Sixty-four percent of CEOs in the private equity and principal investment sector report that their AI projects have delivered no cost impact whatsoever over the past year. Eighty-two percent say they have seen no effect on revenue. Those numbers come from PwC's 29th Global CEO Survey, and they land at a moment when global AI spending is projected to reach $2.5 trillion in 2026.
The problem, according to the Forbes analysis, is not that AI itself is broken. The technology works. What fails is execution. Companies buy platforms, hire consultants, launch pilot after pilot — and then watch the entire effort stall before a single workflow actually changes. The report calls it the "AI execution gap," and it is widening fast.
The pattern repeats across industries. A procurement team licenses an AI tool but never connects it to the purchasing system. A finance department runs a proof of concept that impresses the board but requires a dedicated engineer to maintain. An operations group signs a six-figure annual contract for a platform that three people use. The AI is technically functional. The implementation is not.
Meanwhile, the 36% who do report measurable progress share a recognizable pattern. They started with a single defined use case. They embedded AI into the tools their teams were already using rather than asking people to learn a new platform. And they measured outcomes week by week — not quarter by quarter. These are not the companies with the largest budgets. They are the companies with the clearest briefs.
What does this mean for the business owner who cannot afford a dedicated AI team, a six-figure consulting engagement, or a year-long integration project?
It means the execution model matters more than the model itself.
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.
That is the execution model PwC's outlier companies arrived at independently. An AI tool that lives where work already happens, that handles the task rather than generating a suggestion, and that starts producing output on day one — not after a procurement cycle.
With Viktor, you can hand off a competitive analysis and get back a structured report in minutes. You can ask it to draft a client proposal from your meeting notes and have it arrive in your inbox formatted and ready to send. You can run a weekly dashboard pull that used to take a junior analyst half a day. Viktor runs on Claude, GPT-4, and Gemini — all three included in one credit balance — and selects the right model automatically. No vendor selection. No infrastructure buildout. No six-month implementation timeline.
The 64% who got nothing from AI made a common mistake. They treated AI as a technology project — something to procure, pilot, and evaluate. The 36% who saw results treated it as a workflow decision. They picked one task, put an AI tool inside the process, and let it work.
You get $100 of free credits to begin. No time limit, no commitment. That's enough to do real work and see what Viktor can actually do before you spend a penny. There's also $50 off your first bill. You must use this exact link to receive both benefits.
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.