Introduction

AI made products faster, but GTM problems stayed the same. This report shows why AI helps only when teams fix the basics.

What's the problem it solves?

Companies keep adding AI features but still struggle to turn them into real revenue. The report explains why GTM alignment, pricing, focus, and measurement matter more than speed of product shipping.

Quick Summary

The High Alpha 2025 SaaS Benchmark Report shows a clear pattern. Almost every company shipped AI features, yet most still fail to monetize them. The issue is not the tech. It is the lack of a solid GTM engine. Founders still name GTM execution as the number one thing that keeps them up at night. Even with AI progress, teams still cannot answer basic questions about who they target, how they position, and how they price.

The data makes the gaps obvious. Companies build AI fast, but they do not explain its value clearly. Pricing has evolved in the market, but many teams still sell with outdated models. Only a small share measure AI impact with hard KPIs, so they cannot prove value or scale it. And once companies grow, most new ARR comes from current customers, yet teams still act like new logo hunting is the main goal.

The report’s message is simple. AI raised the ceiling, but GTM still decides the outcome. Companies that want stronger results in 2026 need to rebuild their ICP with real data, update pricing to match value, treat expansion as a core motion, measure AI impact properly, and align all teams around one shared plan.

Key Takeaways

• GTM remains the number one problem for founders, even with rising AI focus.
• 70 percent shipped AI features, but only 41 percent monetize them.
• Pricing is shifting to hybrid and outcome based models, but messaging has not caught up.
• Fewer than 25 percent measure AI impact with real KPIs.
• After twenty million ARR, most growth comes from current customers.
• AI boosts product speed, but only aligned GTM turns it into revenue.

What to do

• Rebuild your ICP with real data from retention, win rates, ACV, and customer health.
• Test hybrid and outcome based pricing that matches real value delivered.
• Treat expansion as a core motion and build playbooks, comp, and workflows for it.
• Measure AI impact with clear KPIs like time saved, errors reduced, and revenue influenced.
• Align product, sales, marketing, customer success, and finance under one shared plan.

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