The Complete Guide to Using AI in the Retail Industry in Finland in 2025

Retail in Finland in 2025 is a test of speed and sensitivity: consumers are cautious after a «vibecession», cultural moments move fast, and regulators are tightening the rules, so the retailers that win will use AI to react faster, personalise offers and tighten supply chains.

Deloitte's Retail Trends 2025 urges brands to “move at the speed of culture” - which in practice means using data-driven tools for dynamic pricing, inventory forecasting and tailored marketing - while Snowflake's Data Trends 2025 shows how unstructured data and AI-powered forecasting can cut waste and shorten delivery times.

For Finnish teams, the real advantage is people who can prompt, validate and govern AI: practical courses such as Nucamp's Nucamp AI Essentials for Work bootcamp train staff to apply AI across operations, marketing and customer service so technology actually lifts margins and customer trust.

Program	Length	Cost (early bird)	More
AI Essentials for Work	15 Weeks	$3,582	Register for Nucamp AI Essentials for Work (15-week bootcamp)

“Marketing will fulfil the first promises of artificial intelligence next year as AI is integrated as part of marketing processes.” - Ville Fredrikson, Dagmar

At the heart of Finland's retail-ready AI roadmap sits the national Artificial Intelligence 4.0 programme, a pragmatic follow‑on to Finland's 2017 AI strategy that bundles skills, funding and ethics to speed digitalisation - especially in SMEs - while driving the “twin transition” of green and digital growth; retailers can tap this ecosystem through targeted R&D support, Business Finland initiatives and local AI hubs that lower the barrier from pilot to production.

The programme's priorities - boosting digital investment, spreading AI literacy (the strategy even flags wide reskilling needs), and combining AI with IoT, high‑performance computing and other industry tech - are spelled out in government materials and independent summaries, and they translate into concrete help for store operations, supply‑chain forecasting and energy‑smart facilities.

Finland pairs this push with a clear ethical and data‑governance thread - open data, regulatory sandboxes and AuroraAI‑style collaboration - to keep adoption trustworthy.

For retailers planning next steps, the message is simple: public programmes, funding routes and cross‑sector networks are in place to fund pilots, scale proven AI use cases and link digital upgrades with sustainability goals by 2030; learn more from the Ministry's programme page and the AI 4.0 final report.

AI 4.0 Focus	Retail relevance
Strengthen digitalisation & SME uptake	Funding and hubs for store tech and inventory AI
Skills, reskilling and lifelong learning	Upskilling staff for AI‑assisted roles (≈1M Finns need retraining)
Twin transition: green + digital	Energy‑efficient, data‑driven stores and logistics

“The key assets of Finnish industry include sustainability, capacity for renewal and technological leadership. Finland has the ability to remain a leading country in technology and artificial intelligence, but this will require concrete and far‑reaching measures.” - Mika Lintilä, Minister of Economic Affairs

The legal picture for Finnish retailers in 2025 is dominated by the EU Artificial Intelligence Act's staged rollout and Finland's move to align national rules with it: Finland is already working on a national legal framework to host an AI regulatory sandbox in line with Article 57, giving local firms a supervised place to test systems before market release (EU AI regulatory sandbox approaches overview).

At EU level, foundational obligations – including bans on unacceptable AI practices and transparency duties for generative systems – began applying in 2025, the AI Office and AI Board are now operational, and specific obligations for general‑purpose AI (GPAI) landed in August 2025, requiring documentation, training‑data summaries and stronger oversight for providers (AI Act obligations (August 2025): documentation and oversight requirements).

Practical risks for retailers include GDPR overlap (the AI Act supplements, not replaces, data‑protection duties) and a new liability outlook where software and continuously learning systems can be treated as

“products”

- so contracts, model inventories and clear supplier cooperation clauses matter.

Enforcement is real: penalties can reach €35 million or 7% of global turnover, a level that will get CFOs' attention; Icelandic‑style caution is no longer enough when selling into the EU (EU AI Act Article 99 penalty rules).

In short: use sandboxes and EDIHs to validate models, tighten governance and document everything to turn compliance from a cost into a growth enabler.

Violation type	Maximum fine
Prohibited AI practices	Up to €35,000,000 or 7% of global turnover
Other operator obligations (providers, deployers, importers)	Up to €15,000,000 or 3% of global turnover
Supplying incorrect/misleading info	Up to €7,500,000 or 1% of global turnover

Generative AI can turbocharge merchandising, chatbots and content for Finnish retailers, but it also forces hard choices about data governance and intellectual property: GDPR and Finland's Data Protection Act apply to training and operational data, so retailers must run DPIAs, limit what prompts or customer records are sent to third‑party models and require clear contractual guarantees about whether inputs will be used to train LLMs (Finland AI practice guide for legal basics).

