Anna Perelyhina

Strategic Summary for SaaS Leaders: While consumer AI usage is high, enterprise AI adoption remains low. Most SaaS organizations are currently in the "Messy Middle"—the transition from AI experiments to scaled operational integration. Success in 2026 is defined not by "isolated AI features," but by redesigning internal workflows, hardening data infrastructure, and treating AI as a horizontal system capability rather than a vertical product add-on. There is a nagging feeling in offices and...

In 2026, the gap between a successful AI feature and a failed one isn't the model you choose (GPT-5, Claude 4, or Llama 4). The gap is your Data Supply Chain. If your data is fragmented, delayed, or unstructured: Your AI will hallucinate. Your AI will generate irrelevant outputs. Your AI will burn tokens without generating revenue. Your AI will fail in enterprise environments. If your data is messy, your AI will be hallucinatory at best and a liability at worst. To scale, you don't need to be...

After working with many B2B SaaS companies approaching the end of their Series A runway, a familiar question inevitably comes up: “How do we increase ARR without rebuilding the product?” Product is not a Cost Function but a SaaS revenue lever It’s a fair question. Time is no longer abundant. Pressure is real. And results need to show fast. In a previous article, I outlined a step-by-step framework for how founders can stabilize and scale a B2B SaaS business quickly—without defaulting to a...