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?
- Expert Provider AI is the advisory core of Ework’s broader AI offering. We are a team of dedicated experts helping organisations move from AI ambition to concrete action. The challenge is quite fundamental: many organisations want to capture the potential of AI but struggle to understand whether they have the capabilities needed to make it happen. We help identify those needs, navigate a rapidly changing market and find the right expertise, rather than leaving the customer to figure it all outon their own.
- Our quarterly analysis of customer demand and professional supply gives us a clear indication of where the market is heading. AI is now among the five most requested skills across Ework, alongside established areas such as test management, project management, SQL, SAP and Python.
- This is where two parts of Ework’s AI offering come together. Our Skillshift Lens helps organisations understand how AI is reshaping roles, ways of working and future skills requirements. It provides a starting point for understanding what is changingin their organisation. Expert Provider AI then helps turn that insight into action. Our dedicated AI experts work with the customer to define the need, navigate the market and secure the right capabilities. It is not simply about delivering a stack ofCVs.
- That is really at the heart of the value we provide. We look beyond the keyword and into the context. Has the person actually delivered AI solutions in production and achieved measurable outcomes, or have they completed a course and experimented with a few tools?
- Basic AI literacy is rapidly becoming a baseline capability across many digital roles. Being able to use AI tools productively, prompt effectively and understand their limitations is increasingly comparable to how basic data literacy or Excel skillsbecame expected over time.
- I think we will see two developments happening in parallel: Within dedicated AI roles, the emphasis will increasingly shift from pure model development towards integrating, operating and governing AI at scale. Skills in areas such as MLOps, AI security and compliance will therefore become increasingly important.
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.
