Last week, I had the pleasure of attending an insightful panel hosted by Introduction Capital, led by the ever-impressive Karen Azlen, on The Role of AI in Startups and Venture Capital. The session, moderated by Kathryn Wortsman (Amplify Capital), featured a sharp and candid conversation with Eva Lau (Two Small Fish Ventures), Matt Cohen (Ripple Ventures), and Peter Shi (Maverix Private Equity).
As someone deeply involved in innovation and capital deployment, this conversation reinforced how artificial intelligence is not just reshaping how companies operate—it’s redefining the fundamentals of venture capital, entrepreneurship, and business building.
🧠AI ISN’T NEW—BUT THE ACCELERATION IS UNDENIABLE
AI has long been part of the toolkit in sectors like banking and media. Wattpad was using AI in 2012 to analyze millions of data points. Financial institutions have leaned on AI models for credit scoring and fraud detection for decades. But today’s shift isn’t about the tools—it’s about the speed of deployment, the ubiquity of applications, and the expectations from both customers and investors.
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⚙️ AI AS INFRASTRUCTURE: IT’S ABOUT OUTCOMES, NOT ALGORITHMS
What resonated deeply was the notion that AI is no longer something we “use”—it’s becoming something we expect. Think customer service platforms that use AI to mine a company’s entire knowledge base for instant answers. Or municipal services like 311 and 911, where AI triage can save time, money, and lives. For example, 911 calls cost ~$50 each, yet 50% are non-urgent. AI can help route them more effectively.
In sectors like legal, AI is already proving transformational—assessing the likelihood of success in personal injury or workplace claims, which number in the hundreds of thousands daily. These insights are key to unlocking legal financing. Process automation is the foundation, but predictive insights are where real value emerges.
đź’Ľ THE EVOLUTION OF VENTURE CAPITAL IN AN AI-DRIVEN WORLD
AI is changing how VCs operate just as much as the companies they fund. What used to be a 1-in-10 bet is now a 1-in-5,000 longshot. With generative AI tools enabling faster prototyping, investor diligence is being compressed and automated. Sourcing, due diligence, portfolio monitoring—entire VC workflows can now be partially or fully AI-powered.
But with so many new entrants building in AI, a familiar challenge returns: how do you spot the signal in the noise?
Key factors include:
Is the problem real, and is the timing right?
Does the company have IP defensibility beyond being an API wrapper?
Are the unit economics and go-to-market strategy robust enough to survive scaling?
Some funds, like EQT's Motherbrain, are investing heavily in internal AI to augment their investment strategy. Meanwhile, the real edge may no longer lie in proprietary tech—but in controlling customer relationships and distribution channels.
🔄 BLURRING LINES BETWEEN VENTURE CAPITAL AND PRIVATE EQUITY
As AI startups mature, the distinction between VC and PE is fading. Traditional BPO services (like insurance claims processing) are being replicated by nimble, AI-powered startups. These new entrants need to meet enterprise-grade expectations—on compliance, security, and data privacy—to win contracts. VCs are operating more like PE firms with a platform mindset, while PE firms are adopting earlier-stage tech strategies. It’s a convergence fueled by the democratization of software and the race to own sticky, recurring revenue models.
đź” EMERGING TRENDS SHAPING THE FUTURE OF AI IN BUSINESS
Some of the most exciting developments discussed:
Edge computing is becoming vital—on-prem AI is seeing a resurgence for privacy and cost control.
Generative SEO is transforming how we think about websites—replacing static pages with dynamic, AI-optimized content.
AI in manufacturing is moving from aspirational to operational, using predictive analytics and real-time optimization.
AI-designed chips (ASICs) are reducing the time and cost to create powerful hardware optimized for machine learning.
In the near future, we may not call it “AI” anymore—it will simply be how modern businesses operate.
⚠️ AI RISKS AND THE URGENT NEED FOR TRUST
No conversation about AI is complete without addressing risks. From hallucinations in LLMs to misinformation campaigns in elections (Slovakia was cited as a recent case), the stakes are rising. As AI becomes more powerful, so do the bad actors trying to manipulate it. Responsible AI, data integrity, and social engineering safeguards aren’t optional—they’re essential to building trust in this next era.
🧠FINAL THOUGHTS
What I appreciated most from this panel was the grounded, thoughtful tone. It was not about AI hype—it was about economic reality, strategic focus, and long-term defensibility. In a world where tech is increasingly commoditized, success will hinge on solving real problems with real urgency—and building businesses that can withstand the next wave of disruption.
Many thanks again to Karen Azlen and Introduction Capital for convening such a rich and relevant conversation. It was a timely reminder that while AI is accelerating everything, the fundamentals still apply: timing, team, traction, and trust.
Peggy Van de Plassche is a seasoned advisor with over 20 years of experience in financial services, healthcare, and technology. She specializes in guiding boards and C-suite executives through transformational change, leveraging technology and capital allocation to drive growth and innovation. A founding board member of Invest in Canada, Peggy also brings unique expertise in navigating complex issues and fostering public-private partnerships—key elements in shaping the Future of Business. Her skill set includes strategic leadership, capital allocation, transaction advisory, technology integration, and governance. Notable clients include BMO, CI Financial, HOOPP, OMERS, GreenShield Canada, Nicola Wealth, and Power Financial. For more information, visit peggyvandeplassche.com.