Technical mitigations - synthetic data, differential privacy and federated learning - are recommended to reduce exposure, and EY practical playbook on mitigating AI privacy risks outlines how to combine privacy‑by‑design with human oversight and bias testing.

On IP, Finnish law still presumes human originality (so pure AI outputs rarely attract traditional copyright) while the Trade Secrets Act can protect model recipes and proprietary datasets; in short, treat models as both a legal and commercial asset, lock down access, and remember one careless prompt or a public sharing link can leak strategic information as easily as an unlocked back door (data‑protection analysis of generative AI for concrete risk examples).

In Finland in 2025 AI is already practical, not hypothetical: the biggest wins are in demand forecasting and inventory orchestration - AI models that pull POS, promotions, weather and social buzz into store‑level forecasts so shelves match real customer signals and waste falls; RELEX's work with Finnish retailers shows this in action across replenishment, clearance and main‑delivery optimisation, and Atria uses near‑real‑time forecasts to delay production until closer to campaigns so fresh meat reaches shelves with less spoilage (Atria case study).

Generative tools and LLMs are powering personalised marketing, automated product content and smarter chatbots, while local predictive‑analytics vendors (RELEX, Analyse², Lumoa and others) are turning those forecasts into prescriptive replenishment and dynamic pricing engines (top predictive analytics companies in Finland).

Industry reporting shows forecast accuracy uplifts of 10–20 percentage points when external signals and unstructured data are used, translating into fewer stockouts, lower markdowns and measurable margin gains for chains that integrate forecasting, promotions and store operations end‑to‑end (demand‑forecasting analysis), a shift that turns inventory from a cost center into a competitive lever.

Use case	Finland example / outcome
Demand forecasting & replenishment	Atria: +3 pp promotion availability via RELEX integration
Clearance & markdown optimisation	S Group: improved margins and inventory turn with RELEX solutions

“With RELEX, the transparency we have into our retailers' forecasts has genuinely put us on the pulse of the end-customer demand. Seeing the changes in short-term demand – almost in real time – gives us more time to adjust and time our production accordingly.” - Mikko Soini, Planning Manager at Atria Finland

A practical Finnish technology stack for AI in retail is increasingly modular: think cloud data platforms and real‑time analytics at the centre, lightweight APIs to stitch together POS, ERP and loyalty systems, and edge components like electronic shelf labels and in‑store assistants that close the loop between online signals and store action; this composable approach is exactly what modern retailers need to scale pilots to production without a rip‑and‑replace upheaval (see the case for a composable tech stack in the Braze article on composable tech stacks for AI: Braze article on the composable tech stack for AI).

Local success stories show how those pieces fit in practice - Kesko's AI transformation with TCS highlights how global systems integrators plug AI solutions into Finnish retail operations (TCS press release: Kesko AI-powered retail transformation) - while S‑Group's rollout of Pricer electronic shelf labels across 100+ stores proves the payoff of integrating cloud price management with store‑level hardware, enabling price and promotion updates across a regional chain in the time it takes to brew a cup of coffee.

To make this real, teams should prioritise a central data layer, model serving and monitoring, clear API contracts with vendors, and edge orchestration so forecasts, pricing and fulfilment move together rather than in isolated silos; the result is a retail stack that turns inventory and checkout data into fast, compliant, and measurable business decisions.

“This next phase of our electronic shelf label rollout marks an important milestone in our digital transformation strategy, and we're excited to continue our successful partnership with Pricer to enhance the in-store experience.” - Sampo Päällysaho, SVP Groceries at S Group

When Finnish retailers buy AI, procurement is as much about contracts and compliance as it is about capability: national procurement law explicitly encourages dividing contracts into lots to let SMEs compete for pilots or single‑store rollouts, and offers award routes from open and restricted procedures to innovation partnerships for truly novel systems, so drafting tends and SOWs with clear risk categories and scalable milestones is essential (market consultations before tendering are permitted to shape realistic specs).

Layer on EU rules and recent AI regulation and the checklist lengthens - include GDPR‑aligned data governance, model documentation, DPIAs, human‑in‑the‑loop and monitoring clauses, and, for high‑risk systems, evidence of registration and lifecycle testing so a contract can withstand post‑award audits; model procurement clauses and GDPR guidance are practical starting points for translating these requirements into measurable KPIs and contractual remedies.

Practical procurement teams should also require transparency on training data, IP and reuse rights, incident reporting, cybersecurity measures and supplier obligations to cooperate on bias testing and updates - and remember remedies exist (complaints to the Market Court, suspension and damages) if procedure rules are breached.

