Only twenty-three per cent of organizations say their workforce is fully ready for AI. That figure has fallen six points in a single year — even as the technology has spread into nearly every corner of the enterprise.
The number comes from Kyndryl's second annual People Readiness Report, published on 25 June and built on responses from 1,100 senior business and technology leaders across eight countries and six industries. The headline is a contradiction. Adoption is accelerating — 57% of leaders now say AI is embedded in core business processes or deployed broadly across the enterprise. Readiness is moving the other way.
The gap shows up in the results. Only 32% of organizations said they had achieved at least one of their top two AI goals. Just 11% had achieved both. So the machines are installed, the budgets are spent — and against a worldwide AI spending forecast Kyndryl puts at $2.52 trillion, most companies still cannot point to the outcome they bought the technology to deliver. Kyndryl's own framing is blunt: AI success is not driven by strategy or use case alone, but by whether organizations redesign how work gets done and manage that change all the way through.
The report does find a group getting it right. Kyndryl calls them Pacesetters — about 9% of the sample — who redesign roles, apply change management, and tie governance and training to stronger AI-related revenue growth. The lesson is not that AI fails. It is that AI bolted onto an unchanged organization fails.
What does this mean for the business owner who cannot afford a dedicated AI team, a change-management program, and a year of workforce retraining before any of it pays off?
It means the honest move is to start with a tool that does the work rather than one that demands the reorganization first. Viktor is built for exactly that. It is an AI co-worker that acts inside the tools you already use — not a platform you must deploy across the enterprise and then teach everyone to operate.
Where Kyndryl's leaders describe months of role redesign, Viktor runs on Claude, GPT-4, and Gemini from a single credit balance and picks the right model for each task itself — so there is nothing to configure and no model strategy to get wrong. Where the report describes AI that is embedded but not delivering, Viktor does tasks rather than handing back answers: it drafts and sends the email, builds the spreadsheet, researches the supplier, updates the document, then files the result where it belongs. Kyndryl's Pacesetters get there by redesigning roles across an entire company; a small business gets there by handing the job to a co-worker that already knows how to finish it. And where readiness depends on retraining a whole workforce, a single owner can put Viktor to work on real jobs the same afternoon and judge it on what it actually finishes.
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 difference between adoption and outcome. One fills a dashboard. The other clears your desk.
You get $100 of free credits to begin — no credit card, no time limit, no commitment. Explore Viktor properly. Do real work. 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.