms were widely used long before anyone started talking about today’s AI revolution. The same was true of waste management companies.
These companies are not starting from scratch. On the contrary, they were optimizing their operations long before artificial intelligence entered the public consciousness.
Republic Services already operates approximately 79% of its residential routes using automated vehicles with a single driver. Waste Management, for its part, has used software for dynamic route optimization for several years and is gradually replacing traditional rear-loading trucks with side-loading vehicles that can be operated by a single person. At a time when everyone is talking about the AI revolution in logistics, the biggest players have already carried out part of that revolution.
Of course, this does not mean that artificial intelligence will not change the waste management sector. It can further optimize routes, predict vehicle breakdowns and improve automated waste sorting. But these are likely to be incremental changes that shift companies’ margins by tenths of a percentage point.
The difference compared with software, media or architecture, for example, is fundamental. AI can increase the efficiency of an existing system, but it is much more difficult for it to eliminate the need for physical infrastructure itself. That is precisely what makes this sector an attractive investment for a long-term portfolio.
For investors, it may therefore be safer to focus not on whom AI will replace, but on sectors that will continue to function regardless of how profoundly artificial intelligence changes the world.
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