The Internet created the digital economy. AI may create the autonomous economy — an economy in which intelligent systems don’t just help humans conduct business; they increasingly conduct business with one another on behalf of humans and organizations.
A company that isn’t AI-native may eventually find itself unable to participate efficiently in parts of an economy increasingly designed for autonomous companies.
That is my thesis. It may sound like science fiction, but I don’t think it is. I believe we are at the start of another major change in how business works.
I don’t expect this change to happen overnight. I think we will start to see clear signs of it within the next three years. Over the next 10 to 15 years, it could change the basic design of a company.
We’ve Seen This Kind of Change Before
I’ve lived through two huge changes in technology. The first was the rise of the personal computer. I remember the move from DOS to Windows and how different computing suddenly felt.
At first, Windows could look like a nicer way to use a computer. But it became much more than that. It made computers easier to use and helped make new kinds of software possible.
Then came the Internet. At first, many companies treated it as another tool. They created websites, got email addresses, and put product information online.
But the Internet did much more than make communication faster. It created the digital economy. Entire businesses and business models became possible because millions of people and companies could suddenly connect.
Amazon could not have existed in its current form without the Internet. Neither could online banking, streaming video, cloud software, or social media. The Internet didn’t just improve old businesses; it made new kinds of businesses possible.
I think AI may do something similar.
We May Be Thinking Too Small About AI
Right now, much of the AI conversation is about helping people work faster. AI can write an email, summarize a meeting, analyze a spreadsheet, or help write computer code. Those things matter and can save a lot of time.
But I think they are only the beginning. The bigger change comes when AI moves from helping people do work to doing parts of the work itself. We are already starting to see this with AI agents.
An AI agent is different from a chatbot that simply answers a question. An agent can be given a goal, gather information, use software, and take actions. Within the right limits, it can also make decisions and check the results of its work.
When needed, the agent can stop and ask a human for help. That gives us a way to keep people involved in important decisions. But it also allows more routine work to happen without a person guiding every step.
Now take that idea one step further. What happens when one company’s AI agents begin working directly with another company’s AI agents? That is where things get very interesting.
Imagine a Manufacturer in the Autonomous Economy
Suppose a food manufacturer needs a certain ingredient to make its products. Today, a person may notice inventory is getting low, check the production schedule, and contact suppliers. The suppliers send prices and delivery dates, and someone compares the choices.
After that, someone creates a purchase order and arranges shipping. When the ingredient arrives, another employee receives it. Later, accounting matches the invoice to the purchase order and receipt.
There may be emails, phone calls, spreadsheets, ERP screens, and several people involved in that one purchase. Each step takes time. Each handoff also creates another chance for delay or error.
Now imagine the same process in an AI-native company. An AI agent watches inventory, sales, and the production plan. It sees a shortage coming before it becomes a problem.
The agent knows which suppliers are approved and contacts those suppliers’ agents. One supplier can deliver Tuesday for one price, while another can deliver Monday but costs more. A third has the best price but cannot meet the required delivery date.
The manufacturer’s agent considers price, inventory, production needs, shipping costs, quality rules, and management’s buying limits. It chooses the best option within the authority management has given it. If the decision falls outside those limits, it asks a person for approval.
The purchasing system can then create the order. Another system can schedule transportation and update the production plan. When the shipment arrives, the system can check what was received against what was ordered.
Later, an accounting agent can help match and reconcile the transaction. Much of this could happen without people sending emails back and forth. Humans would step in when their judgment or approval is actually needed.
That is more than automation inside one company. It is business systems conducting business with other business systems. That is what I mean by the autonomous economy.
Humans Don’t Disappear
This is an important point. An autonomous economy does not mean humans have no role. I think the human role changes.
People decide what the company is trying to accomplish. They set strategy, decide how much risk is acceptable, and create the rules. They also decide how much authority an AI agent should have.
People will still handle unusual situations and major decisions. They will decide when an agent must stop and ask for approval. They will also be responsible for making sure these systems are safe, secure, and working as expected.
The machines may increasingly handle routine execution. Humans move toward judgment, leadership, design, and control. That could be one of the biggest changes AI brings to business.
AI-Enabled Is Not the Same as AI-Native
This leads to a distinction that I think will become important. An AI-enabled company takes the company it already has and adds AI tools. Employees get AI assistants, departments automate tasks, and people become more productive.
That’s useful, and for many companies it will be the right place to start. But an AI-native company goes further. It begins to rethink how the company itself should operate.
An AI-native company asks a different question: If intelligent systems can perform work, make limited decisions, and communicate with other intelligent systems, how should we design the company? That question changes the conversation.
Now we have to think about data, ERP systems, APIs, security, permissions, and business rules. We also have to think about AI agents, governance, testing, and what happens when something goes wrong. AI is no longer just another tool employees use.
It becomes part of the operating design of the company.
Why Today’s Technology Decisions Matter
This is why I believe companies should start thinking about AI-native architecture now. You cannot simply flip a switch in 2035 and become an autonomous company. The foundation has to be built first.
AI needs information it can trust. If customer information is wrong, AI can make the wrong decision faster. If inventory records are unreliable, an autonomous purchasing system can create problems instead of solving them.
