AI as a Force-Multiplier: A Venture Partner's Perspective on Efficiency and Growth

Early-stage investing is as much about building great companies as it is about placing capital. As an operator-turned-investor, I joined PHX Ventures to bring decades of product and operational experience to founders. Before joining the firm I spent more than twenty years in higher-education technology, designing products, guiding organizational change and launching the first cloud-based student information system (SIS). At CampusLogic we created the industry's first Student Financial Success platform, proving that the right technology, integrated into existing processes, can change outcomes. That operational lens continues to shape how I view artificial intelligence (AI) today.

The surge of AI investment — and the fear of missing out

The venture ecosystem is awash in AI. According to Sapphire Ventures, venture capital investment reached about $505 billion in 2025, a 30 percent year-over-year increase, and AI captured more than half of that total. Funding for AI-native startups grew 146 percent to $136 billion, and eight of the ten largest funding rounds on record occurred between early 2025 and early 2026. In some cases, companies such as Anthropic went from $1 billion to $14 billion in annual recurring revenue in about a year. These numbers are intoxicating, and they're creating a very real fear of missing out (FOMO) among executives.

That FOMO isn't confined to investors. A recent survey of IT leaders found 63 percent worry their companies will be left behind without AI, and 55 percent say customer pressure is a key driver for adoption. In Australia, nearly 73 percent of IT leaders fear falling behind and 97 percent plan to increase AI investment, even though they cite cost, talent gaps and complexity as major concerns. In this environment the temptation is to bolt AI onto every workflow, hoping it delivers miraculous growth. But adopting AI out of fear rather than purpose is a recipe for wasted time and distracted teams.

What AI actually delivers

The reason AI commands such attention is that — when deployed thoughtfully — it does unlock meaningful efficiency gains. Microsoft's 2026 Work Trend Index found that 66 percent of AI users say the technology allows them to spend more time on high-value work, and 58 percent report producing work they could not have created a year ago. Among advanced "frontier" professionals those numbers jump to 80 percent. At the same time, AI raises the premium on human judgment: 50 percent of users say quality control is more important and 46 percent say critical thinking matters more. A remarkable 86 percent treat AI output as a starting point, not a final answer, and many intentionally perform some tasks without AI to keep their skills sharp. In other words, the technology excels at accelerating rote tasks and surfacing insights, but it relies on humans for oversight, context and creativity.

How we advise founders

At PHX Ventures we invest exclusively in B2B software and AI companies. That focus gives us a unique window into how AI can accelerate early-stage growth. Here are a few principles we share with portfolio founders:

• ·Start with assistive use cases. The biggest wins come from freeing people's time. Automating customer support responses or summarizing user feedback allows teams to devote more energy to product development and customer relationships. AI users spend more time on high-value activities — but only when the technology is integrated into real workflows.
• ·Invest in data and governance before scaling. Many companies rush into AI without clean data or clear processes. Founders should ensure their data is reliable and that models are monitored for bias. Every AI recommendation should have a human decision-maker.
• ·Treat AI as a co-worker, not an autopilot. The Work Trend Index underscores that most users view AI output as a draft. Encourage your teams to challenge what AI produces, refine it and use it as a thought partner. This approach guards against complacency and keeps skills sharp.
• ·Focus on efficiency before valuation. The explosion of AI funding is impressive, but capital alone doesn't build enduring companies. The founders we back concentrate on how AI drives faster product iterations, lower customer-acquisition costs and more resilient operating models. That operational discipline ultimately commands the valuations investors are chasing.
• ·Beware of hype cycles. Not every AI model will be a category winner. While more than 80 companies have crossed the $100 million revenue mark quickly, thousands more are experimenting with AI without a clear business case. We tell founders to resist chasing every trend and to prioritize the use cases that move the needle for their specific customers.

Building durable, AI-native companies

My time building the first cloud-based SIS taught me that technology succeeds when it fits seamlessly into people's workflows. Venture-backed startups live and die by their ability to scale efficiently. AI can be a powerful force-multiplier for early-stage companies — accelerating product development, improving customer experience and unlocking data-driven insights. But its true impact comes when leaders combine the technology with clear operating systems, rigorous change management and a commitment to human judgment. In a market where funding and FOMO are high, the startups that thrive will be those that use AI to make their teams smarter and their businesses stronger — not those that adopt AI simply because everyone else is doing it.