Will AI Replace Customer Service Jobs in Kazakhstan? Here’s What to Do in 2025

Will AI replace customer service jobs in Kazakhstan in 2025? The short answer: not wholesale, but change is already here - Kazakhstan's rapid digital transformation has pushed more than 92% of public services online and delivered millions of digital transactions this year, and the government's push to integrate AI (including plans for over 50 intelligent virtual assistants by the end of 2025) means many routine queries will shift to automated channels (Astana Times report: Kazakhstan accelerates digital transformation with AI and blockchain (2025); GlobalCIO analysis: Digital strategies of Kazakhstan and plans for AI virtual assistants).

Local language limits and regulatory work on AI and data protection mean human agents with Kazakh‑ and Russian‑language skills, complex-problem handling, and prompt-engineering know-how will stay in demand - upskilling is practical now, for example through targeted programs like the AI Essentials for Work bootcamp - prompt writing and applied AI skills, which teaches prompt writing and applied AI skills for everyday roles.

“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.”

Kazakhstan's AI push is deliberately national and practical: the government's Concept for the Development of Artificial Intelligence (2024–2029) sets out clear pillars - data, infrastructure, human capital, R&D and regulation - to turn public-sector digitization into an innovation engine rather than a tech experiment (Kazakhstan's AI Concept 2024–2029 (government AI strategy)).

That means pooling state datasets through Smart Data Ukimet, building a home supercomputer and a National AI Platform, and launching centers like Alem.AI to connect academia, business and government while scaling local models (a Kazakh LLM trained on 148 billion tokens is already public).

Parallel targets - training millions in AI skills, producing dozens of sectoral AI products, and boosting local IT exports - make talent development as important as servers and policy, so customer‑service teams face a future where language and problem‑solving skills sit alongside prompt‑crafting and tool fluency (Astana Times report on Kazakhstan national AI strategy and rollout).

“The concept covers international experience, the current situation in Kazakhstan. We describe our tasks and goals in six main areas: human capital, infrastructure, data, public policy, and others,” Baitursynov said.

AI is already reshaping customer service across Kazakhstan by automating routine touches, surfacing faster answers, and freeing humans for harder problems: banks and superapps that once only pushed payments now embed e‑government services and chatbots, while natural‑language tools, speech recognition and OCR speed document checks and call resolution so agents can focus on escalations rather than basic requests (see the CSIS deep dive on Kazakhstan's digital public infrastructure for how payments, digital ID and apps power these customer journeys).

Local firms report real productivity gains from AI, but the language gap matters - models work best in English today, so Kazakh and Russian‑aware systems and localized prompts are essential to keep service relevant and compliant (Astana Times analysis on Kazakhstan's AI progress explains the language and productivity dynamics).

Practical on‑ramps are already in place: speech‑to‑text for Kazakh and Russian, conversation summaries, and prompt templates that coach agents in real time; Nucamp's tool guides and rollout checklists show how teams can start small (30/60/90) and scale safely.

The upshot: customers increasingly expect one‑phone‑day convenience - pay for coffee, register a motorbike and even apply for a mortgage from the same app - and AI is the technology stitching those experiences together, so service roles that blend language, empathy and prompt‑crafting will be the ones to keep and grow.

“artificial intelligence should become a key driving force for the development of Kazakhstan and all its industries.”

Which customer‑service roles are most exposed to AI in Kazakhstan? The short answer: those built around routine, predictable transactions - think bank tellers, basic call‑centre agents, administrative back‑office staff and repetitive onboarding tasks - because these can be reliably codified and automated; Kazakhstan's national analysis even estimates nearly 52% of future jobs are at high risk of automation (Astana Times analysis of job automation in Kazakhstan).

Local workforce studies add useful nuance: while about 75% of workers are currently unlikely to be fully automated, roughly 17% face a material probability of having duties shifted to machines and 7.9% have already been flagged as potentially displaced - with the highest sectoral pressure in information & communications (53.3%), finance & insurance (52.1%), and notable exposure among managers and civil servants (58.9%) where routine supervisory tasks can be digitized (Center for Human Resources Development summary of automation risk in Kazakhstan).

For customer‑service teams that means prioritizing roles that require language nuance, escalation handling and cross‑system judgment; jobs that are mostly script‑driven should be treated as migration candidates rather than long‑term core roles, and employers should plan 30/60/90 upskilling paths to redeploy rather than simply cut headcount.

“The work of a bank specialist is gradually being replaced by ATMs. We no longer need a teller for the operations that we can either do ourselves over the Internet or we go to the bank and do it through an ATM. But if we go to the bank in bad weather and we have puddles of mud coming off our shoes, then immediately two cleaning persons will come running to clean up the mud. And that labor, which is not routine, and which is very simple, very low-skilled, can hardly be replaced,” said Vladimir Gimpelson.

