A Gartner survey of 700 CIOs indicates that, by the end of the decade, all business IT work will involve AI, while bots will do 25 percent of that work by themselves. Good news: The analyst firm claims AI causes only one percent of job losses. Bad news: You’ll have to learn some new jargon.

To survive the transition, it might be helpful to at least sound like you are up on the latest terminology, even if you can’t bring yourself to use it. That way, you can understand what others think they mean as they style their way through the new era.

So here are the five key buzzwords and phrases to look out for.

AI accuracy survival kit

GenAI has an error rate of up to 25 percent depending on the use case. That might be OK in some areas, but certainly not in others. The problem is that 84 percent of CIOs and IT leaders “don’t have a formal process to track AI accuracy”, said Rob O’Donohue, VP analyst at Gartner. The idea of mitigating this by having a human in the loop, as some vendors still cling to, is unsustainable, as AI output is more than humans can keep up with.

Hence, there’s a need for an “AI accuracy survival kit”, which includes formal metrics to test AI output against an established norm, two factor error check, and so on. “We get one AI model to check another: a good enough ratio, a measure for AI accuracy, is just good enough for your initiative,” O’Donohue said.

Pipeline choke

The pitch from many a vendor is that agentic AI can handle the more mundane aspects of a team’s work, allowing its members to focus on higher-level things. The problem is that those very mundane bits of work are where junior members of staff once cut their teeth. Okay, so you don’t need to hire so many staff out of college or second-jobbers. But that lack of junior hiring also has a knock on effect and raises the question of who will replace senior or mid-career staff when they leave.

“When a senior staff delegates to AI some of the work that juniors used to do. That approach captures value, but it can stall your growth, so pair it with a robust talent development strategy, or risk choking your future pipeline,” said Gabriela Vogel, Gartner VP analyst.

• AI eats leisure time, makes employees work more, study finds
• AI benchmarks are a bad joke – and LLM makers are the ones laughing
• AI gets more ‘meh’ as you get to know it better, researchers discover
• AI agents get office tasks wrong around 70% of the time, and a lot of them aren’t AI at all

Experience compression

Almost opposite to the effect choking your pipeline is one which creates experience compression. Bear with us. The tech analysts’ argument goes that AI can allow junior members of staff to perform tasks well beyond their years.

O’Donohue cited an example from the insurance industry. “Companies are exploring GenAI simulators that can… mimic business scenarios. With this experiential knowledge, one company saw a 71 percent drop in failure rate for underwriter certification, resulting in senior underwriter output and junior salaries.”

“We call that experience compression, where junior people with AI are performing roles that senior people would be,” he said.

Behavioral by product, including skillatrophy

Deploying AI across an organization can result in some unintended consequences. People behave differently as a result. Some behavioral byproducts are good, others not so much. AI can generate meeting summaries and it might be a skill we can live without if we lose it.

“That’s probably a skill you can let atrophy, whereas you want your employees to keep their critical thinking skills, their decision making skills, they’re the behavioral byproduct you don’t want to have: that’s a negative sign,” O’Donohue said.

Capacity paradox

Because the AI boom seems to have caught the attention of senior business leaders for the current moment, tech teams might see the benefit in terms of extra capacity. But having built the teams to support the expected demand for AI, they are going to continually pitch new projects to the business.

“We are warning the CIO. We call it the capacity paradox and saying, ‘your organization is now going to be embedded with AI. You’re going to get all this massive, supercharged team with a bunch of capacity now, if you don’t use that space and time and resources to find alternatives that go beyond it, your teams might be seen as redundant, and then we go back to that notion of redundancies,” Vogel said. ®