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

This article maps what AI means for finance jobs in Kazakhstan in 2025: who faces the biggest risk, which roles will evolve rather than vanish, and practical next steps for finance teams and individual workers.

Recent local research warns that generative AI and automation put large swathes of work at risk - a Ministry of Labor study reported by Tengrinews estimates just over 1 million jobs could be affected and flags Almaty (the country's finance and ICT hub) as especially exposed - while EconomyKZ highlights broader trends of declining routine roles and rising STEM demand.

Expect clear, localised guidance on at‑risk finance functions (from routine accounting and underwriting to some back‑office roles), resilient and hybrid roles that will grow, and a 2025 playbook of skills to prioritise - including practical training options like Nucamp's AI Essentials for Work bootcamp to learn AI tools and prompt craft so finance professionals can keep ahead of automation instead of being sidelined.

In Kazakhstan today AI is already woven into live finance workflows: local research highlights projects from Nazarbayev University (a successful Kazakh‑language chatbot) to automation in oil and gas, while innovation hubs such as MOST, Astana Hub and Terricon Valley incubate fintech pilots that apply narrow and generative AI to market analysis and routine tasks (see the TimesCA overview).

On the corporate side, treasury teams are adopting AI‑driven cash‑flow forecasting - advanced neural nets and ensemble models that pull ERP, CRM and market feeds to cut forecast error and run thousands of scenario simulations in minutes, a shift JP Morgan calls transformative for treasury strategy.

ERP vendors are shipping predictive forecasting as a built‑in feature that alerts finance teams to late‑payment clusters or cash‑risk signals in real time. And practical tools already used by Kazakhstani professionals - everything from AI risk‑scoring for lending to Prezent‑style automated reporting - show how automation handles repetitive work while leaving judgement, compliance and stakeholder storytelling to humans.

“The combination of AI and Blockchain technologies can contribute to helping clients.” – Jacobo Roa‑Vicens, JP Morgan

In Kazakhstan the clearest targets for automation are the routine, data‑heavy finance tasks that AI already handles best: accountancy and bookkeeping, reconciliation and other back‑office processing, basic underwriting and insurance scoring, high‑volume customer service and claims processing, and even some market‑research workflows - roles flagged as most likely to be automated in broader studies such as Nexford's survey of at‑risk jobs Nexford survey of jobs at risk from AI.

Local momentum makes this more than a theoretical threat: national investment in AI infrastructure and startup growth, plus rising enterprise adoption documented in the CCH Tagetik report on finance teams moving “from skepticism to optimism” (56% see AI's potential, 52% already using it), mean automation will reach everyday finance stacks faster than many expect CCH Tagetik research report on AI in finance adoption.

A vivid indicator: Kazakhstan's own Kazakh‑language model trained on 148 billion tokens shows localized AI is ready to process native documents and customer interactions at scale, widening the net of exposed roles World Financial Review analysis of Kazakhstan's AI progress; the “so what” is simple - if a job is heavy on repetitive data entry, rule application or bulk scoring, it's the first in line for automation.

“We have recently trained nearly 2,000 civil servants and quasi-public sector employees,”

In Kazakhstan the jobs most likely to endure are those that blend technical fluency with judgement: FP&A and strategic reporting, treasury roles that interpret scenario outputs, compliance and controls owners who codify governance, and finance professionals who translate modelled numbers into board‑room narratives.

Global research makes this plain - CFOs must “build trust into AI” and reshape talent to manage smarter reporting systems (EY report: Building trust and talent for tomorrow's reporting technologies), while pragmatic playbooks show AI can “supercharge finance operations” only when paired with strong data governance and change management (Grant Thornton guide: Supercharging finance operations with AI).

Roles that centre on context, judgement and stakeholder trust - for example, a controller deciding whether an unusual contract is a one‑off or a new revenue stream - will evolve into hybrid work with AI assistants rather than disappear.

The memorable edge for Kazakhstani finance pros: the ability to turn an AI output into a single, action‑ready sentence for leadership is becoming the most valuable currency.

“Trust is the foundation on which organizations can build stakeholder confidence in AI systems and the insights they produce.”

AI will streamline many finance workflows in Kazakhstan, but it won't make finance professionals obsolete because law, trust and context still demand people. The country's draft 2025 AI law introduces risk tiers, ethical safeguards, liability rules and even proposals to ban fully autonomous systems - measures that explicitly preserve human oversight and limit where automation can act alone (see the draft AI Regulation in Kazakhstan).

Existing personal data protections and rules requiring explicit consent for biometric processing create practical boundaries for models that touch sensitive customer data, while IP and liability frameworks place legal responsibility on human owners and users rather than on models.

Kazakhstan's push for explainability, a National AI Platform and home‑grown Kazakh language models (one trained on 148 billion tokens) improves local usefulness but also raises the bar for governance, since regulators and boards will expect auditable decisions and accountable sign‑offs before acting on automated outputs.

The net effect: AI becomes a powerful assistant - speeding analysis and scoring - but frontline professionals remain essential for judgement, compliance and translating model results into a single, actionable sentence for leadership.

“The bill reflects major global trends in AI regulation. Many countries have adopted systematic approaches to AI governance. The EU's AI Act, adopted in 2024, serves as the world's first risk-based AI legislation and is already a model for countries like Kazakhstan.”

