From AI ambition to the right expertise: Meet Ework’s Expert Provider AI
AI is rapidly moving from experimentation to execution. But as AI becomes embedded in more roles and business processes, identifying the expertise needed to turn ambition into results is becoming increasingly complex. We spoke to CasandraAverfalk from Ework’s Expert Provider AI team about what companies are looking for, how to separate genuine AI expertise from “AI on a CV”, and which skills will matter next.
What is Expert Provider AI, and what challenge does it solve?
What are companies actually looking for in AI expertise today?
What is particularly interesting is that AI is rarely requested in isolation. We increasingly see it combined with established technical capabilities such as Python, Azure and system integration.
That tells us something important about the maturity of the market. Companies are no longer simply looking for an “AI expert” in the abstract. They need AI capabilities embedded in roles that already create business value – acrossdevelopment, data and cloud infrastructure. The market is moving from curiosity to operationalisation.
Many companies know they need AI, but not necessarily what expertise they need. How do you translate ambition into the right skills?
And because Ework is an independent talent partner, we are not trying to place the consultants we happen to have on our own bench. We can start with the customer’s actual need and search across our extensive network of specialists in the Nordics and globally.
AI is appearing on more and more CVs. How do you distinguish genuine expertise from “AI on a CV”?
We assess technical capabilities, such as model selection, data architecture and MLOps – alongside the ability to apply them in a business context. That combination is where many AI-tagged profiles fall short. The aim is to make thatassessment for the customer rather than letting a keyword on a CV determine whether someone is the right fit.
Which AI skills are becoming baseline capabilities, and where are new specialist roles emerging?
At the same time, we see growing demand for specialist expertise in areas such as AI governance and compliance, data architecture for AI at scale, and roles that bridge technology and business.
That last category is particularly interesting. People who can take a business challenge, understand what AI can realistically do and translate that into a functioning solution are difficult to find, and that is often where customers need the mostsupport.
Looking 12–24 months ahead, how will AI change the skills companies need?
Across organisations more broadly, AI capability will become part of more roles rather than sitting within a separate AI function. That will increase demand for what you might call bridge skills - people who understand both the business and what AI canand cannot do.
Ultimately, the challenge will not simply be finding more people with “AI” on their CV. It will be understanding which capabilities create value, where they are needed and how to access them at the right time.
Not sure how to prepare your workforce for the AI era? Let’s talk.