Artificial intelligence is changing how organisations attract, assess, and hire talent. That much is obvious. The question worth asking is a more specific one: how is the Portuguese recruitment market actually adopting it, and where is the gap between enthusiasm and practice?
To find out, Damia ran the first survey in Portugal dedicated exclusively to AI adoption in recruitment. We partnered with Mesh-AI, gathered responses from 128 recruitment professionals across the country, and followed the survey with a round table featuring practitioners from Snyk, Datadog, and the wider Portuguese talent community.
This article breaks down the findings. No predictions, no hype. Just what the data says.
Who responded
Understanding the sample matters, because the answers read differently depending on who gave them.
Of the 128 respondents, 73% work as recruiters or sourcers and 16% are managers. The remaining 11% do both. In terms of employment context, 63% work in-house, 29% are in consultancy or agency, 6% in RPO, and 2% are freelancers. This is a practitioner-heavy sample, people who interact with AI tools in their daily workflow rather than just setting strategy around them.
Usage is high, and it’s daily
The headline number: 45% of respondents use AI tools every single day. Another 29% use them several times a week. That means roughly three quarters of Portuguese recruitment professionals are using AI at least multiple times per week.
Only 5% of respondents said they are not using AI at all. That number is small enough to treat AI adoption in Portuguese recruitment as mainstream, not experimental.
The frequency distribution drops off sharply after the top two categories. Occasional use accounts for 16%, while monthly usage (whether once or a few times) sits at just 5% combined. The pattern is clear: once people start using AI in recruitment, they tend to use it often.
ChatGPT dominates, but the landscape is fragmenting
When asked which tools they rely on, ChatGPT leads with 32% of usage, followed by Gemini at 13% and Copilot at 9%. LinkedIn’s built-in AI features account for 4%, Metaview for 3%, and JuiceBox for 2.5%. Claude, Perplexity, MagicalAI, and various internal tools make up the remaining share.
Two things stand out. First, ChatGPT’s dominance is significant but not overwhelming. It holds roughly a third of the market, which means two thirds of AI usage in Portuguese recruitment is spread across a growing ecosystem of alternatives. Second, recruitment-specific tools like Metaview and JuiceBox have already carved out small but visible shares, suggesting that general-purpose models alone aren’t meeting every need.
The way people discover these tools is also telling. Self-research is the top channel at 35%, followed by company adoption at 21% and social media at 14%. Colleague recommendations, training workshops, and events round out the picture. The takeaway: most recruiters are finding and choosing their own tools rather than waiting for their organisations to mandate them. This is bottom-up adoption, not top-down rollout.
Where AI is actually being applied
The survey asked respondents to identify which categories of AI tools they use most. Content generation leads at 37%, followed by translation and linguistic adaptation at 25%, chatbots at 18%, profile matching platforms at 10.5%, and predictive analysis at 8%.
More revealing is where AI shows up across the recruitment process itself. Job description generation tops the list at 25%, which makes sense: it’s a high-frequency, low-risk task where AI output is easy to review and edit. Candidate communications come next at 17%, covering outreach messages, feedback emails, and follow-ups. Candidate sourcing and recruitment reporting each sit at 13%. CV screening accounts for 10%.
The bottom of the list is where it gets interesting. Interview scheduling sits at just 6.5%, assessment of technical or behavioural skills at 5%, and video interviews with automatic analysis at 3.5%. Note taking barely registers at 0.5%.
The pattern is a familiar one in technology adoption. AI is being used most where the task is text-heavy and the stakes of a mistake are low. Writing a job description with AI help is low risk, because a human reviews it before it goes live. Automating candidate assessment is high risk, because a bad model can screen out the right person silently. Portuguese recruitment teams are adopting AI pragmatically, starting with the safe bets and moving cautiously toward higher-stakes applications.
