One in three senior business leaders does not know what their AI deployment is costing them. That is not a projection. It is a finding from KPMG's Global AI Pulse Q2 2026, a survey of executives tracking the state of enterprise AI adoption globally, published this week.
The report captures a market moving faster than most companies expected. Twenty-two percent of organizations now have AI embedded in everyday work — up from 13 percent in Q1, the single largest quarterly jump at any maturity stage since KPMG began tracking. The number moving from experimentation into active adoption nearly doubled in three months. On the surface, those numbers describe an industry gaining genuine momentum. Look more carefully and what you see is a large cohort running hard into a cost structure they cannot yet clearly see.
The mechanism is familiar to anyone who has managed a technology transition. Per-seat licenses for one AI tool. A separate subscription for another. Model costs that spike when usage patterns change. Integration charges. An API fee bundled into something else. Thirty-three percent of leaders in the KPMG survey cited limited understanding of usage costs as the primary barrier to further AI deployment — not security, not regulation, not skills gaps. Not knowing what the bill will be.
What does this mean for the business owner who cannot afford a dedicated AI team? The enterprise cost problem scales down. The specific numbers are smaller, but the underlying structure is identical: multiple tools, multiple pricing models, no single number to report. That is before you account for the management overhead of handling access across platforms, training staff on different interfaces, and troubleshooting when something breaks.
Viktor lives inside Slack and Microsoft Teams. You @mention it in a thread the same way you would ask a colleague. The output — a PDF, a report, a task created in your CRM, an email drafted in Gmail — lands where it should land.
Viktor also solves the cost visibility problem directly. It runs on Claude, GPT-4, and Gemini — all three included in a single credit balance, with the right model selected automatically for each task. There is no separate subscription per model, no per-seat license per tool, no invoice from four different vendors at month end. You use credits. You can see exactly what you have spent. That one number is your AI cost.
Three things that produce a clean cost line in practice: a marketing team member running weekly competitor research through Viktor instead of maintaining a separate research tool subscription. An operations lead drafting supplier communications across multiple email chains without switching platforms. A finance analyst running document summaries and data extraction that would otherwise require a dedicated afternoon from a staff member. One tool. One credit balance. One number to put in the budget meeting.
You get $100 of free credits to begin. Registering for the free credits runs a $1 card check — it is a validity hold, not a charge, and it releases automatically. No time limit, no commitment. When you are ready to go further, $50 comes straight off your first bill.
Disclosure: Some links in this article are affiliate links. If you choose to get started with Viktor using the links provided, I may receive a commission — at no additional cost to you. I only recommend tools I use and believe in.