How AI Is Changing The Playbook For Venture-Backed Companies
Nada Usina is CEO & Co-Founder of NU Advisory Partners.
gettyThe question I hear most often in VC circles is whether the AI investment boom is a wave that will eventually crash. Will the flood of capital and climbing valuations prove to have sustainable traction and revenue? I’ve been at the forefront of several major technology shifts, from leading digital media companies through the dot-com era to working at the leading edge of mobile. Today, I’m building an AI-native, high-growth business. I’ve seen firsthand what happens when excitement gets ahead of fundamentals.
AI investment will continue well beyond 2026, but what interests me most is how AI is changing the way companies are built and led. Technology allows them to move faster with fewer people, challenging assumptions about what an executive team should look like.
The enormous amounts of capital being poured into AI make the market appear more mature than it is. Commercially, it is still early. A breakthrough in technology does not automatically create distribution, customer trust or a sustainable business.
AI can shorten that timeline considerably. We are seeing companies go from zero to $100 million in revenue at speeds that would have seemed extraordinary a decade ago. When a company can accomplish in a few years what once took 10, investors naturally start looking for the next one.
That speed can also lead to bad bets. Some companies will be swallowed by larger platforms while they are still small. Others will discover that an impressive product does not solve a problem customers urgently need to solve. It also raises a practical question for investors: What kind of leadership does a company need when it can grow this quickly with a much smaller team?
For years, companies approaching a new stage of growth often responded by adding people. Layers of vice presidents, senior vice presidents and functional leaders came in as the organization became more complex. With AI, companies can accomplish more with smaller teams, which means the people at the top have to be much closer to the actual business.
Leaders need to understand the product, the customer, the economics and how the business actually operates. They need to make decisions quickly, work across functions and know when technology can replace a process rather than simply adding another person to manage it.
As AI reduces the need for some layers of middle management, the expectations of the C-suite are getting higher. We are seeing investors look for leaders with the judgment and operating experience to work effectively in much leaner organizations. With fewer people between the C-suite and the work itself, the people at the top need to be able to run the business, not just oversee it.
For a portfolio company, I would ask: Is AI actually changing the business, or has it just been added to the product? The strongest companies are using it to improve the customer experience, make the product smarter through proprietary data or change the economics of the business. Calling something “AI-powered” does not tell an investor very much if the underlying business still operates the same way.
That can also point to a talent decision. A company may need a more commercially minded CEO, a different product leader or an executive who has already navigated a similar technology shift.
Public markets will make it easier to see which AI companies have built durable, profitable businesses and which have benefited primarily from the private-market environment. Investors will scrutinize revenue quality, retention, margins and the cost of maintaining the technology. They will also look at who is running the company.
I have seen strong technology companies lose momentum because their leadership team was built for invention rather than growth. The executives who made sense at $10 million in revenue may not be the right people at $100 million. Waiting too long to recognize that can cost a company valuable time.
My experience with frontier technology goes back to the early days of the internet and mobile media. At broadcast.com, I worked at a company that was among the first to stream live content over the Internet. Later, at Nokia, I worked with the music industry to bring music, games and video to mobile phones.
Both experiences showed me what happens when technology opens up a market before the infrastructure, business models and consumer expectations have caught up. AI presents a similar challenge: Leaders have to figure out what the technology makes possible while building a business that can actually take advantage of it.
We are applying the same thinking at our company, where we have built an AI-native executive search firm. We use AI throughout the search process while relying on human judgment to assess leadership, experience and fit.
We ask ourselves many of the same questions we ask our clients: Where can AI make a meaningful difference? Where does judgment still matter? And how do we make the best use of our team’s expertise for the complex advisory work our clients rely on us for?
AI investment will continue, but investors will become more selective. Companies will have to prove that their products solve urgent customer problems, their economics improve with scale and their growth can survive outside a generous funding market.
Technical credibility can earn a company its first check, but building a lasting business requires operating experience and commercial judgment. AI may allow companies to operate with fewer people and fewer layers, but that does not make talent less important. It puts more responsibility on the people at the top.
Investors should be asking not only whether a company has the right technology but also whether it has the right people to make the most of it.
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