Top 5 Jobs in Real Estate That Are Most at Risk from AI in Switzerland - And How to Adapt

Swiss real estate professionals can no longer treat AI as a distant buzzword - it's already shifting both where capital flows and how deals get done: UBS highlights that AI is driving demand for data centres and warned the “annual datasphere” could double by 2027, tightening supply and pushing rents in core markets, while the EY European AI Barometer shows Swiss managers reporting strong, practical gains (81% positive experience) and three-quarters expecting AI to take over some tasks; at the same time, industry reporting notes many Swiss firms are still in early stages (single-digit to mid‑teens adoption), so the competitive edge will go to teams that adopt thoughtfully and upskill fast.

Practical steps - automating routine valuations, deploying chat assistants for tenant queries, and training staff - are low-risk wins; for structured upskilling, programs such as Nucamp's AI Essentials for Work (15 weeks) offer a workplace‑focused route to close the gap and keep Swiss firms in the lead.

It is essential for companies to think about meaningful AI applications.

Methodology - How we selected these top 5 roles: selection began with the task‑based exposure framework used by the ILO (updated GenAI/ISCO method) and the Swiss‑specific exposure/complementarity lens from Avenir Suisse, then narrowed to real‑estate job families that blend high task exposure with low complementarity - the mix that most clearly signals displacement risk rather than pure augmentation.

Practically that meant: map Swiss real‑estate tasks onto the ILO/ISCO task scores (the GenAI gradients and task‑level scoring process that uses human surveys, expert validation and AI‑assisted prediction), flag occupations that sit in higher exposure gradients or whose routine tasks (data entry, contract processing, scripted tenant responses, standardized credit checks, simple comparable valuations) score high, and cross‑check with Avenir Suisse's Swiss analysis showing office/clerical roles and call‑centre work as particularly vulnerable.

The result is a shortlist grounded in international task‑scoring rigour but filtered for the Swiss market realities - so the five roles picked are those where many repeated, well‑structured tasks already score high on ILO's exposure index and where Avenir Suisse's complementarity analysis suggests limited upside from simple AI support.

Imagine a routine tenant inquiry that today ties up a human agent for ten minutes but, by the scoring method above, could be reliably handled end‑to‑end by GenAI - that

low‑value, high‑volume

signature is exactly what guided the picks.

For methodology details see the Avenir Suisse Swiss exposure approach and the ILO task‑based GenAI index.

Swiss property-marketing creatives - photographers, illustrators, listing copywriters and graphic designers - are already feeling a tangible squeeze as generative models eat into routine image- and text-production tasks: a large freelancing-platform study found a 21% fall in posts for automation-prone writing and coding gigs and a 17% drop in image-creation demand after ChatGPT and image AIs emerged, signaling real downward pressure on volume work (SSRN CESifo study on AI replacing freelance writing and coding jobs).

On the ground in Switzerland, reporting shows experienced illustrators losing commissions and fees - one freelance illustrator's rate reportedly fell from CHF1,000 for a single piece to CHF400 for two before the client shifted to AI-generated art, even sending a standardised dismissal letter the illustrator believes was produced by ChatGPT (SWI swissinfo.ch: How AI is affecting Switzerland's creative workforce).

That combination of fewer commodity requests and easier image synthesis means the competitive edge will go to creatives who can pair human judgement, local market nuance and brand storytelling with AI tools rather than compete on price alone; for a deeper look at how AI is reshaping photographic authorship and authenticity, see recent analysis on photography and AI (AM Journal analysis: The Impact of AI on Photography and Photographic Authorship).

“Generative AI has caused one of the biggest technology shocks in recent times. It is inevitable that it will have repercussions on people and businesses.”

Transaction coordinators and back‑office administrators in Switzerland - leasing administrators, contract processors and listing managers - are among the clearest early targets for automation because their daily work is dominated by repeatable, document‑heavy tasks: UBS notes the first wave of AI adoption will focus on routine back‑office roles, while industry tool guides show purpose‑built apps for lease abstraction, rent‑roll processing and chat‑based tenant handling.

Firms that pilot these automations can capture real efficiency: automated contract processing is already driving typical >20% admin reductions in Swiss firms, and CRE platforms now offer lease‑to‑data pipelines, rent‑roll rollups and lead‑calling agents that triage enquiries before a human ever touches a file.

The practical takeaway for Swiss teams is concrete - start with pilots that replace the most repetitive checks (lease abstraction, reconciliation, standardised tenant replies), pair tools with governance and local data controls, and keep an eye on evolving Swiss rules and sector guidance as you scale.

