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What Software Leaders Learned at Vista’s 2026 CXO Summit
Software companies have widely embedded AI into their products and operations. Success now depends on proving AI’s impact.
Companies across Vista’s portfolio are releasing Agentic AI products and implementing AI across internal functions like sales and marketing. Turning that activity into measurable results was the focus of Vista’s 2026 CXO Summit, which brought more than 550 executives and Vista leaders together in Miami.
The Market Is Rewarding AI Transformation
Investors are judging software companies on a new set of results.
Vista Senior Managing Director Monti Saroya explained that old measures of software performance, like subscription revenue and seat growth, are no longer sufficient. Now, investors are looking for evidence of returns on AI investment, including Agentic AI products that customers pay for and operations that can run measurably leaner and faster because of AI.
Panelists were clear that bolting AI features onto existing products and workflows won’t meet that bar. Instead, they challenged companies to imagine how their business would look if AI had always existed, and to build toward that vision.
We believe incumbents are well positioned to do it, with customer relationships, workflow context and proprietary data that AI-native startups have to build from scratch. The goal, Saroya said, should be to use those assets to become the system of action for customers’ work. Companies that simply wrap frontier models in their software are building on technology that changes every six months, if not more frequently.1
Alegeus offers a recent example. Vista’s sale of the healthcare benefits technology company to Optum closed in July. Alegeus brought AI to a foundation of deep partner relationships, proprietary data and strong growth. Its first AI products automate high-volume work like claims processing and identity verification, early steps in turning AI into tangible business value.
Drive the Top and Bottom Lines
In our view, transforming a company around AI should aim to deliver results on both the top and the bottom lines – potentially leading to higher revenue and stronger margins.
“You have to drive both bottom-line and top-line impact. You can’t pick and choose – that world was two years ago.”
Nadeem Syed
Vista Senior Managing Director and Head of Value Creation
That starts with measuring AI against clear targets across the business. Pilot counts and token consumption demonstrate activity. Transformation can show up in the profit and loss statement (P&L) through customers who use and pay for AI products and through lower costs across the business.
Vista Operating Managing Director Patrick Nichols shared examples of how Vista evaluates AI progress, each tied to a financial outcome:
- Innovation and revenue: growing the share of net revenue that comes from AI products
- Product development: improving research and development (R&D) efficiency, measured by more output per dollar spent on R&D and lower R&D spend as a percentage of revenue
- Customer support: raising the AI net deflection rate (the share of support requests resolved by AI without a human agent) and reducing support costs as a percentage of revenue
- Customer success: increasing gross revenue retention and annual recurring revenue (ARR) per customer success manager
- Marketing: improving pipeline generation and lowering sales and marketing spend as a percentage of revenue
Portfolio companies on stage showed what results look like on each side of the P&L. One risk and compliance management platform saw 80 percent of ARR from new customers over the past 12 months come from customers who chose it for its generative AI capabilities. Meanwhile, a company providing sales and marketing technology cut roughly half its development costs in six months.2
Leadership Can Make AI Work
The most difficult parts of AI transformation are often organizational. They involve leadership decisions about which products should become agentic, which internal workflows should be rebuilt and how roles and incentives should change.
Vista Managing Director Beth Knuppel presented portfolio data on how leadership teams work together, scoring 55 portfolio companies on five behaviors: trust, productive conflict, commitment, accountability and a focus on results.
The findings showed how closely executive team dynamics track with AI outcomes.3 Teams that scored well performed better on the financial AI metrics Vista tracks and, on average, saw stronger growth and profitability than lower-scoring teams. Of the five behaviors, peer accountability among executives was most closely linked to AI success.
Without alignment and accountability across the executive team, AI experimentation can become siloed, making it harder for companies to move from isolated pilots to broader deployment and measurable results.
What Comes Next
In our view, AI transformation has unfolded in three stages: experimentation in 2024, deployment in 2025 and measurable P&L impact in 2026. Next year, Vista expects companies to raise their AI ambitions, starting with the impact they want to create and working backward to the teams, products and AI that will deliver it. That means building AI revenue and margin targets into 2027 operating plans and executing against them.
Vista Operating Managing Director Jessica Cash urged companies to make that shift quickly. “The window is open, but we do not think it’s going to be open for long,” she said. “Some of the things that are most cutting edge in this room will become table stakes in a year, even in a quarter.”
When portfolio leaders reconvene at next year’s CXO Summit, we expect companies will be focused on demonstrating and scaling results.