Finally, use the public ecosystem: Finland's AI policy hubs, sandboxes and innovation vouchers can derisk pilots and help structure phased contracts that move from R&D to production without locking buyers into opaque, ungovernable systems - see ICLG's Finland procurement overview and the EIPA guide to AI procurement for model clauses and implementation tips.

Threshold / Contract type	National threshold	EU threshold (example)
Supply & Service contracts	€60,000	€134,000 (central authorities)
Construction contracts	€150,000	€5,186,000
Concession contracts	€500,000	-

Workforce, ethics and bias sit at the intersection of opportunity and risk for Finnish retailers: the Nordics have seen AI usage surge -

“from 12% to 65% in one year”

according to EY - but turning that momentum into safe, fair value requires deliberate reskilling, change management and legal hygiene rather than blind tool rollouts (EY report on AI adoption and workforce impact in the Nordics).

Surveys show many organisations use AI frequently but few are truly ready to scale (Amperity finds 45% use AI weekly or more while only 11% say they can scale it), which raises the practical need for role redesign, prompt training and measurable adoption plans (Amperity 2025 State of AI in Retail report).

Legal frameworks in Finland - GDPR, the Non‑Discrimination Act and emerging AI supervision - mean bias testing, DPIAs, human‑in‑the‑loop checkpoints and explainability are not optional; Chambers' Finland AI guide flags liability and discrimination as top concerns and recommends governance, documentation and staged rollouts to reduce harm (Chambers Artificial Intelligence 2025 - Finland trends and developments guide).

A vivid test: when a store assistant trusts a model's replenishment suggestion and acts on it before the next coffee break, that's a practical sign adoption, governance and ethics are working together - turning potential legal exposure and employee anxiety into faster service, fewer stockouts and real competitive advantage.

Metric	Value (source)
Nordic employee AI usage (year‑on‑year)	12% → 65% (EY, May 2025)
Retailers using AI weekly or more	45% (Amperity, 2025)
Retailers ready to scale AI across the business	11% (Amperity, 2025)

Look ahead to 2030 and Finnish retail will feel less like a pilot project and more like a finely tuned, data‑driven economy: AI‑powered services are expanding fast (Finland's AI in media & entertainment market is projected to hit about US$2.11 billion by 2030), while e‑commerce itself is set to grow from roughly US$7.71B in 2025 to US$10.53B by 2030 - growth that underwrites smarter personalisation, faster fulfilment and richer retail media monetisation (Finland AI in Media and Entertainment market outlook, Finland e-commerce market forecast).

Practically, expect micro‑fulfilment centres, ship‑from‑store and split‑shipping logic to turn local shops into nimble distribution hubs and shave days off delivery windows; retailers that pair those flows with well‑governed generative tools and workforce reskilling can turn inventory into a margin engine rather than a cost burden (see actionable orchestration playbooks for inventory and delivery).

At a continental level the AI in retail market is also accelerating, signalling broad vendor maturity and interoperable platforms across Europe that Finnish chains can plug into - so the competitive imperative is clear: pilot fast, standardise the data layer, and scale the human+AI workflows that produce measurable availability and cost wins.

Metric	Value / Forecast	CAGR (2025–2030)
Finland AI in Media & Entertainment (2030)	US$2,111.0 million	29.6%
Finland E‑commerce (2025 → 2030)	US$7.71B → US$10.53B	6.42%
Europe AI in Retail (2030)	US$8,454.8 million	19.8%

Finish strong: for Finnish retailers the clearest path is pragmatic and staged - pick one high‑impact pilot

identify suitable pilot

that links demand forecasting or ship‑from‑store logic to a measurable KPI, run it in a supervised sandbox or pilot store, document DPIAs and supplier commitments, and use the results to harden contracts and scaling plans; Finland's legal playbook and ethical guidance (see the Chambers Finland AI practice guide) underline why governance, transparency and staged rollouts aren't optional but the route to commercial trust.

Pair that programme with focused reskilling so store teams and planners can validate outputs (a single compliant pilot that reduces stockouts before the next coffee break proves the

human+AI case

), then codify procurement clauses for training‑data use, bias testing and incident reporting so vendors are accountable as you scale.

For many retailers the fastest next step is training staff who will run, prompt and govern these systems - Nucamp AI Essentials for Work bootcamp teaches practical prompting, AI tools for operations and governance skills to turn pilots into repeatable business outcomes.

Program	Length	Cost (early bird)	More
AI Essentials for Work	15 Weeks	$3,582	Register for Nucamp AI Essentials for Work (15-week bootcamp)