The Economics of Building AI-First Companies

A Blueprint for the Future

As artificial intelligence continues to evolve, it's clear that the foundational structures of companies will need to change as well. Historically, scaling an organization meant hiring more people to manage growing complexity and workloads. But we’re now facing a paradigm shift—what if this model is no longer the most efficient path forward? What if building AI-first companies could enable us to rethink how teams work, delivering unprecedented levels of productivity with fewer people?

People Don’t Scale

One of the realities of business is that simply adding more people doesn’t scale output in a linear fashion. In fact, research and experience suggest otherwise. The "square root law" of productivity proposes that a company of 200 people isn’t 10 times more effective than a company of 20. Instead, its efficiency gain might be closer to 3x due to coordination challenges, communication breakdowns, and diminishing returns.

As teams grow, they inevitably face more complexity—coordination becomes harder, decision-making slows, and inefficiencies creep in. These challenges often erode productivity. While the "square root law" is a useful heuristic, the core insight is that growing headcount doesn’t always lead to proportional gains in performance.

AI Copilots: Amplifying Human Potential

Now consider a company where AI copilots enhance human capability, helping employees work faster and smarter. AI isn’t just a tool for automating routine tasks; it can act as an advisor, analyzing data, making recommendations, and freeing up human workers to focus on high-impact decisions. The result? A 20-person team powered by AI could perform at the level of a traditional 200-person team.

This is not a far-off theory—there are tangible examples in various industries. AI is already being deployed to speed computer programming, streamline customer service, and massively aid in writing. By integrating AI systems that act as copilots rather than replacements, companies can amplify the effectiveness of their human teams, allowing them to outperform in both speed and quality of decision-making.

The Economic Shift: A New Value Equation

What does this mean for the future of company economics? AI-first companies stand to benefit from radically different dynamics compared to traditional organizations. With fewer people delivering more output, these companies are poised to operate with much more efficient economics. This opens up multiple avenues for rethinking compensation, equity, and profitability.

1. 10x More Equity per Employee

In traditional companies, equity tends to be distributed across large teams, which dilutes individual ownership. However, if a small AI-empowered team can achieve the same results as a larger team, each person could command a significantly larger share of equity. The overall value created doesn’t shrink, but the rewards are concentrated among fewer people, offering the potential for much greater upside.

2. Competitive Salaries for Top Talent

With fewer people producing the same, or greater, value, AI-first companies could afford to pay more to attract and retain top talent. This model could allow companies to hire the best people in their respective fields, leading to better outcomes overall. The shift towards higher compensation for fewer people would also allow organizations to create environments that attract top-tier talent—driving a positive feedback loop of success.

3. Improved Financial Performance

AI-first companies will likely enjoy better financial metrics across the board. With lower headcounts and higher productivity, these companies could achieve profitability more quickly, with stronger margins. This would translate to better cash flows, healthier balance sheets, and stronger valuations. As a result, equity would appreciate faster, benefiting both employees and investors.

Building a Healthy Culture: Avoiding Organizational Drag

Beyond the economic advantages, AI-first companies may also enjoy cultural benefits. As organizations grow larger, they often struggle with internal politics, which can slow down decision-making and introduce inefficiencies. But with AI-driven companies designed to operate with smaller teams, there is a reduced risk of these dynamics taking root.

Smaller, more focused teams allow for clearer communication, more direct accountability, and fewer layers of management. By leaning on AI to handle many operational tasks, companies can avoid the bureaucratic bottlenecks that typically plague larger organizations. This creates an environment where innovation and collaboration thrive, rather than getting bogged down in the politics of scale.

Why You Can’t Retrofit an AI-First Model

It’s important to acknowledge that transitioning an existing company to an AI-first model isn’t as simple as firing 180 out of 200 people and expecting the rest to suddenly embrace AI. In practice, people are resistant to change, particularly when it threatens their roles or status. In traditional organizations, the introduction of AI can be seen as a disruptive force, making it difficult to achieve true transformation.

For companies to fully unlock the potential of AI, they need to be designed with this technology at their core from the outset. A ground-up approach allows for workflows, processes, and cultural norms to be built around the concept of human-AI collaboration. Employees come in with the understanding that AI is a powerful ally in amplifying their capabilities, not a tool that will replace them. This mindset is critical for successfully scaling an AI-first organization.

The Rise of AI-First Companies: It's Already Happening

The future of work is shifting toward AI-first companies, where AI copilots are not just tools but core elements that amplify human potential. This transformation is already underway, with AI-powered tools helping employees work faster and smarter across industries.

In programming, tools like GitHub Copilot and Cursor assist developers by suggesting code and automating repetitive tasks. These AI copilots drastically improve productivity, enabling smaller teams to accomplish what would have once required much larger groups.

For writing and content creation, tools like ChatGPT help professionals draft, edit, and generate ideas faster than ever. Whether it’s blog posts, reports, or customer outreach, AI-enhanced writing tools are speeding up workflows while maintaining quality.

In customer service, AI-driven platforms like Zendesk AI and Salesforce Einstein are already handling routine inquiries, automating responses, and offering intelligent suggestions to human agents. These tools improve efficiency and free up teams to focus on more complex, high-value tasks.

This AI-first shift isn’t a distant concept—it’s happening now, and the new startup companies adopting these tools today are on the path towards being AI First.

Conclusion: A New Era of AI-First Companies

The rise of AI offers an unprecedented opportunity to rethink how companies are built and operated. AI-first companies, designed around the integration of human-AI collaboration, will be leaner, more productive, and more profitable than traditional organizations. By leveraging AI to scale output while minimizing headcount, these companies will unlock new levels of efficiency, create better financial outcomes, and attract the best talent.

But this transformation requires more than just adopting AI tools—it requires a shift in mindset. To fully realize the benefits of AI, companies need to be built with the assumption that AI will play a central role in how work gets done. This is how we’ll usher in a new era of business, where human potential is amplified by AI, and the organizations that thrive are those that embrace this future.