Customer‑service roles least likely to be replaced in Kazakhstan are those that demand human nuance, deep language skills and judgment - think bilingual escalation specialists, relationship managers, and support leads who combine cultural fluency with domain expertise.

Local experts note that AI still struggles to capture the “soul” of creative, context‑rich responses and that Kazakhstan's push for Kazakh‑language tools makes multilingual human agents indispensable (ISSAI interview on AI in Kazakhstan and the limits of automation); global analysis also shows skills like active listening and speaking have lower GenAI exposure, so roles centered on empathy and complex interactions are relatively protected (EY analysis: How generative AI will impact the labor market).

Practical upskilling - localization, prompt‑crafting and multilingual speech models - further hardens these roles against replacement, so agents who can coach models, resolve non‑routine complaints in Kazakh or Russian, and translate policy into day‑to‑day customer outcomes will stay valuable (see guides on localization and cultural training for AI models in Kazakhstan).

Picture the difference between a canned reply and a trusted agent who calms a distraught customer in their mother tongue - that human touch is what keeps some jobs safe.

“Humans will always have a place in creativity.”

Reskilling is turning the risk of automation into a hiring and entrepreneurship opportunity across Kazakhstan's customer‑service sector: national programs and hubs are training cohorts at scale - from Tomorrow School and AI Qyzmet to QazCoders and Alem.ai - so front‑line agents can pivot into prompt engineers, localization specialists, data annotators, AI‑enabled quality analysts and bilingual escalation coaches who supervise models that understand Kazakh‑Russian code‑switching; Kazakhstan's plan to train 500,000 schoolchildren, 300,000 students, 90,000 civil servants and 80,000 business representatives over five years makes these pathways real rather than theoretical (Kazakhstan national AI training targets - Astana Times).

Homegrown models and projects like ISSAI KAZ‑LLM and KAZ LLM mean local demand for engineers who can fine‑tune models, create culturally accurate prompts, and build AI tutors - imagine an agent who once handled 200 scripted calls now coaching an AI tutor that generates quizzes on Abai's poems in Kazakh and scales help for thousands of learners (ISSAI KAZ‑LLM multilingual GPT model announcement - TimesCA); short, practical bootcamps and 30/60/90 rollout plans make transition faster and measurable for employers and workers alike.

“This is a strategic initiative of the Kazakh government.”

Customer‑service agents in Kazakhstan should treat 2025 as a “learn‑by‑doing” year: start with a short, practical course - such as NobleProg's instructor‑led Building Your First Chatbot in Kazakhstan - to understand NLP, conversational flow and how to deploy a simple bot (NobleProg Building Your First Chatbot in Kazakhstan course); next, pilot a single, high‑volume task (missed‑call recovery or FAQ triage) using a no‑code/low‑code agent platform so teams can iterate fast and keep humans in the loop (Kore.ai's Agent Platform shows how multi‑agent orchestration, observability and human‑in‑the‑loop reviews work in practice: Kore.ai Agent Platform for multi‑agent orchestration and observability).

Pair that pilot with localization - deploy speech‑to‑text for Kazakh and Russian and use a 30/60/90 rollout checklist to set measurable goals, handover rules and SLA targets (30/60/90 AI rollout checklist for Kazakh customer service).

Focus personal upskilling on prompt‑crafting, bilingual escalation handling and RAG‑grounding techniques so agents become the model supervisors who catch errors before customers do - imagine turning a clogged queue into an app that calmly answers in your mother tongue while you handle the hard cases.

“As we enter the era of AI commerce, it's pivotal to have brands and products innovating in this space that users already know, trust and are comfortable with. We're excited to partner with Visa in this next wave of the internet.”

Employers and policymakers in Kazakhstan should move from talk to tangible steps: establish a small, accountable “AI value realization office” to pilot quick-win automations and scale successful playbooks (see EY's practical roadmap), run a nationwide skills‑gap audit led by HR so training targets are evidence‑based and tied to career paths (Aon shows how to link skills data to reskilling), and co‑fund short, role‑specific pathways - on‑the‑job microlearning, bilingual prompt‑crafting modules and subsidized 30/60/90 pilots - to lower cost and time barriers that Nexford and KellyOCG flag as key to resilience.

Pair these people efforts with a phased data‑architecture and governance upgrade and a few strategic ecosystem pilots (vendors, universities, and global consortia) so tools are localised for Kazakh and Russian use.

Measure progress with simple KPIs (retraining completion, redeployment rate, AI‑error catch rates) and tie incentives to retention and internal mobility: employers who invest in AI fluency will keep talent and preserve institutional knowledge while regulators should fast‑track ethical guardrails and funding for regional training hubs.

