How AI Is Helping Retail Companies in Finland Cut Costs and Improve Efficiency

For Finnish retailers facing tight margins and rising energy bills, AI is rapidly moving from buzzword to bottom-line tool: AI-driven accounting can lift accounts-payable automation to 70–90% and deliver 100% line-item visibility so hidden subscriptions or electricity waste stop quietly eroding margins - read more in the Semine AI-powered accounting case study Semine AI-powered accounting case study.

At the same time, strategic cost programs should balance short-term cuts with long-term agility; EY highlights how digital supply chains, hyper-automation and generative AI help retailers cut costs without sacrificing future growth in their EY report on digital supply chains and generative AI for retailers EY report on digital supply chains and generative AI for retailers.

Practical retail use cases in Finland also include smarter staff scheduling and workforce optimization tied to footfall and promotion forecasts - see retail prompts and use cases on Nucamp's AI Essentials for Work syllabus Nucamp AI Essentials for Work bootcamp syllabus: retail prompts and use cases.

For teams ready to act, building in-house skills matters: Register for Nucamp AI Essentials for Work (15-week bootcamp) to learn the hands-on prompts and workflows staff need to turn these AI opportunities into real savings.

Finnish retailers are turning to AI to shrink waste, cut stockouts and make sure the right products land in the right store at the right time: solutions like the RELEX AI-powered supply chain platform blend machine learning for demand forecasting, probabilistic safety-stock planning and even phantom-inventory detection to smooth flows and boost visibility across networks (RELEX AI-powered supply chain platform).

Local implementations show the point: STARK Suomi chose RELEX to unify forecasting and replenishment across 27 stores, 4 distribution centres and a central warehouse, a reminder that real-world scale matters for Finnish supply chains (STARK Suomi integrated forecasting and replenishment).

Industry reporting also stresses that AI excels when it ingests external signals - social, weather and market data - and that demand sensing and generative tools can raise forecast accuracy by double digits, unlocking lower inventory carrying costs and fewer markdowns (how AI transforms demand forecasting).

The practical takeaway: combine specialised forecasting tech with cross-team processes so savings stick and service levels improve.

“We're excited to collaborate with RELEX and lean on their expertise and advice as we improve and optimize our supply chain forecasting and replenishment processes.” - Kari Wahlman, Logistics Director, STARK Suomi

AI-driven pricing and promotions give Finnish retailers a practical lever to protect margins: start with the fundamentals - price elasticity - to set discounts, bundles and dynamic rules rather than guessing what customers will tolerate (Simon‑Kucher guide to price elasticity), then layer in data‑fusion and causal methods to turn noisy sales histories into reliable price signals.

Academic work from Finland shows this path: by combining purchase history, conjoint studies and population stats from Statistics Finland, researchers built a Bayesian, causality‑aware model that simulated a market of about 3.96 million people and identified a clear profit‑maximising price in their scenario (an illustrative €15), while also demonstrating that even small moves (€0.50 steps) change outcomes - so granular testing matters (Finnish Bayesian price-optimization study (Valkonen et al.)).

To scale across thousands of SKUs and stores, AI-based elasticity modeling and automated optimization help translate those causal insights into segmented, automated promotions and dynamic price rules that protect margin without triggering a race to the bottom (Revionics modeling price elasticity for optimized pricing).

Store-level AI in Finland is shifting from back‑office theory to front‑line gains: workload forecasting, shift optimisation and phantom‑inventory detection from platforms like RELEX operations AI platform help match staffing to real footfall and promotions so overtime falls and service levels rise, while retailer pilots such as S Group show the scale of practical benefits; complementing those tools, smart in‑store tech - think image‑powered smart carts that tally items and surface coupons in real time - reduces cashier friction and frees staff for higher‑value tasks (and those new tasks are exactly what training programs aim to support).

To capture this value, Finnish teams should pair specialised scheduling models with upskilling: IKEA's company‑wide AI education push and assistant experiments underline how literacy and tooling go together (IKEA AI assistant and training initiatives).

Yet caution is warranted - research shows many large Finnish firms still under‑serve or underestimate digital assistants - so start with focused pilots that link footfall, promotions and roster rules and measure overtime, queue times and customer satisfaction.

Practical prompts and templates for those pilots are available in Nucamp's labour‑planning resources on workforce optimisation informed by footfall and promotion forecasts (Nucamp AI labour-planning resources for workforce optimization).

