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

Kazakhstan's retail landscape is at a practical inflection point in 2025: with about 19.2 million internet users and a booming e‑commerce market that reached 3.439 trillion KZT in 2024, consumers expect faster, hyper‑relevant experiences and local language support - trends documented in recent market analysis and digital marketing reports.

National programs and pilots - from the multilingual Oylan model to cloud and data‑center investments - mean government policy is actively lowering barriers for AI in commerce, including plans to deploy over 50 intelligent virtual assistants this year to streamline services (Global CIO analysis of Kazakhstan's AI rollout).

For retailers, practical wins include AI forecasting, personalization and fraud reduction; turning those tools into daily operations starts with skills, so busy managers and merchandisers can learn hands‑on workflows through targeted training like the AI Essentials for Work bootcamp, which teaches prompts, tools and job‑based applications to make AI a reliable part of store operations.

“By the end of 2025, Kazakhstan plans to launch over 50 intelligent virtual assistants that will operate on the basis of AI to simplify citizens' access to ...” - Global CIO

In 2025 the global AI race is still led by massive U.S. and Chinese investment and model development, but Kazakhstan is no longer just watching from the sidelines - it is carving a regional lane by turning policy, compute and skills programs into real productivity gains for developers and public services.

Stanford's 2025 AI Index makes clear that the U.S. produces most top models while China is closing the gap, yet Kazakhstan's own momentum is striking: large-scale research found Kazakh developers using AI boosted productivity by about 16.8% (slightly above the 16.4% global average), a sign that targeted state support and a growing tech ecosystem are paying off (Stanford 2025 AI Index report on AI, Astana Times profile of Kazakhstan's AI progress).

That said, language and infrastructure remain strategic chokepoints - projects like a Kazakh-language model and new GPU data centers tackle both, while draft 2025 legislation proposes tiered risk rules and data limits to balance innovation with trust (Digital Nemko guide to Kazakhstan AI regulation (2025)).

The upshot for retailers: global advances lower the cost of AI tools, but local success will depend on closing language gaps, securing data, and tapping the government's expanding compute and training pipeline - imagine a local virtual assistant that understands Kazakh slang and restocks shelves before a popular holiday rush.

“For Kazakhstan, the development of AI is one of the top national priorities and is closely monitored by President Tokayev. This year, the country plans to launch a series of NVIDIA GPU-based data centers and the international AI center Alem AI. All this is expected to lead to a $5 billion export of AI-based products and services by 2029,” said Abdualiyev.

When asking which country is No.1 in AI technology, the short answer is: the United States still leads on research, models and private investment, while China is closing gaps in performance and has surged ahead in patent volume - but Kazakhstan is showing encouraging pockets of engagement that matter for retailers planning local AI adoption.

Stanford's 2025 AI Index documents that U.S. institutions produced far more notable models (about 40 in 2024) while China produced fewer but rapidly improved systems and is narrowing benchmark gaps (Stanford 2025 AI Index report); at the same time China dominates patent filings by volume, outpacing peers by a wide margin (2025 global AI patents by country analysis).

Kazakhstan does not sit in the superpower tier of compute or patents, but the AI Engagement Index places it in the global mix (global rank 54, per‑capita rank 45 with a per‑capita score of 3.08), a signal that local talent and buyer demand can still accelerate practical retail use cases like Kazakh‑language assistants and automated replenishment.

Put simply: the U.S. and China shape the frontier (compute, models, patents), but Kazakhstan's rising engagement means retailers who translate global tools into Kazakh‑aware workflows can win customers while infrastructure and data sovereignty catch up (AI Engagement Index country rankings (2025)).

“Everything is becoming more split. We are losing.” - Nicolás Wolovick, on the global AI divide

China's blunt goal to become the world AI leader by 2030 - backed by an industrial playbook that aims for a $100 billion AI core industry and state tools from subsidized compute to national AI funds - reshapes the regional competitive picture (see the RAND Full Stack analysis of China's AI policy RAND Full Stack analysis of China's AI policy and the Carnegie Endowment critique of Beijing's AI‑everywhere strategy Carnegie Endowment critique of Beijing's AI‑everywhere strategy).

