How AI Is Helping Healthcare Companies in Kazakhstan Cut Costs and Improve Efficiency

Kazakhstan's health system is quietly becoming a testing ground for practical, cost-cutting AI: tools like PneumoNet are speeding CT reading and triage across regional clinics, while home‑grown platforms such as ImmuniGuide use blood‑test data to flag hidden infections and tailor immune‑health advice - real-world wins that show AI can lift capacity in understaffed hospitals.

The World Bank's FPIP/TCGP support helped PneumoNet scale to hundreds of devices and tens of thousands of monthly screens, and WHO's push for digital health skills highlights a parallel need to train clinicians and managers to use these tools safely.

For nontechnical health staff and managers who need to harness AI immediately, short practical programs such as Nucamp's Nucamp AI Essentials for Work bootcamp can teach promptcraft and tool workflows, while deeper pilots documented by the World Bank feature on AI research and commercialization in Kazakhstan and reporting on Astana Times coverage of ImmuniGuide's immune-health assessment show how diagnostics and screening are already cutting clinician time and improving detection.

Metric	Value
Medical devices connected	240
Medical organizations	130
Monthly screenings	30,000
Lung diseases identified by PneumoNet	17
TCGP grant to consortium	$340,000

“We spent more than eight years developing this platform. Starting from initial concepts in 2016, we secured four copyrights, registered a trademark and redesigned the platform to incorporate AI. In July 2024, we launched it for industrial use and it is already delivering positive results in clinics,” said Nurlybek Uderbayev, co‑founder of ImmuniGuide.

AI is already doing the heavy lifting across Kazakhstan's health system: PneumoNet's algorithms can flag 17 infectious lung diseases - speeding CT triage so radiologists can do their work in roughly half the time and helping prioritize who needs urgent care - while regionally deployed teleradiology networks mean patients no longer wait days for film reports.

Nation-wide pilots show this scales: PneumoNet is connected to hundreds of devices and runs about 30,000 screenings a month, and a Zhetisu region system analyzed roughly 400,000 images last year, helping detect more than 150 early-stage breast cancers and now covering about 90% of public institutions there.

Beyond imaging, Kazakhstan is trialing new AI services - from therapists that can make preliminary diagnoses at up to 80% accuracy to home‑grown imaging tools - creating faster, remote-ready workflows that cut clinician time and bring diagnostics closer to small towns and industrial cities hard-hit by lung disease.

See the World Bank feature on PneumoNet in Kazakhstan and the SilkwayTV report on Zhetisu's AI rollout for details.

Metric	Value
PneumoNet: diseases identified	17
PneumoNet: devices connected	240
PneumoNet: monthly screenings	30,000
Zhetisu AI: images analyzed (last year)	~400,000
Zhetisu: public institution coverage	90%
Zhetisu: early breast cancers detected	150+

“The implementation of a centralized system has helped address one of the most pressing problems in the sector – the shortage of radiologists, particularly in remote areas. Previously, to interpret an image, radiologists had to personally travel to regions or districts or wait for the developed film to arrive, which could take several days. Sometimes, especially at night and on weekends, this meant they had to come to the hospital urgently. Today, thanks to secure VPN access, doctors can connect to the system from anywhere with internet access, view images in full quality, write their reports, and send them back to the medical organization,” said Yerzhan Kaliyev, project manager for the implementation and maintenance of information systems.

PneumoNet is a practical, on‑the‑ground AI success story in Kazakhstan: developed in partnership between the Kazakh Research Institute of Oncology and Radiology (KRIOR) and Forus Data, the tool can screen for 17 contagious lung diseases - including pneumonia, tuberculosis, cancer and COVID‑19 - and by May 2020 was already deployed in three frontline hospitals in Almaty and Nur‑Sultan to speed triage and prioritize who needs urgent care or hospitalization, complementing PCR testing as CT use jumped during the pandemic.

The result is less time wasted waiting for reports and faster identification of patients who need treatment now, not later; that shift from slow film workflows to instant AI‑assisted reads is one reason regional clinics can manage surges without hiring a proportional number of radiologists.

Practical workforce supports like the Tech Orda training simulator help clinicians translate those faster reads into safer decisions, while clinical CT studies underline why timely imaging and AI triage matter for patients with COPD and COVID‑related pneumonia.

