Artificial intelligence is moving quickly into business.

That is hardly news anymore.

Companies are adding copilots. Employees are using ChatGPT. Software companies are adding AI features to products that businesses already use. And a new generation of AI agents is beginning to perform tasks that once required people.

But I think there is a much bigger change underway.

The companies that benefit most from AI will not simply be the companies that buy the best AI tools.

They will be the companies willing to redesign themselves around a world in which people and intelligent systems work together.

We can already see signs of this happening in the food industry.

PepsiCo, Nestlé, and Kraft Heinz are three interesting examples.

None of these companies represents a finished version of an “AI-native company.” The technology is still changing too quickly for that.

But look at what they are building, and a pattern begins to emerge.

They aren’t just implementing AI.

They are changing the foundations of their businesses.

PepsiCo: Building an Intelligent Operating System

PepsiCo gives us perhaps the clearest picture of where this could eventually lead.

In January 2026, PepsiCo announced a collaboration with Siemens and NVIDIA involving AI and digital twins for manufacturing plants and warehouses.

The idea behind a digital twin is fairly simple.

Before changing a real factory, PepsiCo can create a detailed digital version of it. Machines, conveyors, pallet movements, operator paths, and other parts of the facility can be modeled inside a virtual environment.

The company can then test changes before spending money or disrupting the real operation.

PepsiCo says early deployments have already produced significant improvements in areas such as throughput and capital spending.

But the technology itself isn’t the part I find most interesting.

PepsiCo describes a future in which plants and warehouses become parts of a more connected and intelligent operating environment.

Think about what that means.

Instead of a factory simply responding when something happens, data and AI could increasingly help the operation predict what is likely to happen next.

A system might identify a bottleneck before management would normally see it.

It might simulate several possible solutions.

It might recommend the best one.

Eventually, within carefully defined limits, intelligent systems may be able to take some actions themselves.

PepsiCo is also working with Google Cloud and its Gemini Enterprise Agent Platform. The company says the effort is aimed at strengthening its digital foundation while applying AI across areas such as supply chain management, decision-making, go-to-market execution, and employee workflows.

That last part matters.

We are moving from AI that tells us something toward AI that can increasingly do something.

That is the beginning of a very different kind of company.

Nestlé: The Boring Work Comes First

Nestlé may offer an even more important lesson.

Everyone wants to talk about AI.

Far fewer people want to talk about standardizing data, replacing old systems, connecting factories, cleaning up processes, and building common technology platforms.

But those things may determine who actually succeeds with AI.

In its most recent business-transformation reporting, Nestlé says it has scaled a single manufacturing system to nearly 90% of its 335 factories.

Those connected factories use real-time data to improve production-line performance, reduce downtime, and increase automation.

Nestlé also says it plans to push this further with AI, robotics, and digital twins.

That sequence is important.

Imagine trying to build an intelligent agent across hundreds of factories if every factory describes products differently, stores information differently, and runs completely different systems.

The AI model isn’t necessarily the problem.

The company underneath the AI is the problem.

Nestlé’s broader transformation shows why data and architecture matter so much.

This tells us something else about becoming AI-native.

It isn’t just a technology project.

It is a people project.

Employees have to learn new ways of working.

Managers have to decide when AI should make recommendations, when it should take action, and when a human must remain involved.

The company’s culture has to change along with its technology.

Kraft Heinz: Connecting the Supply Chain

Kraft Heinz provides another view of the same transition.

The company has developed what it calls an AI-enabled supply-chain “control tower”.

Think of it as an information center sitting above the supply chain.

Instead of different parts of the organization seeing only their small piece of the operation, the goal is greater visibility across the entire system.

Kraft Heinz says the platform helps it predict challenges and opportunities across the supply chain.

The company also developed a Connected Worker platform designed to turn operating data into information frontline employees can use.

And its digital transformation goes back several years. In 2022, Kraft Heinz and Microsoft announced plans to create digital twins for 34 North American manufacturing facilities.

Those digital models allow the company to test changes and improve processes before applying them on the real factory floor.

That is another important clue about the future.

AI-native doesn’t necessarily mean removing people from the business.

It can mean giving people better information while machines and agents handle more of the routine analysis and execution.