“AI‑everywhere” push

For Kazakhstan retail, the takeaway is strategic, not adversarial: competing head‑to‑head with China's scale is unrealistic, but Kazakhstan can convert that global momentum into practical local advantage by pairing targeted infrastructure (more GPU capacity and the emerging Alem AI hub) with Kazakh‑language models, compliance‑aware data practices, and merchant-focused workflows.

The result is concrete: retailers that plug into local compute and language pipelines can use cheaper, better off‑the‑shelf tools shaped by global R&D yet tuned for Kazakhstan - think a virtual assistant that understands Kazakh slang and triggers automatic replenishment before a national holiday sells out - a small operational win that translates into fewer empty shelves, happier customers, and measurable margin improvement.

Global estimates for the size of the AI market in 2025 vary - reports range from roughly USD 294 billion to more than USD 750 billion - yet every forecast points the same way: fast growth, falling costs, and broad enterprise adoption, all of which matter directly to Kazakhstan retailers.

Whether analysts use a narrower or broader market definition, projected CAGRs in the high teens to mid‑30s percent (and multi‑trillion dollar forecasts by 2030–2034) mean cheaper models, more cloud services, and a growing pool of off‑the‑shelf tools that can be localized for Kazakh workflows; see the detailed market figures in the Precedence Research analysis and the Fortune Business Insights forecast for context (Precedence Research: AI market, Fortune Business Insights: AI market forecast).

so what

For everyday retail operations the is tangible: lower inference costs and more SaaS copilots make it realistic to deploy Kazakh‑aware virtual assistants, automated replenishment and NLP vendor‑onboarding in stores from Almaty to smaller towns - workflows already outlined in practical guides for Kazakhstan retail (Inventory Monitoring & Automatic Replenishment).

The net effect is simple: as global investment pours in and tools commoditise, retailers who translate those tools into local language, compliance‑aware workflows can turn large market momentum into fewer empty shelves, faster checkout experiences, and measurable margin gains.

Key AI technologies reshaping Kazakhstan's retail scene in 2025 are practical and familiar - but now tuned for local scale: hyper‑personalization and recommendation engines powered by ML are turning high mobile engagement and marketplace traffic into tailored offers, while dynamic pricing and visual search speed discovery across apps and stores; see how programmatic and in‑app ad growth is driving these shifts in Kazakhstan (What Awaits Digital Marketing in Kazakhstan in 2025 - BYYD).

Natural language processing and Kazakh‑aware virtual assistants (built on local datasets like Oylan) make multilingual chatbots, voice search and vendor‑onboarding practical for merchants and consumers, and automated replenishment systems cut empty‑shelf losses by triggering orders when demand spikes - a workflow already recommended for Almaty–Astana routes (Inventory Monitoring and Automatic Replenishment for Almaty–Astana Routes).

Underpinning these tools are growing local cloud and data‑center capacity plus RPA and ML platforms that handle fraud detection, loyalty segmentation and supply‑chain forecasting (see Kazakhstan IT trends and infrastructure plans in the Global CIO review), so retailers can deploy real‑time personalization, automate routine tasks, and deliver Kazakh‑language experiences to the majority of customers who now prefer local content.

“By the end of 2025, Kazakhstan plans to launch over 50 intelligent virtual assistants that will operate on the basis of AI to simplify citizens' access to ...” - Global CIO

Retailers in Kazakhstan must build compliance into every AI rollout because the country's 2025 draft AI law is reshaping what's allowed - and how it must be explained and documented - by introducing risk tiers, tighter data‑protection limits (including explicit consent for biometric data), liability provisions and ethical guardrails that echo the EU's risk‑based approach; see a practical summary of the draft framework for details (Practical summary of Kazakhstan's 2025 draft AI law) and coverage of the bill's EU‑inspired, human‑centred aims (Euractiv coverage of Kazakhstan's EU‑inspired AI law goals).

Operationally this means classifying systems as high/medium/low risk, documenting explainability for customer‑facing models, avoiding banned fully‑autonomous deployments, and treating large‑scale misuse as potentially criminal - all while tapping the National AI Platform and the new Kazakh‑language model (148 billion tokens) to keep local UX and transparency practical.

The transition window rewards retailers who invest now in data governance, consent flows, and human oversight: those steps shrink legal risk and make features like Kazakh‑aware virtual assistants and automated replenishment defensible under the coming rules, turning compliance from a cost into a customer‑trust advantage.