“RELEX machine learning-based forecasting is critical to our ability to accurately forecast our most challenging categories.” - Tapani Potka, SVP, Delivery Chain Management, Atria

AI-powered search and recommendation engines are a practical lever for Finnish retailers aiming to lift conversion and make omnichannel feel effortless: tools that stitch search, personalized product pods and cart-level suggestions turn browsing into relevant discovery, with Klevu reporting a 37% increase in revenue per web session and even an omnichannel retailer, Eurokangas, doubling click‑through rates online in two weeks - see Klevu's work on product recommendations Klevu AI product recommendation solutions for ecommerce.

Local examples show the tech scales: a Helsinki case in MindTitan's guide improved email click‑through by ~30%, illustrating how hybrid recommenders and content-aware models solve cold‑start problems and boost AOV across web, mobile and email (MindTitan AI product recommendation engine case study).

The “so what?” is simple and vivid: a well-tuned recommender acts like a patient personal shopper that surfaces the one addon a customer actually wants, reducing decision fatigue while driving repeat business - start with search + recommendations, A/B test pods sitewide, and measure CTR, AOV and repeat purchase uplift to prove value fast.

“We've found that using Klevu AI increases AOV, on site customer experience, CLV, and ROAS.” - Tim Ryan, Director of Digital at Seasalt Cornwall

Generative AI is moving from novelty to toolbox for Finnish retailers: by automating product descriptions at scale, generating personalized marketing content, powering conversational grocery assistants and even helping design virtual try‑ons, it can cut marketing and catalogue costs while freeing teams to focus on strategy.

Publicis Sapient's review of the top generative AI retail use cases stresses the hard truth - ROI depends on a clean customer data foundation and small, scalable micro‑experiments - so pilots that start with automated product copy or recipe-to-shopping‑list assistants make sense in Finland's price‑sensitive grocery and apparel markets (Publicis Sapient generative AI retail use cases).

Practical vendor and platform work shows the payoff: a TietoEVRY project sped up the creation of thousands of product information descriptions, and Databricks highlights how unified data and RAG‑style GenAI chatbots unlock personalization and faster decisions - exactly the plumbing Finnish chains need to turn content automation into measurable savings (TietoEVRY generative AI product information case study, Databricks generative AI personalization and forecasting).

The memorable takeaway: with tidy data, a single overnight run of a GenAI content pipeline can replace weeks of manual copywriting and launch more targeted offers the next morning.

“If retailers aren't doing micro-experiments with generative AI, they will be left behind.” - Rakesh Ravuri, CTO at Publicis Sapient

Cutting costs in Finnish retail increasingly comes down to turning scattered data into repeatable decisions: the Bank of Finland highlights how AI and massive data unlock new signals but also make outcomes highly sensitive to data quality, so cleaning the inputs is non‑negotiable - see the Bank of Finland analysis on AI and massive data Bank of Finland analysis on AI and massive data.

Practical steps start small and structural: Vincit's data‑quality playbook reminds teams to treat accuracy, completeness and timeliness as business processes, not IT chores, because poor source data produces poor forecasts and wasted automation efforts Vincit data-quality playbook: foundation of AI success.

On the execution side, procurement and spend analytics platforms show how automation pays: a 360° procurement lens can surface rapid wins (Sievo reports ~$20M incremental savings per $1B analyzed, 63× average ROI and high classification accuracy), turning previously invisible tail spend into tangible cash - in short, combine governance, targeted automation and off‑the‑shelf analytics to harvest the low‑hanging savings and fund broader AI pilots Sievo procurement analytics: procurement savings and ROI.

“I can't believe how inefficient we would be if we had not implemented Sievo as a procurement analytics solution and, hereby, as a single point of truth a few years back. I get around 20 questions from our leadership about spend figures, now it takes me like 15 seconds to find the information.” - Stephan Schulte, Head of Procurement Steering & Analytics

Finland's retail AI momentum is backed by a visible national playbook: Business Finland is actively funding generative AI pilots to turn productivity promises into pilots and products, and its Generative AI campaign offers networking, peer learning and targeted funding to help firms - including retailers and vendors - experiment with PoCs (Business Finland Generative AI campaign details).

The recent GenAI Proof‑of‑Concept call attracted north of 200 R&D applications and has already launched roughly 130 projects, with over half coming from companies new to Business Finland, signaling lower barriers for first‑time retail innovators (Business Finland GenAI Proof‑of‑Concept funding call).

