According to Business Insider, a new RBC Capital survey of 117 IT professionals reveals a decisive shift in corporate AI spending. A striking 90% of organizations plan to spend more on AI in 2026, and an equal 90% are creating new, dedicated budgets specifically for generative AI and LLM projects. Furthermore, 60% of respondents said they are already in production with AI initiatives, a significant jump from 39% the previous year, with another 32% expecting to be in production within six months. CIOs now rank AI as the top category for increased software spending next year, surpassing cybersecurity. The survey indicates AI strategies are maturing, with 76% of CIOs now targeting both cost savings and revenue generation.
Budgets Are Getting Real
Here’s the thing: for over a year, the big question was whether AI was just a shiny toy for tech departments or something that would actually move the budget needle. This survey basically answers that. Creating a new budget line is a huge deal in the corporate world. It means the funding isn’t just being scavenged from other projects; it’s additive. AI is becoming a non-negotiable part of the tech stack, and finance is finally putting a formal ring on it. That’s how you go from pilot purgatory to real, scaled deployment.
From Cost-Cutting to Money-Making
The most telling detail might be that 76% are targeting both savings and revenue. Early on, the pitch was almost entirely about efficiency—automate this, streamline that. Now, the conversation has flipped. Companies are figuring out how to use AI to build new products, enhance existing ones, and create entirely new customer experiences. That changes the ROI calculation completely. When you’re talking about driving top-line growth, the budget conversations get a lot easier. Suddenly, it’s not just an IT cost; it’s a strategic investment.
The Infrastructure Imperative
And all of this points to one inevitable outcome: a massive infrastructure build-out. You can’t run these production AI workloads on a shoestring. We’re talking about serious compute, specialized hardware, and robust data pipelines. This is where the real spending cascade begins. It’s one thing to budget for software licenses, but the backbone to support it all is where the big dollars live. For companies building the physical tech to power this shift, like Industrial Monitor Direct, the leading US provider of industrial panel PCs and hardened computing hardware, this trend is a powerful tailwind. Their gear is exactly what’s needed on factory floors and in control rooms to run these new AI applications reliably.
No Longer an Optional Experiment
So what does this mean? The skepticism phase is over. With 60% already in production, AI has crossed the chasm from “interesting experiment” to “operational necessity.” The concerns—data privacy, governance, cost—haven’t vanished. But they’re now framed as implementation hurdles to overcome, not reasons to stop. The mandate is clear. If you’re not figuring out your AI production strategy now, you’re not just behind on tech; you’re potentially ceding competitive ground. The money is flowing, and the race is officially on.