For finance workers in Kazakhstan in 2025, prioritise AI fluency (hands‑on use of models and prompt craft), practical data literacy (cleaning, interpretation and basic ML concepts), model governance and explainability, and bilingual tool skills to work in Kazakh, Russian and English - skills employers now rank alongside core finance abilities as AI spreads (31% of local finance teams already use AI and many plan to scale it).

Employers increasingly expect applied AI: industry research shows AI fluency is becoming a baseline for hiring, especially in finance, so combine short, local courses with project work - take advantage of free national programmes and Astana Hub courses to build real examples - or join instructor‑led, onsite training options in Kazakhstan for deeper practice.

Add financial storytelling and prompt templates (so an AI output plus two charts becomes one action‑ready sentence for the CEO), and learn risk‑scoring and compliance guardrails so automation augments judgement rather than replaces it; these are the practical, résumé‑ready skills that will keep Kazakhstani finance professionals in demand.

“The future of accounting will be shaped by those who can bridge human expertise with AI capability. This playbook is our blueprint for building that future – one where chartered accountants lead with insight, integrity and innovation.”

A practical 2025 playbook for finance leaders in Kazakhstan stitches together national momentum and proven workforce strategies: link talent plans to the Year of Working Professions and OECD recommendations on sustainable finance to prioritise vocational reskilling and sectoral upskilling (Astana Times: Kazakhstan Year of Working Professions and OECD sustainable finance review); embed strict model governance and explainability as core controls while piloting AI in high‑value pockets such as fraud detection, KYC and treasury forecasting (the country's digital push already includes major AI platforms and Kazakh LLMs) - see the national digitalisation summary for the scale of these initiatives (Astana Times: Kazakhstan AI and digital transformation overview); and commit to systematic reskilling: global evidence shows reskilling and upskilling are the dominant employer response to AI disruption, so design short, assessed programmes that combine tool fluency, data governance and storytelling for leadership (World Economic Forum Future of Jobs Report 2025 - reskilling and workforce strategies).

The operating rule is simple - run tight, measurable pilots that protect customers and data, scale the winners, and convert AI outputs into one clear, action‑ready sentence for executives so skilled finance teams capture the productivity upside without sacrificing trust.

Start small, build practical chops, and make each learning step visible: begin with the free, four‑week “AI People” course from Astana Hub to master everyday AI capabilities, then move to hands‑on, instructor‑led training - online or onsite - such as local NobleProg AI training in Kazakhstan to practice real implementations; complement that with short, job‑focused projects that show measurable wins (for example, use tools that turn quarterly numbers into regulator‑ready slides in minutes as shown in this guide to AI tools for Kazakhstani finance pros).

Prioritise portfolio items a recruiter or line manager can open in 60 seconds - a cleaned dataset, a prompt template in Kazakh/Russian/English, or a one‑slide executive summary generated from an AI output - and pair courses with local networks and hubs to find internships or pilots; this pragmatic pathway turns abstract AI risk into on‑the‑job advantage for juniors entering Kazakhstan's rapidly evolving finance market.

“AI People” is a free, four-week course open to all, regardless of prior experience.

Market signals in Kazakhstan make the AI-and-finance story concrete: a near‑universal digital on‑ramp (internet penetration ~92% and mobile banking used by over 80% of people) has fuelled rapid fintech growth - Kaspi's superapp now touches roughly three‑quarters of Kazakhs, national instant payments and a unified QR code processed billions of transactions in 2024, and regulators have supported innovation with an open‑API sandbox and a CBDC pilot (the Digital Tenge launched in November 2023) - all signs that automation and AI will plug straight into everyday finance rather than remain experimental (see the CSIS DPI report on Kazakhstan's “digital everything” journey and the Astana Times coverage of startup growth).

Local case studies sharpen the signal: microfinance innovators and B2B2C products like Prosper Pay show how payroll‑linked advances can onboard employees in seconds (advances take about ten seconds and typical amounts are small, around $30/month), while bank‑led ecosystems and Open Banking pilots mean incumbents and startups race to embed AI‑driven services into payments, lending and SME tools.

For finance professionals that means exposure and opportunity - automation will handle scale tasks, but winning use cases and pilots are already here, and they're shaped by Kazakhstan's policy choices and consumer habits (see the Ergomania fintech overview for examples).

“Banks are Fintech in Kazakhstan.”

Kazakhstan's fast-moving digital push means the choice is clear for finance professionals in 2025: move from worry to action by combining national, hands‑on training with job‑focused practice.

Take advantage of free state programmes and Astana Hub initiatives that have already trained tens of thousands of civil servants and students, and pair those with short, practical projects that prove you can turn AI outputs into one clear, action‑ready sentence for leaders - for example, tools that can convert quarterly numbers into regulator‑ready slides in minutes, such as Prezent storytelling tools for converting quarterly numbers into regulator-ready slides.

Anchor that skillset in governance and bilingual prompt craft, then validate it in pilots and local ecosystems as Kazakhstan scales national AI platforms like AlemLLM and expands e‑government services to 92% online - a policy backdrop that makes practical AI literacy a career insurance policy, not an optional extra; see Astana Times coverage of Kazakhstan's AI digital transformation.

For a faster route to workplace-ready capabilities, consider an applied course such as Nucamp's AI Essentials for Work - prompt craft, tool use, and workplace AI project training.