The Next Breakout in AI Isn’t a Model. It’s Collaboration

For more than a decade, the AI industry has run on a simple storyline: whoever trains the biggest model wins. Faster chips, larger datasets, more compute. Tech giants poured billions into outmuscling one another, each convinced that the next breakthrough would come from scale alone.

But that logic is starting to crack. The industry now faces bottlenecks that no single lab, no matter how well-resourced, can solve in isolation. Training data is plateauing. Safety problems are getting harder. And the models themselves are so complex that even their creators struggle to fully explain how they work.

This is why a growing number of researchers and engineers are arguing that the next wave of AI won’t come from competition. It will come from collaboration.

“The future of AI will be defined by collective intelligence. No single company or system can physically hold all the data, all the talent, or all the insights needed to solve the complex challenges that often come with AI,” says Brian Peret, Director of CodeBoxx Academy.

That idea is gaining traction across the industry, especially as companies see diminishing returns from going it alone. And it comes at a time when global demand for AI is skyrocketing. Gartner estimates that worldwide spending on AI software will reach $297 billion by 2027, driven largely by generative AI adoption.

But more money and bigger models aren’t the whole story. The deeper question is whether AI can continue to progress without a structural redesign of how the industry builds it.

Peret has spent the last several years training new developers entering a field where the rules change every few months. And what he’s seeing isn’t just the rise of larger models, but the rise of shared ones.

He believes that collaboration is becoming the new killer feature. “Collaboration is where true modern innovation happens, when technologists, ethicists, creatives, and communities unite to shape systems that serve everyone. The most powerful AIs won't be in silos; they will connect, integrate, and amplify the strengths of others. In this new era, the ability to form productive partnerships becomes the competitive edge.”

The logic is simple: large language models work best when they can access diverse, high-quality information. But gathering that data, labeling it, testing outputs, and monitoring safety requires expertise far beyond what any single organization can maintain.

Even the labs setting the pace know this. OpenAI, Google DeepMind, Anthropic, and Meta have all created partnerships with universities, national labs, nonprofits, and policy organizations. Hugging Face has built an entire ecosystem around open-source model sharing. NVIDIA now collaborates with more than 40,000 companies across its developer programs.

The pattern is clear. Collaboration is not a threat to innovation. It is becoming the engine of it.

If the last era of AI was about automation, the next era may be about coordination. And not just among models, but among the humans who build them.

Peret argues that the industry has spent too long pretending that technical progress alone is enough. Real innovation, he says, is created by bringing people together. “When people work together, it puts humanity and creativity back into the system. But if not, AI might risk the opportunity to thrive later.”

This may sound idealistic, but the implications are practical. Collaborative development leads to more ethical review, more diverse perspectives, more robust datasets, and fewer blind spots. Problems get caught earlier. Real-world use cases emerge faster. And systems become safer because more people understand how they are built.

The opposite is already revealing its limits. Siloed development produces opaque systems, uneven safety standards, and models that reflect the biases of a narrow group. In a global industry, that simply doesn’t scale.

The traditional AI arms race is being replaced by something more complex. Companies are beginning to realize that their biggest competitor isn’t each other. It’s the limits of building alone.

Peret believes the companies that win the next chapter of AI will be the ones that understand that unity is not a weakness. It’s a multiplier.

“The most powerful AIs won't be in silos,” he says. “They will connect, integrate, and amplify the strengths of others.”

If he’s right, the next major AI breakthrough won’t be announced at a press conference or during a product demo. It will happen quietly, through partnerships, shared datasets, joint research, and global networks of people willing to build together.

The question for the industry is no longer who can move the fastest alone. It’s who is willing to shape the future together.