For pragmatic guidance, adapt the EY playbook, Aon's skills audit approach, and a Nucamp 30/60/90 rollout to local realities and languages.

“Organizations can lead the AI charge by ensuring that the integration of AI into the workplace is done thoughtfully and ethically, maximizing benefits for both the organization and its employees.”

Kazakhstan already has practical, local wins that show how AI and automation can lift customer service rather than just cut jobs: Halyk Bank's wide AI adoption - from KYC to fraud detection and about 180 “invisible” RPAs that speed routine work - demonstrates enterprise-scale gains (Halyk Bank digital strategy and national IT trends), while Otbasy Bank's Python RPA rollout processed some 2,000 scanned documents per day (work that would have needed roughly 13 people), freed help‑desk staff for higher‑value tasks, and shows how a mix of OCR, low‑code bots and human oversight scales fast (Otbasy Bank Python RPA case study).

Other sector examples - Kazpost's eGov integration and Tele2/Altel's ML marketing platform - prove the point: when pilots focus on language, integration and observability, customers get faster, more personalized service and agents get room to handle the complex cases that machines can't.

For teams ready to adopt these approaches, practical toolkits like the Nucamp AI Essentials for Work roundup of Kazakh-friendly AI tools make starting small and scaling safely straightforward (Nucamp AI Essentials for Work Kazakh-friendly AI tools roundup).

“We have formed criteria for selecting processes for robotization. We make robots to reduce human errors, improve the manageability of processes and to free up man-hours. We are not reducing staff, but redistributing the workload, and employees have free time for other, more complex tasks.”

Kazakhstan's rapid digital push brings a parallel surge in cyber risk that customer‑service teams can't ignore: high‑profile incidents - from the 16‑million‑record leak dissected by The Astana Times to a string of service outages and leaks tracked by the Times of Central Asia - have eroded public trust and amplified hourly fraud calls, while incident counts logged by KZ‑CERT jumped from about 34,500 in 2023 to roughly 68,100 in 2024, underlining how threats are scaling fast.

Practical mitigation is straightforward and local: enforce real‑time monitoring, regular independent penetration tests, tighter rules for inter‑agency data sharing, clear incident playbooks and faster forensic audits to restore confidence (the ministry has pledged audits after recent breaches).

Close the human loop with basic digital hygiene - strong passwords, two‑factor authentication, NomadGuard checks and free CitizenSec training for staff and customers - and pair that with sectoral cybersecurity centres, bug‑bounty programs and small, measurable pilots (a 30/60/90 rollout checklist helps teams test AI automations safely while preserving customer data).

Because regulatory fixes only work when implemented, employers should tie reskilling, observability and vendor contracts to KPIs that reward security‑minded behaviour: when a bank teller becomes a model supervisor and a team can block a phishing wave before it hits the queue, the whole system gets safer and trust rebuilds.

“From a prevention standpoint, several key measures play a critical role – regular independent penetration tests that help identify vulnerabilities before malicious actors can exploit them, connecting organizations to sectoral cybersecurity centers, which facilitate the exchange of information on threats, incidents, and protection guidelines, and participation in bug bounty programs, where ethical hackers help uncover flaws in a secure and controlled environment before they lead to data breaches,” Kabi explained.

The short outlook for 2025–2029 is pragmatic: AI will reshape many customer‑service tasks in Kazakhstan, but large‑scale replacement is unlikely where policy, investment and education are creating new demand and skills - the government's drive to double GDP by 2029 is paired with a $1bn high‑tech investment push and digital reforms that embed AI across public services (Astana Times report on Kazakhstan's GDP doubling plan and $1bn high‑tech investment), while a national talent build - from mandatory AI in universities to a 2‑exaflop supercomputer and plans to attract 150,000 international students - supplies the workforce to run and localize those systems (Times of Central Asia coverage of higher-education transformation and international student targets).

For customer‑service professionals that means a clear path: routine tasks will be automated, but bilingual escalation specialists, prompt engineers and AI‑literate supervisors who can ground models in Kazakh/Russian will grow in value; practical reskilling is within reach through short, applied programs such as Nucamp's AI Essentials for Work (Nucamp AI Essentials for Work bootcamp syllabus), which teach prompt writing and on‑the‑job AI skills.

The memorable takeaway: with Alatau City, national platforms and new funding channelling investment into high‑tech jobs, Kazakhstan's customer‑service sector looks set to shift from volume handling to value creation - those who learn to coach and localize AI will be the ones leading teams through 2029.

“To achieve this, fundamentally new methods of controlling and monitoring public services across all sectors of the economy must be established through the deep integration of digitalization and artificial intelligence technologies.” - Prime Minister Olzhas Bektenov (as reported by Astana Times)