Learn more in the Borgen Project overview of Kazakhstan's AI rollout and the Tech Orda training simulator for hands‑on imaging practice.

Funding in Kazakhstan has been practical and catalytic: the World Bank's Fostering Productive Innovation Project (FPIP) and its Technology Consortia Grant Program (TCGP) deliberately link research labs with private firms to derisk commercialization and create early market pathways.

That model paid off for PneumoNet - an innovation consortium led by KRIOR and Forus Data - which received a $340,000 TCGP grant to scale an AI CT‑screening system now connected to 240 devices across 130 medical organizations and running about 30,000 screenings each month; FPIP's broader program supports some 70 subprojects across sectors, helping teams move prototypes into fielded tools like LungCancerCT and MGraphNet.

For healthcare companies, this shows how modest, well‑targeted public grants and consortia can provide credibility, early customers and vocational training pathways that rapidly expand service capacity - imagine a single grant acting like a turbocharger for nationwide screening.

See the World Bank's feature on AI commercialization in Kazakhstan and the FPIP project summary for program details.

Metric	Value
TCGP grant to PneumoNet consortium	$340,000
Medical devices connected (PneumoNet)	240
Medical organizations	130
Monthly screenings	30,000
FPIP-supported subprojects	70

“In the early days of the pandemic, frontline medical staff were introduced to working with the PneumoNet system. By May 2020, the system was used by three frontline hospitals in Almaty and Nur-Sultan, allowing radiologists to do their work in half the time and expediting the triaging of patients based on need for critical care and hospitalization. In addition, the system complemented the PCR diagnoses as the number of COVID-19 cases increased,” says Dauren Baibazarov, the executive director of Forus Data.

Follow-on pilots in Kazakhstan have turned PneumoNet's momentum into practical next steps: the innovation consortium behind it parlayed AI screening into a LungCancerCT tool now being tested at the Almaty Oncological Center and scheduled a breast‑cancer detector, MGraphNet, for launch trials in April 2022, while the World Bank's FPIP continues to seed roughly 70 commercialization subprojects that spread these gains across sectors; clinical evidence for low‑dose CT screening in radon‑affected Kazakh regions adds local clinical rationale for these pilots (see the PubMed study on low‑dose CT screening in Kazakhstan), and workforce readiness is being strengthened by hands‑on simulators like the Tech Orda training simulator to help radiologists and technicians translate automated reads into safe follow‑up plans.

These follow‑on projects show a clear pathway: diagnostic AI that proved it can triage urgent lung disease is now being adapted to find earlier cancers and broaden screening, backed by modest public grants that reduce commercialization risk and speed real clinic adoption - turning a pandemic-era backlog into continuous screening capacity that can spot treatable disease earlier.

Learn more from the World Bank feature on Kazakhstan's AI commercialization and the Kazakh low‑dose CT screening study.

Metric	Value / Status
PneumoNet: diseases identified	17 infectious lung diseases
PneumoNet: devices connected / monthly screenings	240 devices / ~30,000 screenings
TCGP grant to consortium	$340,000
FPIP-supported subprojects	70
Follow-on pilots	LungCancerCT (Almaty testing); MGraphNet (trials Apr 2022)

“In the early days of the pandemic, frontline medical staff were introduced to working with the PneumoNet system. By May 2020, the system was used by three frontline hospitals in Almaty and Nur-Sultan, allowing radiologists to do their work in half the time and expediting the triaging of patients based on need for critical care and hospitalization. In addition, the system complemented the PCR diagnoses as the number of COVID-19 cases increased,” says Dauren Baibazarov, the executive director of Forus Data.

Kazakhstan's national approach to AI is shifting from pilots to system‑level procurement and governance: the Government adopted a Concept for Artificial Intelligence Development (2024–2029) that pairs a national AI platform and a newly installed supercomputer with a centralized Smart Data Ukimet (already linking 93 information bases) so public and private buyers can access higher‑quality datasets and compute for clinical models and services, while ministries have been tasked to simplify leasing of ICT infrastructure and open the supercomputer to business and academia.

Policy work is moving in parallel - a draft law, a new AI and Innovation Development Committee, and plans for ethical standards and a legal regime for “AI objects” aim to make procurement, certification and risk management clearer for hospitals and vendors.

