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CONTENT:
The next steps of the report are talking about the AI demand, the rise of industries and multidisciplinary AI experts but also AI portraits of freelancers and projects, and few client cases projects.
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AI, beyond
the hype!
At Malt, we’ve had the privilege of observing thousands of AI projects of companies of all sizes, across industries in Europe, with their pitfalls and successes. We’ve also had the internal experience of building AI features since 2019. Three areas make all the difference to ensure impactful AI:
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Introduction
The focus of this analysis has been on the skills, job titles, and job categories on the Malt platform from 2021 to 2024. We started the analysis by building
a list of AI keywords and extracting all the projects and freelancer profiles where at least one of the keywords appear in
the skills or job titles over all European Malt markets.
This report focuses on supply and demand for only the technical expertise in AI, so we further reduced the data set to the projects and profiles where the main job category falls under a predetermined list
of technical AI projects. For this report, we’ve decided to distinguish between two aspects of AI:
Science
Engineering
Lastly, we also used AI for the composition of this report. For efficiently writing certain parts of the content, our team relied on tools such as ChatGPT-4 and Claude 3 Sonnet. We believe that a collaborative effort between humans and AI is the way forward, alongside a strong human involvement throughout the whole process.
Demand Quadrant
Supply Quadrant
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Market trends IN AI
The freelance spark: igniting business AI adoption
Skilled freelancers can be the spark that enables and fosters AI adoptionfor businesses. And make it last.
While companies may be navigating the AI curve cautiously, independent talents have often embraced
it more rapidly. As Arnaud Vidal, Head of Geospatial
at TotalEnergies, highlights, companies leverage freelancers for both speed and specialized skills:
“We train our own people, but when we need to accelerate and identify specific needs, we use external support.”
Emmanuel Vignon, CEO of Sicara, Data & AI by Theodo, echoes this sentiment:
“Expertise in data and AI favors freelancers due to the skill shortage.”
This access to specialized talent allows businesses
to bridge the gap between their in-house capabilities
and the full potential of AI.
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Driving efficiency across industries: the surge in AI projects focused on automation
Companies are increasingly turning to AI, with project demand for tech & data 70% between 2022 and 2024. However, as Thomas Lenormand, Tech Lead Cloud at TotalEnergies, points out :
“Most AI projects that companies deal with are actually around automation and not creation.”
Currently, most companies focus on automation
to streamline processes. This focus on efficiency is reflected in the top three requested industries: software (11%), education (10%), and high tech (9%). In the Tech & Data segment, the talent pool is expanding rapidly, with the percentage of freelancers on the platform growing from 8.9% in 2022 to 10.4% in 2024.
The focus on automation mentioned above aligns
with the rising demand for Data Scientists (39%),
Data Engineers (23%), and Backend Developers (15%)
on platforms such as Malt. This echoes with freelancer Mohamed Kadiri :
“Automation, driven by the goal of production optimization and reducing human intervention, has become the cornerstone of client requests in my field and represents 80% of my current workload.”
This shift from digitization to automation exemplifies how AI is transforming industries and workflows, often by optimizing existing processes rather than replacing human roles entirely.
“ AI goes beyond new capabilities for companies. It empowers us to finally tackle neglected tasks and improve existing ones. ”
Rodolphe Marinier
Bizdi Digital Founder Interim Manager
AI projects are on the rise
Sharp rise in AI projects enabled by increasing demand and supply
DEMAND
Increasing number of opportunities are demanding AI projects to better leverage this advanced tech.
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SUPPLY
More and more AI freelancer profiles are signing up on the platform.
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France, Spain, and Germany fastest growing markets: Highest share of AI project opportunities and number of AI freelancers
Demand (clients)
Top 3 markets by growth rate
in number of opportunities
in 2023-2024.
Germany
+67%
France
+42%
Spain
+11%
Supply (freelancers)
Top 3 markets by growth rate
in AI freelancer profiles in 2023-2024.
Spain
+32%
France
+28%
Germany
+30%
AI portraits
Portrait of an AI freelancer
Engineering is a more mature field than AI overall, while Science is a more novel field
AI Freelancers on the whole have an intermediate level of experience, whereas AI Science sees more freelancers with entry level expertise. We see a lot more expert professionals in Engineering as compared to Science (+20pp).
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AI engineers and AI scientists have similar daily rates, though daily rates for AI engineers have increased faster
Freelancer daily rates at intermediate experience level
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Portrait of an AI project
AI projects, especially Engineering, are more complex than most Tech & Data projects.
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AI projects are generally full-time engagements
% Share of full-time projects by category
Tech & Data
67%
AI Engineering
80%
AI Science
67%
They require higher expertise than Tech & Data
% Share of projects demanding skill level “Expert” by category
26%
Tech & Data
29%
AI Science
31%
AI Engineering
AI supply is split 60-40 between Science and Engineering profiles, a ratio that has remained stable over time
AI supply (2024)
Distribution of job categories among freelancers with AI expertises, broken down by specialization (Science and Engineering)
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40% of AI profiles are “multi-specialists”, i.e they list both data science and engineering job categories on their profiles.
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AI demand is split equally between Engineering and Science, a ratio that has remained stable over time
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Industries leading the AI charge
Top 10 industries demanding AI projects
Beyond coding: the rise of multidisciplinary AI experts
The rise of AI is driving a significant shift in the talent landscape within corporations. Despite cost management pressures, companies are actively building their internal
AI teams, recognizing its potential to transform businesses.
However, managing costs while competing for a limited pool of AI talent is a challenge. As Darwin X points out, companies are increasingly looking to a balance between core in-house AI competencies and scalable external support. This past year, all industries within their study
saw internal AI talent pools grow, with some sectors like Banking experiencing a surge of 44%.
