The Big Idea: The next wave of AI

In the 1999 sci-fi blockbuster The Matrix, Neo, a computer hacker, discovers he’s been living in a world where intelligent machines have reshaped human existence. The film imagines a future where artificial intelligence (AI) performs complex tasks and reasons, adapts, and manipulates the world around it.

More than 25 years later, reality hasn’t caught up with Hollywood, but advances in AI have made one of the film’s underlying questions far more relevant. That is, what happens when machines are capable of more than just following instructions?

Some researchers and industry experts are already focused on that very possibility, looking beyond today’s generative and agentic AI, toward artificial general intelligence (AGI). Unlike current AI systems, AGI would be capable of learning, adapting, and solving problems much more like people do.

For some experts, AGI’s significance lies not in its capabilities, but in what those capabilities could make possible. According to Neil Sahota, chief AI officer at financial services provider loanDNA, in Santa Ana, Calif., and a United Nations AI advisor, AGI is more of a paradigm shift. “AGI isn’t just another technology,” he says. “It’s an entirely new operating model.”

Opinions vary widely over when AGI might arrive. But regardless of the timeline, Sahota thinks organizations should already be paying attention. And that’s not because of the technology, itself, but because it forces leaders to rethink how decisions are made, how knowledge is managed, and how value is created.

More Than Just Better AI

What distinguishes AGI isn’t just that it’s more intelligent, it’s that the AI is fundamentally more capable. To illustrate the difference, Sahota compares the adoption of today’s AI capabilities to hiring human specialists. One might excel at producing written content, another at coding, another at video creation, and so on. AGI changes that way of thinking.

“With AGI, you’re essentially hiring someone that’s far more adaptable,” Sahota explains. “They can walk into an unfamiliar business, take a look at things without much prompting — or any prompting — understand how the business creates value, learn about the business, and figure out how to then contribute and improve it without having someone to retrain them.”

In other words, AI shifts from performing isolated assignments to contributing across an organization, much like an experienced employee who can learn, adapt, and take on new responsibilities over time. AGI has the potential to become an active contributor, capable of identifying opportunities and solving problems independently. “Effectively, today’s AI executes,” Sahota says. “AGI redesigns work.”

A Shift in Business Thinking

Historically, businesses have operated around a simple premise: Work creates value. People at all levels of the organization perform tasks and make decisions, and that generates value.

AGI, Sahota notes, would flip this premise on its head. “In the future,” he says, “value is going to create work.”

Instead of defining jobs first and assigning people to perform them, organizations may increasingly begin with desired outcomes and determine whether people, AI, or some combination of both, can best deliver them. Roles could become more fluid, with responsibilities evolving as intelligent systems continuously learn and adapt.

That doesn’t mean people become less important. In fact, Sahota asserts the opposite. As AI assumes more routine analytical and operational responsibilities, uniquely human capabilities — including creativity, ethical decision-​making, and relationship-​building — could become even more valuable.

“When it comes to the future of work, companies are going to ask, ‘What value do we need people to create for us?’” he says. “Not just in terms of outcomes, but what can people produce — and produce better — than AI?”

Sahota points out that this shift is already starting to happen, particularly where agentic AI increasingly performs tasks that were previously handled by people. But instead of displacing those individuals, he’s observed that it enables the organization to reposition them to perform tasks that produce even more value.

“What I’ve seen is that value migrates,” he says. “And we’ll see AGI accelerate that process, and our role in the workforce won’t be our title or our job responsibilities anymore. Instead, it’s going to be defined by how we create value.”

Judgment in Short Supply

For leaders, deciding how to best leverage the value people can bring may be one of the greatest challenges AGI introduces. Organizations could find that while information is no longer a limiting factor, human judgment is.

Rather than gathering information or evaluating routine choices, which AGI could readily handle, leaders may increasingly focus on determining where human judgment remains essential. Decisions involving risk tolerance, ethics, or organizational values may require oversight that extends beyond what AI can realistically deliver.

At the same time, organizations may face pressure to make decisions more quickly. Sahota notes that AI has the potential to dramatically reduce “organizational latency” — the delays created when information and decisions move through layers of management. The challenge will be balancing speed and oversight, empowering AI to act where appropriate, while ensuring people make the decisions that matter most.

That responsibility becomes even more important as organizations grow increasingly comfortable with relying on AI. Sahota says the greatest long-term risk isn’t widespread job loss — it’s allowing human decision-making skills to gradually erode.

“If we let AI make every decision, eventually we’ll forget how to make those decisions ourselves,” he says. “We’ll lose our decision-making muscles.” Over time, he warns, organizations could experience a form of institutional “learned helplessness,” in which employees may come to feel less able, or less willing, to make decisions without AI guidance, even when they have the knowledge and authority to do so.

For Sahota, the goal isn’t to keep people in the decision-making loop simply for the sake of oversight. It’s to ensure organizations continue developing the uniquely human capabilities that AI cannot easily replicate. As intelligent systems become more capable, those skills may become one of an organization’s most valuable competitive advantages.

AGI as Infrastructure

Sahota says one of the biggest misconceptions about AGI is that it represents just another technology investment. Instead, he argues, it’s more useful to think of it as infrastructure, like electricity.

Just like broadband connectivity and cloud computing before it, AGI could become a foundational capability underpinning virtually every aspect of an organization’s operations. It has the potential to reshape an enterprise’s operations from the ground up, rather than simply supporting individual tasks or processes.

That, Sahota asserts, is why organizations asking how AGI will function as a product or tool are asking the wrong question. “The truth is every process is going to become an AGI process,” he says.

And that may be the most important lesson from The Matrix. Preparing for AGI isn’t just about the utility of intelligent machines; it’s about recognizing when it’s time to see the world differently.