Customer service and call‑centre agents in Swiss property management are squarely in the crosshairs because so much of their work - initial lettings enquiries, routine tenant support, maintenance requests and appointment booking - is high‑volume and highly standardisable: EY already flags tenant chatbots as a growing part of property operations, able to handle maintenance tickets, account queries and rent collection, while industry guides show chatbots qualifying leads, scheduling viewings and freeing staff to focus on complex cases (EY report on generative AI in real estate).

Real deployments deliver clear gains: chatbots run 24/7, instantly qualify prospects and push qualified leads into CRMs, cutting human follow‑up and speeding conversions (Biz4Group guide to AI chatbots in real estate and Appgain analysis of AI chatbots in real estate (2025)).

In Switzerland that means multilingual, compliant bots matter - a WhatsApp conversational search and scheduling assistant that understands Swiss dialects and books showings across cantons is a practical, low‑risk pilot that captures after‑hours enquiries and slashes response time; the real challenge for Swiss teams is governance and handoffs so human agents handle empathy, negotiations and exceptions while bots soak up the repetitive traffic.

Mortgage brokers and loan‑processing clerks in Switzerland face one of the clearest practical risks from GenAI: task automation that turns manual document sifting and rule‑based credit checks into near‑real‑time pipelines, so that what used to be a multi‑day paper chase (or a half‑day of reconciliation) becomes loan prequalification in minutes and underwriting prep for human review.

Global estimates warn that roughly 30% of work hours could be automated by 2030, underscoring scale rather than sudden disappearance, and the mortgage workflow is a prime candidate because it is document‑heavy, repeatable and measurable (McKinsey estimate on automation of work hours (Fox Business)).

Vertical solutions are already pitching loan prequalification, intelligent underwriting support and automated QC - capabilities that can shrink turnaround times and cut tedious checks while leaving complex exceptions to licensed humans (AI tipping point for mortgage lending (TRUE.ai)).

Swiss teams should pilot these tools with strict explainability, canton‑level compliance and multilingual handling, and pair deployments with retraining so skilled brokers move up‑market rather than compete on repetitive tasks; automated contract processing pilots already report material admin reductions in Swiss firms (Automated contract processing pilots in Switzerland).

"Our research does not lead us to estimate job losses, although we cannot definitively rule out that conclusion, at least in the short term."

Junior valuers and routine appraisers in Switzerland should watch AVMs closely: automated valuation models now produce fast, consistent desktop values for standardised residential stock and bulk portfolio checks - what once took a junior valuer a day can be generated in seconds - so routine comparable‑based work and retrospective analyses are the most exposed.

AVMs shine on speed, scale and objectivity, supporting mortgage pre‑qualification, portfolio monitoring and high‑volume desk valuations (see PriceHubble automated valuation model guide and Valligent AVM speed and efficiency overview), yet the research is clear that credibility hinges on explainability and governance; RICS guidance and ValuStrat AVM standards‑first approach argue for a hybrid model where AVMs cross‑validate and speed up workflows while human valuers retain on‑site inspections, judgement on complex or bespoke assets, and oversight of confidence scores.

For Swiss firms the practical move is not an either/or: pilot AVMs for low‑risk, repeatable tasks, lock in audit trails and reserve human expertise for exceptions, high‑value assets and regulatory reporting (see ValuStrat AVM standards‑first approach).

“Automation should never compromise professional rigour. As valuers, we have a responsibility to uphold trust, consistency, and compliance. At ValuStrat, our approach to AVMs is rooted in international best practice - not speed for speed's sake, but governance‑led innovation that enhances internal quality, never replacing professional judgement.”

Conclusion - practical checklist and next steps for Swiss real‑estate professionals: start by mapping your firm's highest‑volume, repeatable tasks (tenant queries, lease abstraction, routine valuations) and run small, measurable pilots - think a multilingual WhatsApp scheduling assistant for showings across cantons, an AVM for desk valuations, or automated contract processing that can cut admin >20% - then scale the pilots that deliver clear ROI; pair every pilot with a strict data‑strategy and model‑validation plan (train on Swiss, canton‑level data, log audit trails and explainability) and a governance owner to manage privacy and compliance as recommended by Deloitte guidance and JLL insights; treat AI as copilot not replacement: redesign roles so humans handle empathy, negotiation and exceptions while routine work is automated, and track nonfinancial KPIs (response times, tenant satisfaction) as well as cost savings; seek PropTech partners who understand real estate workflows, prioritise use cases with fast payback, and avoid one‑size‑fits‑all solutions; and finally, invest in fast upskilling - practical courses like Nucamp AI Essentials for Work (15 weeks) syllabus give prompt‑writing, tool workflows and job‑based AI skills to help teams move from fear to leadership in months rather than years (see JLL on piloting and strategic adoption and Deloitte on data governance and model validation for more detail).

“Location, location, location”