Software Leaders Share Insights at Baird Silicon Slopes Event

AI’s Next Frontier

AI remains the defining technology of this era, with a total addressable market in the trillions and investment at unprecedented levels. But where does it go from here?

Key Takeaways:

• AI Spending is Historic, and So is the Potential ROI – Infrastructure investment is accelerating, and while concerns of overcapacity exist, the long-term return on investment (5-10 years) remains compelling.
• Falling Costs, Rising Adoption – The cost of AI training and inference is dropping rapidly due to innovation and competition, making AI more accessible across industries like healthcare, financial services, and manufacturing.
• Multiple AI Winners Will Emerge – While tech history suggests winner-take-all dynamics, this time, at least three major AI platforms are expected to dominate.
• Apple’s $500B Bet on AI – Apple announced plans to spend $500 billion over five years to expand its AI capabilities—likely just a portion of its total AI investment.
• Software’s Pricing Model is Changing – AI is shifting software’s TAM into “labor TAM,” meaning automation could replace 50% of certain workforces. Investors are closely watching whether pricing moves from subscription models to consumption-based pricing.

What It Takes to Reopen the IPO Window 

The private markets panel tackled a major question: When will IPOs return? The answer: selectively and with a focus on efficiency.

Key Takeaways:

• Valuations Need to Reset – The massive pull-forward effect of 2021 left many startups waiting to grow into their past valuations, creating a slow IPO market.
• Venture Funding is at Multi-Decade Lows – With LPs concentrating capital in mega-funds, private capital markets are highly selective.
• M&A Will Lead Before IPOs – Private equity (PE) is expected to return first, as large firms prefer taking companies private over dealing with distributed cap tables.
• Investors Want a Clear Growth Story at IPO – Companies don’t need $400M+ in revenue, but they must demonstrate a path to profitability and consistent growth (ideally 25%+ annual growth).
• AI Continues to Dominate VC Investments – 46% of all venture dollars in 2024 are flowing into AI companies, particularly in LLMs and application-layer AI.
• The Four Metrics Investors Care About at IPO:
  • TAM (Total Addressable Market)
  • Sustainable & Proprietary Competitive Advantage
  • Business Model Durability
  • Strong Leadership Team

Bottom Line: The IPO market isn’t closed—it’s just highly selective in the near-term. Companies that can prove efficient, durable business models, scale and competitive advantages will lead the next wave of public listings.

The Future of AI: What Comes After LLMs? 

The dinner panel took a forward-looking approach: What happens after LLMs? How does AI evolve beyond today’s breakthroughs?

Key Takeaways:

• ROI is the Key to Enterprise AI Adoption – Customers won’t buy AI solutions unless they can prove tangible business impact.
• LLM Scaling is Hitting a Limit – The next breakthrough needs to go beyond just scaling up models to specialized, industry-tuned AI.
• AI is Reshaping the Developer Landscape – AI-driven tools are transforming legal, marketing, and programming workflows.
• The Web is on the Way Out – AI-powered agents may soon replace traditional web interfaces, fundamentally changing how we interact with technology.
• S. Government is Betting Big on AI – A bipartisan push for digital transformation is creating major opportunities, with the Department of Defense partnering with AWS and Palantir to expand AI capabilities.

The next AI revolution won’t be about “bigger” models—it will be about “smarter” AI that seamlessly integrates into workflows.

Perspectives from Company Presentations

Impact of Macro Uncertainty

• While numbers felt safe coming into this year, there is a unanimous view that the world has changed.
• Tariff concerns are focused more on the larger macro environment and consumer sentiment, and less on near-term direct impact to business performance

Opportunities Around AI

• Adoption of GenAI remains early with few customer-facing applications in production; however growing AI adoption should be longer-term tailwind
• Customers are seeking GenAI use cases to enhance productivity, marking a positive shift from “infrastructure only” to “applications on infrastructure.”
• As GenAI adoption ramps, there is an increased focus on reliable data to drive better outcomes that are safe and secure.
• Continue to see tailwinds around natural language processing (NLP) and companies who have seen success are crediting NLP in assisting with increased efficiency and productivity.
• AI companion adoption is driving higher engagement with customers, which leads to potential AI product expansion as a result.
• While adoption has picked up overall, companies are still seeking ways to more effectively monetize AI – it will take time for AI to start moving the revenue needle

Packaging and Pricing

• With increased GenAI solutions more companies are pivoting to hybrid “solutions-based” models.
• While shifting pricing models pose a risk, companies need to get it right and ultimately, the companies that deliver the value will get paid for it