Nordic State of AI - Central Observations 3/5: AI Talent

The AI talent bottleneck is getting worse and more domain-specific 

The gap in AI talent is not just widening, it is becoming a sector-specific crisis that urgently demands attention from companies.

In today's rapidly evolving digital landscape, AI transforms industries and alters the operational dynamics of businesses. However, the successful adoption and integration of AI critically depends on one key element: expertise. 

In this five-part blog series, we will dive into the central observations of the Nordic State of AI report, an annual report examining AI adoption across leading Nordic multinational companies by surveying their current use of AI. In this third part, we will explore the challenges and opportunities companies are facing related to AI talent.

The Nordic State of AI report highlights a critical need for professionals who possess both technical AI skills with domain-specific expertise and a broader technological understanding. 

The talent shortage is not merely a broad gap, but it is increasingly becoming specific to certain industries, making it more challenging to find the much needed expertise as the required skills become more and more specific to particular domains.

The escalating lack of AI talent

"One year ago, this was a problem. Now, it has become chaotic."‍

‍Niko Vuokko, PhD

CTO, Silo AI 

What was once merely a challenge has now escalated into a severe bottleneck. Reflecting on last year's data, 35% of companies identified the lack of AI talent as their biggest challenge, a concern that has grown even more acute by 2024, with over half (51%) of companies reporting a severe shortage of essential AI expertise.

As a result, efforts to recruit new AI specialists are ongoing. Between 2021 and 2022, over half of companies hired only 1-5 new AI specialists each year. In 2023, only a third of companies maintained the same hiring pace. Meanwhile, the number of companies adding 6-20 AI specialists annually has increased significantly, from 7.6% to 22.85% over two years. 

Furthermore, the number of companies that do not hire any AI talent has decreased.

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The critical shortage in machine learning and data science roles

Companies struggle to fill specialized roles like machine learning engineers and data scientists, which are vital for AI projects but require years of specialized training. According to the report, in the next 12 months, 65.7% of companies are seeking to hire data scientists, 57.14% are looking for data engineers, and 54.29% report recruiting machine learning engineers.

"The AI talent bottleneck is not as severe in product and business roles, where skills can be acquired relatively quickly. The largest gap exists in technical machine-learning roles, which typically require at least five years of university training."‍

‍Niko Vuokko, PhD

CTO, Silo AI 

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The gap in AI skills isn't limited to the technical aspects of creating AI algorithms but also extends to integrating AI into existing technology systems and increasing AI literacy among all staff. Additionally, there is a growing need for experts who understand both AI technology and specific industries, as this combination can make AI applications more effective and aligned with business goals.

Delay in developing a robust pipeline of AI-proficient professionals risks widening the gap between potential technological advancements and their practical applications.

Fostering cultural development, collaboration, and AI literacy

For business leaders and policymakers, the path forward entails enhancing AI education, supporting continuous professional development, and nurturing a culture that values learning and collaboration.

According to the Nordic State of AI report, the development of basic AI literacy is progressing well, although it is a substantial effort that requires time.

“Basic AI literacy is scaling quite quickly because it’s something you can relatively easily scale out. We’ve trained thousands of people in our client companies – There is a lot of scale, but it still takes time.”‍

‍Niko Vuokko, PhD

CTO, Silo AI 

Expanding the talent pool will necessitate more than traditional recruitment strategies. It requires a paradigm shift towards fostering an ecosystem where continuous learning and innovation are prioritized, preparing the workforce for future AI technology demands.

This talent strategy is not solely about maintaining competitiveness. It's about leading in a future where AI permeates all sectors. Europe's commitment to developing a robust pool of AI talent will be crucial to its global standing.

Reaching scale requires focus

One key solution for companies aiming to alleviate talent bottlenecks is focus. The more focus is maintained, the less training individuals need. A decreased dependence on diverse domain expertise reduces the need for process changes. Focus enhances scalability.

"The more you have focus, the less you have to train people to understand the new technology. The less you need different domain expertise, the less you need to change processes."

‍Niko Vuokko, PhD

CTO, Silo AI 

Moreover, focus aids in various other aspects. It is essentially about energizing the flywheel. Achieving scale with outcomes that are not only theoretically attractive but also impressively concrete is the challenge. The solution to maintaining focus entails avoiding the rush to adopt AI across the board immediately, which often results in many initiatives fading away due to a lack of sustained effort in a consistent direction. 

It is more effective to prioritize core business domains over opting for simple, low-impact use cases. Additionally, companies should target significant, long-term gains rather than marginal efficiency improvements.

‍_{The annual Nordic State of AI report provides an overview of the use of artificial intelligence in the Nordic region, with the goal of offering business leaders, academics, policymakers, as well as anyone interested, a comprehensive view of the latest changes and developments in Nordic AI.}

_{Read the report.}

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