This public push builds on earlier, large programmes - Finland's AI Business initiative funded hundreds of projects and hundreds of millions in support - while Finland's deep‑tech stack (LUMI, Silo AI and strong university links) creates a practical ecosystem where a shop‑floor pilot can scale to national impact; the most memorable metric is McKinsey's estimate that generative AI can raise productivity by up to 40%, turning one successful overnight PoC into measurable savings the next quarter.

For retailers, the path is clear: leverage grants, partner with research labs, and use staged PoCs to derisk adoption.

Talent shortages and scaling friction are the practical choke points for Finnish retailers that want to turn AI pilots into recurring savings: Finland already ranks third in the EU for AI integration with more than 15% of companies using AI, and studies show one in five Finns work in occupations where roughly half their tasks are exposed to AI, so the workforce impact is real and immediate (see the Nordea Economic Outlook: Can AI Boost Productivity in Finland) - start by treating skills and data as procurement priorities, not afterthoughts.

Practical moves include subsidised upskilling and hands‑on micro‑experiments to raise baseline literacy (a common Nordic prescription), tapping national programmes and co‑funding to derisk early projects, and partnering with universities or shared expert pools so SMEs get “doers” as well as ideas.

Technology Industries of Finland's €10M push (plus thesis grants and a planned national AI network) and Business Finland's Landscape report show the routes retailers should use: apply for co‑funding, leverage VAT R&D relief, recruit thesis projects and shared experts, and measure pilots against clear KPIs (productivity, repeat purchases, and cost per transaction) before scaling.

The clearest rule: combine targeted external support with internal upskilling and clean data to turn local pilots into nation‑scale wins via grants, networks and pragmatic procurement choices (Technology Industries of Finland AI investment overview and €10M initiative, Business Finland: Finnish AI Landscape 2025 report).

“AI is now the fastest-evolving general-purpose technology that can be harnessed in all businesses and sectors. Fast adopters will enhance their competitiveness.” - Matti Mannonen, Executive Director, Innovation and Economic Policy, Technology Industries of Finland

Start with a focused, high‑impact pilot: pick one clear problem (examples that worked in Finland include AI‑optimized main replenishment days or assortment clustering), collect and straighten the data, and set simple success metrics like smoother inbound goods flow, stable or improved on‑shelf availability, fewer capacity issues and more predictable shifts.

Build a short roadmap: (1) define the business case and KPIs, (2) prepare a “digital twin” or unified dataset, (3) run a controlled PoC in a manageable set of stores, (4) measure against controls and iterate, and (5) stage the rollout with change management and vendor support.

Use proven local examples to de‑risk choices - S Group's RELEX pilot scaled to nearly 200 stores to automate main delivery‑day optimization, while SOK began with ~20 pilot stores and 20 controls for assortment clustering - so size your pilot to the complexity of the use case and the data you have.

The practical payoff is immediate: consolidated deliveries let staff shelve many similar items in one go, cutting repetitive handling and smoothing workload across the week.

For concrete designs, see the S Group AI‑optimized goods flow case study and SOK's assortment optimization story for inspiration.

“We spent a lot of time adjusting the main replenishment days. It worked, and the results were clear, but the approach was very time-consuming and the results still not optimal. We were thrilled about the opportunity to develop AI-based optimization of main replenishment days in collaboration with RELEX.” - Tuulia Wennerkoski, VP Supply Chain at S Group

Finland stands at a practical inflection point: companies plan big digital bets (the AWS Finland brief notes a predicted 58% lift in digital investments in 2024 and 68% over the next three years), so the upside from AI is real, measurable and near-term - but the path is hybrid, not fully automated (AWS Finland digital investment outlook 2024 briefing).

Industry studies show AI can cut operating costs sharply (contact‑centre automation has driven ~30% reductions and 43% adoption in some segments) yet most customers still want humans for complex issues, so success depends on pairing AI with clear escalation rules, data hygiene and human oversight (ISG-One study: AI reduces costs by ~30% but customers still prefer human support).

For Finnish retailers, the pragmatic move is staged pilots plus skills investment: short PoCs that prove KPIs, coupled with team training so staff move from routine tasks to higher‑value roles - practical, applied training is available through Nucamp's AI Essentials for Work to build those prompt‑writing and workflow skills (Nucamp AI Essentials for Work bootcamp syllabus and registration).

The balanced conclusion: embrace AI to reduce waste and boost speed, but design systems so technology amplifies people rather than replaces the human judgement customers still value.