The relationship between the person and the system changes.

The Pattern Behind All Three Companies

PepsiCo, Nestlé, and Kraft Heinz are doing different things.

But underneath those differences, I see a common pattern.

They are building connected data foundations.

They are connecting physical operations to digital systems.

They are using AI to understand increasingly large amounts of information.

They are creating digital models of real operations.

They are giving employees better information.

And they are beginning to use intelligent systems that can move beyond reporting toward recommending and, in some cases, executing actions.

This is why I don’t think the coming transformation is simply about implementing AI.

It is about redesigning the company.

You Can’t Bolt AI Onto a Broken Foundation

This may become one of the hardest lessons for businesses over the next several years.

Imagine a manufacturer where customer agreements live in email.

Product specifications are stored in PDFs.

Pricing is maintained in spreadsheets.

Inventory is inside a 20-year-old ERP.

Salespeople keep important customer knowledge in their heads.

Different departments have different definitions of the same business terms.

Now imagine management saying:

“We need an AI agent.”

The company probably doesn’t have an AI problem yet.

It has a data and architecture problem.

An intelligent agent is only useful if it can reach reliable information and understand what that information means.

And access creates another problem.

What is the agent allowed to see?

What can it change?

Can it create an order?

Can it change a price?

Can it communicate with a customer?

Can it commit inventory?

Can it issue a credit?

When does it have to stop and ask a person?

These are not questions that can be solved by simply purchasing a better AI model.

They involve architecture, security, governance, process design, and management.

The Culture Has to Change Too

There is another side of this transformation that may be even harder.

People.

For decades, companies have designed jobs around people operating software.

A person opens the ERP.

A person runs the report.

A person copies information into Excel.

A person emails another employee.

A person reviews the spreadsheet.

A person enters something into another system.

We have built entire organizations around humans moving information between applications.

Agents begin to challenge that design.

If an agent can retrieve the information, analyze it, prepare the transaction, communicate with another system, and bring exceptions to a person, what exactly is the person’s job?

The answer isn’t necessarily “there is no job.”

The job changes.

People may spend more time setting goals, making judgments, handling exceptions, building relationships, approving important decisions, and improving the systems doing the routine work.

That requires a different culture.

Employees have to learn how to work with intelligent systems.

Managers have to learn how to manage work performed by both people and agents.

Executives have to decide how much authority autonomous systems should receive.

That is organizational change, not software installation.

What This Means for Mid-Sized Food Manufacturers

PepsiCo, Nestlé, and Kraft Heinz have enormous resources.

Most food manufacturers don’t.

A $100 million food manufacturer cannot simply copy PepsiCo’s technology strategy.

But it can learn from it.

The lesson isn’t:

“Build a digital twin of every factory.”

The lesson is:

Start preparing the business so intelligence can operate across it.

That might begin with much simpler questions.

Is our product data trustworthy?

Can systems communicate with one another?

Can AI securely reach our ERP?

Are customer and distributor relationships represented correctly in our data?

Are important business rules documented?

Do we know which decisions require human approval?

Where does critical knowledge live outside our core systems?

Which business process would create the most value if people and agents could perform it together?

Those are questions companies can start asking today.

The Next Great Business Transformation

I lived through the move from DOS to Windows.

I watched businesses adapt to the Internet.

Then came cloud computing.

Each transition initially looked like a technology change.

But each one eventually changed how companies operated.

I believe AI may produce an even larger transition.

The Internet created the digital economy.

AI may create an autonomous economy.

In that economy, businesses won’t simply use software. Intelligent systems will increasingly participate in the work of the business itself.

They will retrieve information.

They will analyze situations.

They will communicate with other systems.

They will recommend decisions.

And within carefully governed boundaries, they will increasingly take action.

That is why I believe:

The next great business transformation isn’t implementing AI. It’s redesigning the company so people and autonomous systems can work together.

PepsiCo, Nestlé, and Kraft Heinz aren’t the final destination.

Nobody knows exactly what the final destination looks like yet.

But they are giving us an early view of the road ahead.

The important question for every other company isn’t whether it can afford to copy them.

It’s much simpler:

What should we start changing today so our company is ready for the business environment that is coming tomorrow?