The Concept sets concrete targets (a fivefold rise in AI products by 2029 and expanded AI education), backs LLM and language‑tech work to preserve Kazakh content, and signals that governments will use procurement, shared infrastructure and training programs to scale proven tools like PneumoNet across regions - a practical pathway that turns one‑off pilots into repeatable, budgeted buys.

See the Kazakhstan AI Concept 2024–2029 (government document) and Astana Times coverage of Kazakhstan AI policy and implementation tasks.

Metric	Value / Note
Smart Data Ukimet connections	93 information bases
AI products target by 2029	Grow 5×
Universities with AI specialisations	17 universities; 15 specialisations; 2,196 students
Infrastructure	Supercomputer, national AI platform, data centres

Kazakhstan's digital push is already paying off in hard savings and faster care: national reforms - from paperless medical certificates to widespread telemedicine - helped shave 13 billion tenge (about US$24.1 million) from citizens' costs and delivered some 1.5 million remote consultations, while streamlining public services contributed to a reported 51.3 billion tenge economic effect overall; the government's full account is in the Kazakhstan Presidential Address on building a digital ecosystem (2024).

On the clinical side, strengthened primary health care models already saved an estimated 270 million tenge in one region over two years and could scale to roughly 32 billion tenge nationwide if rolled out, proving that shifting care closer to home and using telemedicine cuts unnecessary hospital stays and costs (Astana Times: Kazakhstan primary health care reform saves millions).

These gains depend on skilled staff who can use the tools safely and efficiently - an issue WHO highlights as critical for sustaining savings and quality as digital services and AI scale (WHO report on Kazakhstan's digital health workforce needs).

Picture a village clinic that once sent patients on costly journeys now resolving cases by video the same day - that practical shift is the clearest measure of “so what” in Kazakhstan's efficiency story.

Metric	Value
Telemedicine services	1.5 million
Citizen savings from telemedicine	13 billion tenge (~US$24.1M)
Regional PHC savings (example)	270 million tenge (~US$516,000)
Potential nationwide PHC savings	32 billion tenge (~US$59.2M)
Total economic effect of digital solutions	51.3 billion tenge
Budget savings from electronic medical certificates	450 million tenge

“Today Kazakhstan ranks 24th among 193 countries in the world in terms of digitalization and is among the top ten leaders in the online services index. Already 92% of public services are available online,” said Minister Zhaslan Madiev.

Kazakhstan's move from paper records to rapid digital care has put workforce development front and center: WHO‑led roundtables with deans from seven medical universities stressed that safe AI adoption needs foundational digital literacy, telemedicine skills, and hands‑on experience with data analytics so clinicians can trust and act on automated reads; this is being backed by an EU‑co‑financed €10 million WHO programme that funds training and immunization system strengthening through 2026.

Practical steps are already visible - interdisciplinary curricula that pair clinicians with data scientists, simulators to rehearse imaging cases, and national efforts to build secure data platforms - so hospitals can scale PneumoNet‑style tools without creating new safety gaps.

Funded UN and WHO initiatives such as the Joint SDG Fund's Integrated Approaches programme further amplify training reach and investment in a National Digital Health Strategy, meaning that a nurse in a regional clinic can soon access the same AI decision support and security training as a capital‑city specialist, turning rapid tech change into reliable, everyday improvements in patient triage and follow‑up (WHO roundtable on Kazakhstan's digital health workforce, Joint SDG Fund: Integrated Approaches for Digital Health Transformation in Kazakhstan, Medical Futurist: Kazakhstan as a digital health hub).

Metric	Value
EU–WHO project funding	€10 million (2022–2026)
Joint SDG Fund total funding	US$7,545,823
Healthcare professionals reached (Joint programme)	~280,711
Medical universities represented at WHO roundtable	7

“The planning horizon for education and human resource management in health care is extremely long, while technologies are bringing us everyday revolutions right now. This means we have to address the topic of digital health in pre-service education in a strategic and mindful manner,” stated Mr Beibut Yessenbayev, Vice Minister of Health of Kazakhstan.