“The bill reflects major global trends in AI regulation.” - Sholpan Saimova

Practical use cases in Kazakhstan's retail scene are immediate and local: marketplaces and retail media on platforms like Kaspi.kz turn targeted promos into sales at scale (marketplaces account for roughly 91% of e‑commerce sales and Kaspi's super app reported ~14.7 million MAUs and >5.9 billion transactions in 2024), while inventory monitoring and automated replenishment tailored to Almaty–Astana routes prevents empty shelves and lost revenue (Inventory monitoring and automatic replenishment in Kazakhstan retail).

Natural language processing speeds vendor onboarding and contract review, making multi‑lingual (Kazakh‑aware) chatbots a practical frontline tool for small merchants (Kazakh-aware NLP for vendor onboarding and contract review), and seamless cross‑border QR payments - now enabled for international wallets via Kaspi QR and Alipay+ - boost tourist spend without new POS hardware (Alipay+ and Kaspi QR enable international payment acceptance in Kazakhstan).

Combine these elements - programmatic in‑app ads, Kazakh‑language assistants, automated replenishment and unified payments - and retailers can convert higher mobile engagement and rapid delivery into measurable margin gains and fewer stockouts: a vivid operational win is a flash sale that auto-reorders via local logistics and lands on a customer's phone within hours, not days.

“Since last year, Kazakhstanis have been able to pay in their favourite travel destinations using the Kaspi.kz super app,” - Mikhail Lomtadze, CEO and Co‑founder of Kaspi.kz

Begin with a short compliance check and a focused pilot: map your planned systems to Kazakhstan's draft 2025 risk tiers and data limits so you can choose a low‑risk, high‑impact use case (for example, inventory monitoring and automatic replenishment on Almaty–Astana routes), then run a time‑boxed pilot that proves value while keeping human oversight in the loop.

Treat data governance as step one - centralize records, log model inputs, and obtain explicit consent for sensitive data - and use the National AI Platform and the new Kazakh‑language model to keep UX local and explainable; see a practical summary of the draft law for the latest compliance cues (Kazakhstan 2025 AI regulation draft summary).

Parallel to pilots, tighten third‑party controls: apply AI readiness checks and vendor due diligence to any cloud or SaaS provider (the EY playbook on AI for third‑party risk is a useful template) so contracts and monitoring scale with the tech (EY playbook for managing third‑party AI risk in Kazakhstan).

Finally, start small, document everything, train a handful of merchandisers on day‑to‑day prompts and dashboards, and expand only after you can point to one vivid win - a sale that auto‑reorders and reaches a customer within hours, not days - turning compliance into trust and pilots into repeatable operations (Inventory monitoring and automatic replenishment AI use case guide).

“Fraudsters are already using deepfake technology to fake video and audio recordings, which seriously threatens information security. It is important to think about de-anonymization on the internet because everyone should be responsible for the disseminated data,” - Saken Sarsenov

Kazakhstan's retail future now looks less like a distant possibility and more like an operational roadmap: national commitments (AI strategy to 2029, Alem.AI, AlemLLM and new supercomputing and cloud capacity) are building the local language, compute and policy scaffolding that retailers need to move from pilots to profit (Astana Times: Kazakhstan accelerates digital transformation with AI and blockchain (2025)); at the same time global research shows the fastest path to ROI is practical - clean customer data, focused micro‑experiments and repeatable workflows - so grocers, marketplaces and c‑stores can realistically deploy Kazakh‑aware chat assistants, automated replenishment and dynamic pricing without reinventing the wheel (Publicis Sapient: generative AI retail use cases).

The commercial logic is simple: high digital engagement and expanding connectivity make AI tools economically reachable, but winning in KZ requires three linked moves - shore up data hygiene, run time‑boxed pilots that prove value, and train squads to operate models day‑to‑day - skills that busy managers can gain through short, practical programs like the Nucamp AI Essentials for Work bootcamp.

Retailers that stitch together local language models, tightened governance and on‑the‑job AI skills will turn national momentum into everyday wins - think a flash sale that auto‑reorders from a nearby warehouse and lands on a customer's phone within hours, not days - turning technical ambition into measurable margin and customer trust.

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