What people say it’s doing for them
When asked about the perceived benefits of AI in their work, respondents gave a clear top two: increased productivity (31%) and repetitive tasks automation (31%). Together, these two benefits account for nearly two thirds of all responses. The message from the market is unambiguous: AI’s primary value in recruitment today is time savings, not strategic transformation.
After productivity and automation, the numbers drop significantly. Support in data-driven decision making sits at 11.5%, increased hiring quality at 9%, reduction in candidate screening time at 8%, better candidate experience at 6.5%, and reduction of selection process setbacks at 4%.
This is worth sitting with for a moment. Only 9% of respondents associate AI with improved hiring quality, and only 6.5% connect it to a better candidate experience. The industry narrative around AI often centres on “better hires” and “more human hiring.” The Portuguese market, at least at this stage, sees AI as a productivity lever first and a quality lever second. That gap between the promise and the perceived reality deserves honest attention.
The challenges slowing adoption
The top concern among respondents is the risk of technology dependency, cited by 20.5%. This is a mature concern. It suggests that even as professionals adopt AI enthusiastically, they worry about what happens when the tool becomes a crutch rather than an aid.
Lack of precision in results comes second at 16%, closely followed by lack of personalisation in candidate interactions at 15.5%. Both speak to the same underlying problem: AI tools in recruitment are not yet reliable enough for the moments that matter most. A generic outreach message or an imprecise candidate match can do more damage than doing the task manually.
Integration problems with existing tools and ethical concerns each sit at 15%, and cost concerns at 14%. Only 5% cite the learning curve as a barrier, which reinforces the earlier point: adoption isn’t limited by willingness or ability. It’s limited by the tools themselves.
What recruitment teams wish AI could do next
When asked which processes they’d most like AI to handle, respondents grouped around four areas. First, reporting and metrics: pipeline monitoring, general reports, and summaries. Second, operational candidate management: stage tracking, rejections, CV screening, and workflow automation. Third, content-related automation: emails, job description generation, and other time-consuming communication tasks.
And fourth, a category that deserves its own mention: “nothing.” Some respondents remain openly sceptical about extending AI further into their workflow. This is a small but honest cohort, and their caution is a useful counterweight to the adoption enthusiasm elsewhere in the data.
The wishlist reveals where the market sees untapped potential. The demand for AI in reporting and pipeline management suggests that Portuguese recruitment teams are drowning in operational data they don’t have time to process. If an AI tool could reliably generate a weekly pipeline summary or flag stalled processes, it would address a real pain point that current general-purpose models don’t solve out of the box.
What this means for the market
The Portuguese recruitment community is not waiting to be told to use AI. It’s already using it, daily, across most stages of the hiring process, and mostly through tools that individual professionals have discovered and adopted on their own.
But adoption is uneven. AI is concentrated in the early, low-risk stages of recruitment (writing job descriptions, drafting outreach) and has barely touched the higher-stakes parts of the process (assessment, scheduling, candidate experience). The perceived benefits are heavily weighted toward productivity rather than quality. And the challenges that slow adoption are not about willingness or learning curves, they’re about precision, personalisation, and integration.
For hiring teams, the implication is clear: AI is already part of the toolkit, whether your organisation has a formal strategy for it or not. The question is no longer whether to adopt, but how to adopt intentionally, choosing the right tools for the right tasks and knowing where human judgement still outperforms the model.
This survey is the first snapshot. Damia will continue to track how the Portuguese recruitment market evolves with AI, because the only way to advise clients and candidates well is to understand the market as it actually is, not as the headlines suggest it should be.
This article is based on findings from the first AI recruitment survey conducted in Portugal, a Damia initiative in partnership with Mesh-AI. The survey gathered responses from 128 recruitment professionals and was presented at the Next-Gen Hiring: The AI Recruiter’s Toolbox event, which included a round table with André Marques (Damia), Márcia Santos, Raphael Neves (Snyk, Candl.io), Filipe Piedade (Datadog), and Marcelo Marques.