Kazakhstan's fast‑moving AI rollout in health care brings tangible benefits but also clear risks: the still‑evolving draft “On Artificial Intelligence” law signals stricter rules for high‑risk systems (those that touch life and health) and even contemplates bans on fully autonomous decision‑making, so hospitals and vendors must plan for new compliance pathways rather than winging deployments; meanwhile existing personal data rules require written consent, local storage in many cases, rapid breach notification and create real liability exposure if health data are mishandled, making careful data governance non‑negotiable (see the draft Astana Times report on Kazakhstan's draft AI law and the country's long‑standing Kazakhstan Personal Data and Its Protection framework (DLA Piper)).

Operationally, explainability and human oversight are central requirements, and gaps remain between high‑level aims and technical guidance - so without investment in retraining, audit trails, and secure data pipelines, clinics risk regulatory penalties, slowed procurement, and loss of patient trust; the practical consequence is stark: explainability failures or a data breach can turn a useful triage tool into a legal and reputational crisis overnight.

“The principle of transparency and explainability ensures that AI-driven decisions are understandable and verifiable, especially when they affect citizens' rights. The focus on human well-being emphasizes that technology should empower, not replace, people and should not override individual autonomy,” said Sholpan Saimova.

Healthcare companies ready to scale AI in Kazakhstan should take clear, practical steps now: align product roadmaps with the incoming national AI Strategy and standards so procurement-ready solutions meet content‑labeling, classification and responsibility rules (see Kazakhstan's plan to upgrade the AI Concept into a Strategy); register pilots on the National AI Platform and QazTech to gain access to shared datasets and compute - including Central Asia's new supercomputer cluster - rather than building isolated stacks; embed sovereign data and cybersecurity by default (local storage, breach notification and audited pipelines) to meet tightening oversight; partner with the government's new digital headquarters and Samruk‑linked initiatives to win integration into public health pilots and unified medical databases; invest in workforce programs (AI‑Sana, university partnerships and hands‑on simulators like Tech Orda) so clinicians can safely use AI outputs; and design phased procurement-friendly trials with clear human‑in‑the‑loop controls and explainability metrics so hospitals can buy with confidence.

Treating regulation, training and secure infrastructure as product features - rather than afterthoughts - turns compliance into a competitive edge and smoother scale across Kazakhstan's public and quasi‑public health networks (Astana Times: Kazakhstan to Develop National AI Strategy This Year, Astana Times: President Tokayev Calls for Urgent Action to Make AI a Driver of National Development, DIG Watch: New Digital Headquarters Aims to Embed AI Across Kazakhstan's Public Services and QazTech Access).

“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.

Conclusion for beginners: Kazakhstan's AI story is practical and approachable - start by learning the everyday skills that let clinics turn CT scans and messy paper trails into fast, actionable care: PneumoNet today runs about 30,000 screenings a month, is connected to 240 devices across 130 medical organisations, and grew from a $340,000 TCGP grant that shows how modest public funding can derisk commercialization; for an accessible primer on that commercialization pathway see the World Bank feature on Kazakhstan AI research commercialization (World Bank feature: AI and research commercialization in Kazakhstan).

For hands‑on upskilling, nontechnical managers and clinicians can learn promptcraft, tool workflows and practical AI uses in short, job‑focused courses such as Nucamp's AI Essentials for Work (Nucamp AI Essentials for Work syllabus), while national guidance on digitalization and e‑health helps map procurement and data rules for pilots (Kazakhstan government review of digital health reform).

Start small: run a tightly scoped pilot with clear human‑in‑the‑loop checks, document outcomes, and use public programs and shared infrastructure to scale - this turns a tested tool into system‑level savings and faster care without assuming risky, expensive rewrites of existing services.

Metric	Value
PneumoNet: infectious lung diseases identified	17
Medical devices connected	240
Medical organizations	130
Monthly screenings	30,000
TCGP grant to consortium	$340,000

“In the early days of the pandemic, frontline medical staff were introduced to working with the PneumoNet system. By May 2020, the system was used by three frontline hospitals in Almaty and Nur-Sultan, allowing radiologists to do their work in half the time and expediting the triaging of patients based on need for critical care and hospitalization. In addition, the system complemented the PCR diagnoses as the number of COVID-19 cases increased,” says Dauren Baibazarov, the executive director of Forus Data.