Business rules matter too. If important rules exist only inside the heads of experienced employees, an AI system may not know what to do. Companies will need to turn more of that knowledge into clear processes and rules.
Systems also need to communicate with one another. If information is trapped inside disconnected applications, agents may not be able to do their jobs. APIs and other ways of safely connecting systems become much more important.
Security may be even more important. Giving AI the ability to take action means companies must be very clear about what each agent can see and do. More power without good controls can create more risk.
This means some of the least exciting technology work may become some of the most important. Companies need clean data, modern ERP systems, connected applications, clear permissions, and strong security. They also need logs showing what an AI system did and why.
That is the foundation of an AI-native company.
My Three-Year Hypothesis
I don’t believe the autonomous economy suddenly arrives on a certain date. Technology changes don’t work that way. They build slowly and then begin to change how people expect businesses to operate.
My hypothesis is that during the next three years, we will begin seeing much more serious use of AI agents inside companies. At first, many agents will have narrow jobs. They will work within clear limits and often have humans approving important actions.
One agent may work on purchasing. Another may watch accounts receivable, while another helps with customer service. Other agents may monitor quality records or look for problems in the supply chain.
The important change is that AI begins moving from answering to acting. Once companies become comfortable with agents acting inside their own walls, the next step becomes easier to imagine. Agents begin interacting across company walls.
That’s when the autonomous economy starts to become real.
The Next 10 to 15 Years
The larger change could take 10 to 15 years. Some industries will move faster than others, and some companies will move much faster than their competitors. Others may refuse to change at all.
That’s normal. We saw the same thing with computers and the Internet. The old way did not suddenly disappear when something better arrived.
You could still run a company without a website after websites became common. You could still use paper when other companies moved to digital systems. You could still make phone calls when other businesses moved many processes online.
But something important happened: the economic territory where the old way remained competitive became smaller. Companies that adopted the new technology could often operate faster and at a lower cost. Customers also began expecting businesses to work in new ways.
I think AI may follow the same pattern. Small businesses may continue operating in very human-centered ways for a long time. There will always be places where personal service and human relationships matter more than automation.
But imagine a large company trying to compete in 2040 while its employees manually perform work that its competitors’ systems complete in seconds. The problem isn’t that the old company suddenly becomes impossible to operate. The problem is cost, speed, accuracy, and scale.
Eventually, other companies may prefer doing business with organizations that can interact with them automatically. That could put companies that cannot participate at a growing disadvantage. The gap could become larger each year.
What Happens If Your Company Can’t Participate?
This leads back to the second part of my thesis: A company that isn’t AI-native may eventually find itself unable to participate efficiently in parts of an economy increasingly designed for autonomous companies.
Notice that I said efficiently. I don’t believe every traditional company disappears. But the competitive gap could become very large.
Imagine two suppliers. Supplier A can receive a request from a customer’s agent, check inventory, calculate a price, promise a delivery date, confirm the order, and schedule shipment. Its systems can return the needed information almost instantly.
Supplier B requires an email. Someone reads it the next morning, checks three systems, asks another employee about inventory, creates a quote, and emails it back that afternoon. Both companies can still sell the same product.
But which supplier is easier for an autonomous customer to work with?
Price will still matter. Quality and relationships will still matter. But the ability to participate in an automated business network may begin to matter too.
That ability could eventually become a competitive advantage of its own.
This Is Bigger Than Buying AI
That’s why I think the question facing business leaders is bigger than, “Which AI tool should we buy?” Buying tools may help employees today. But it doesn’t answer the larger question.
A better question may be: “How should we build a company that can operate in an AI-native economy?” That question leads us into technology, but it also leads us into business strategy.
Which decisions should people make, and which can agents make? What data should an agent be allowed to see? What actions should it be allowed to take?
When should an agent ask permission? How do we know whether it made the right decision? How does our agent safely interact with another company’s agent?
And perhaps most importantly, who is responsible when something goes wrong?
Those are not just AI questions. They are business architecture questions. They affect how we design the company itself.
The Opportunity Ahead
I don’t know exactly what the business world will look like in 2040. Nobody does. I also don’t know whether “autonomous economy” will be the term we eventually use to describe it.
But I believe the direction is becoming clearer. Computers helped us process information. The Internet connected people, companies, and systems.
Cloud computing gave businesses access to huge amounts of computing power. AI is now adding something different: intelligence and agency. Software is beginning to understand goals, reason through choices, use tools, and take action.
When those abilities become connected across organizations, we may create something much bigger than better office software. We may create a new layer of the economy. And companies may need to learn how to participate in it.
The Question Business Leaders Should Be Asking
I believe we are still early enough that companies have time to prepare. That doesn’t mean trying to automate everything tomorrow. It means building the foundation.
That foundation includes modern systems, good data, connected applications, clear business processes, strong security, and well-defined rules. It also requires human oversight. Leaders need to understand what the technology can do and where its limits should be.
Because the most important question may eventually stop being, “How can our employees use AI?” It may become, “How does our company operate when our customers, suppliers, competitors, and partners have become AI-native?”
And eventually we may face an even more important question:
What happens when your competitors’ systems can conduct business autonomously — and yours can’t?
I believe answering questions like these will be one of the great business challenges of the next decade. It is also why I keep coming back to the mission behind my work:
Translating Emerging Technology into Business Advantage.