This rapid growth reflects a growing demand for specialists in Data Science, Engineering, and Analytics, putting pressure on the labor market.
In the AI era, success demands a multidisciplinary approach beyond just technical skills. As Laura Sibony, author of “Fantasia, tales around AI” notes, there’s a need for “multidisciplinary profiles” that can grasp data’s deeper implications.
Mastering programming languages is insufficient; weaving connections across disciplines and critical thinking become crucial. While specialized hard skills face rapid obsolescence, soft skills like adaptability, creativity,
and critical thinking retain lasting value.
Navigating AI’s complexities requires a blend of technical expertise, interdisciplinary thinking, and a commitment to continuous learning. Embracing this multidimensional skill set unlocks AI’s true potential.
This focus on continuous learning resonates with freelancers like Mohamed Kadiri. He views AI
as a “game-changer for professions, not a job eliminator,” emphasizing its potential to “amplify performance and productivity.” His own experience reflects this ongoing learning process: “AI projects are always a little new in their own way so the best way for me to stay up-to-date is actually to keep on working on new ones.”
Client focused info
Enterprise businesses are pursuing digital transformation requiring modern stack expertise which they tend to outsource
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Use cases: how freelancers cover every dimension of an AI project
Develop Strategy
“As a CEO, I want to integrate new AI tools into my activity so as not miss the transformation brought by AI”
SMB client, one-off project
Build Solution
“Develop AI systems capable
of automatically detecting and characterizing cancer lesions from CT scanner images”
Enterprise client, 6 months
long project
Deploy & Evaluate
“Design software tools to
deploy and monitor the different
Machine/Deep Learning models”
Enterprise client, 12 months
long project
Maintain & Iterate
“We have developed an internal tool but with the large increase
in the size of the user base,
it starts to be very slow and
difficult to maintain”
SMB client, 4 months long project
What about tomorrow?
AI and Malt’s Vision for the Future by Vincent Huguet CEO & Co-Founder Malt
As far as my childhood memories go, I have always had easy access to computers. My father graduated in computer science and worked as a developer on flight simulators or on the first PCs. I have witnessed many technological disruptions since the 80s, but I would say that two, in particular, were for me “aha” moments.
The first was as a young student testing a Mac connecting with Netscape to the “World Wide Web” in 1994 in a computer shop in Paris, La Défense. The second was to test ChatGPT at its launch in 2022, which allowed most of us to understand for the first time as an end user what Artificial Intelligence was really about.
I have since made many connections and envision many similarities between these two moments. We are probably in a “hype” phase of AI, and everyone understands they must prepare for it, test it, and launch projects or companies. In the short term, many of these AI projects may not materialize, leading some to believe that AI was overhyped, much like e-commerce and the Internet after the 2000 dot-com crash. However, in the long run, the impact of AI will be profound. Those who invest in the right talent and resources will emerge winners in this new era of technological disruption.
On that topic, we at Malt are investing heavily to improve our internal operations and, moreover, our matching between offer and demand. Matching is the core of any marketplace, but what is relatively easy for products is way more complicated for talents.
AI, more specifically genAI in that case, enables us to optimize a search based on a complex search or prompt, allowing us to envision an even better service for our customers. With the immense quantity of data on freelancers and searches we have, we are also at the forefront of observing what skills and expertise clients and freelancers are positioned on. After the first hype of talking about “prompt engineers” like we had in the late 1990s, “webmasters” now see how much the AI talent environment is already becoming more complex and specialized, which is a sign of growing maturity.
We will keep monitoring and sharing these emerging trends with our community of freelancers and clients, which will enable all of them to hire, train, or find external freelance talents on the right technologies to become the winners of this new world. AI will definitely reinforce the figure of the “10x developers” or, in general, the concept of “software craftsmanship” or “artisans” of the digital world.
As always, with the birth of disruptive technology, those who will make the most of it are not the ones with the most money, servers, and technologies but, first and foremost, the ones with the right talents. After the “digital transformation,” Malt will be the go-to place in the years to come to find the great entrepreneurial talents of the “AI transformation.”
Facing the rise
of generative AI
While current AI projects heavily emphasize automation,
2024 marks a pivotal shift as companies increasingly turn their attention to the challenges and opportunities presented by AI, especially Generative AI (GenAI) and deploying GenAI assets to end customers. A recent BCG study reveals that 85% of C-suite executives plan to increase spending on AI and GenAI this year, reflecting
a blend of caution and a desire to experiment.
This translates into action, particularly in the retail
and services sectors, with companies like Walmart, Cdiscount, and Carrefour actively exploring GenAI
with internal teams and their hyperscaler partners.
These companies seek to maintain control and aim to
be early adopters, leveraging GenAI’s potential for high-value. However, it’s not a race to be first, but rather a long run to achieve tangible results and making “wonders” for users. Companies with smaller, “gadget” actions won’t cross the finish line first; only those with a strong, dedicated plan will succeed in leveraging value.
Several hurdles persist, including the need for organizations to invest in developing their Robotic Quotient (RQ) – their ability to adapt and thrive with intelligent automation – and foster more agile organizational structures. Ethical considerations, compliance, and effective employee onboarding are also crucial factors. As Rodolphe Marinier emphasizes, “it’s important to gauge ‘when’ it is appropriate to move from a Test & Learn phase to massive investment.”
This evolving landscape presents a significant opportunity for freelancers. Companies are actively seeking professionals with diverse experiences and a commitment to continuous learning – traits that freelancers often possess by design. As showcased in Malt’s Freelancing in Europe 2024 study, freelancers from the Tech & Data category spend an average of 5 hours per week training. By showcasing their market vision and diverse skill sets, freelancers can become valuable assets for companies navigating the exciting and complex world of GenAI.