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More speed, accuracy: AI a booster shot for hospitals, diagnostic companies

Hospital chains like Apollo and Aster lead the way as AI boosts accuracy, cuts costs, and transforms patient outcomes

AI HEALTHCARE, AI HEALTH
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Hospitals across country planning to raise IT innovation spending by 20–25% over next 2-3 years

Shine JacobSohini Das Chennai/Mumbai

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From clinical care to streamlining hospital operations or enhancing patient engagement, artificial intelligence (AI) is redefining the functioning of hospital chains and diagnostic companies in India. 
Industry giants like Apollo Hospitals and Aster are already leading the way by implementing tech initiatives like large language models (LLMs) for clinical decision-support and improving patient experiences through predictive analytics and connected devices. 
According to a CII–EY HealthTech Survey last week, others are also not far behind, with hospitals across the country, driven by the AI revolution, planning to raise their information technology (IT) innovation spending by 20–25 per cent over the next two to three years. 
Apollo Hospitals claims that AI initiatives have helped in reducing emergency incidents by up to 80 per cent, enabling earlier interventions and better patient safety. 
“AI has significantly improved diagnostic speed and accuracy. Tools like AI-powered stroke CT interpretation and oncology imaging allow for faster and more precise analysis. Clinical copilots provide real-time decision prompts during consultations, reducing delays and improving outcomes,” said Sangita Reddy, joint managing director, Apollo Hospitals. 
Apollo is deploying AI across the entire care continuum — from diagnostics to post-treatment monitoring. “We use large language models (LLMs) for clinical decision-support, helping doctors navigate complex care pathways. AI-powered image interpretation tools accelerate detection in stroke, oncology, and gastrointestinal imaging. Predictive analytics and connected devices — such as remote ECGs, glucose monitors, and post-op trackers — help us detect early signs of deterioration. These tools are already delivering measurable improvements in patient outcomes and operational efficiency,” Reddy said.
 
Aster, on the other hand, has piloted AI solutions in collaboration with both industry and academic partners. This has included experiments in radiology with Quer.ai, Carpal.ai, Biocliq, and Annalise, neurology with IISc, pulmonology with L&T, and cardiac risk assessment with Lupin. It already has a dedicated subsidiary driving digital transformation with AI at its core, called Aster Digital Health.
 
“These pilots were conducted to explore how AI could reduce diagnostic errors, improve efficiency, and generate predictive insights for earlier intervention. This experimentation is guiding our next phase, where we aim to integrate proven capabilities into an enterprise data lake, paving the way for advanced analytics and personalised treatment pathways at scale,” said Harsha Rajaram, chief executive officer, Aster Digital Health.
 
The industry, at the same time, is welcoming regulatory frameworks that promote safe, equitable, and ethical AI adoption across the sector.
  “When AI saves every doctor two to three hours a day on paperwork, that is not just efficiency — it is more capacity created to take care of patients. Early detection systems prevent costly escalations and readmissions. Antibiotic stewardship curbs unnecessary and expensive overuse. Our operational dashboards optimise beds, ICUs, and supply chains across the network," Reddy added. These steps have lowered Apollo's costs while improving patient outcomes and experience.
 
“Aster's AI pilots in radiology and neurology are already reducing turnaround times significantly. For example, AI-assisted chest X-ray tools have shown over 99 per cent accuracy in large pilots, enabling radiologists to validate reports faster. Similarly, predictive algorithms in cardiac and neuro care are supporting earlier and more precise interventions,” said Rajaram.
 
Diagnostic firms too are taking AI seriously. Dr Kirti Chadha, chief scientific and innovation officer, Metropolis Healthcare said, “At Metropolis, AI is not a pilot initiative, it is deeply embedded into the very backbone of our diagnostics. We are applying it across oncology, genetics, allergy diagnostics, and high-volume routine tests to enhance speed, accuracy, and consistency.”
 
Their AI-verified expert opinion for prostate biopsy supports pathologists in prioritising critical cancer cases with greater confidence, while their AI-powered karyotyping platform accelerates the interpretation of complex chromosomal patterns, reducing turnaround time by nearly 50 per cent, compared to manual methods. 
 
AI-driven workflows in labs cut down turnaround times across high-volume routine tests. On the operational side, AI-driven workflows, inventory, and reporting systems have enhanced productivity per pathologist and reduced routine errors. This has improved quality while also optimising costs, resulting in faster patient turnaround and stronger clinician confidence.
 
“We are also setting new benchmarks, with studies showing up to 90 per cent faster diagnosis times and an 80 per cent reduction in discordance among pathologists,” Chadha said, adding that they are also among the first in India to adopt AI-assisted allergy testing.
 
“At a population health level, our proprietary AI-based TB detection algorithm is transforming how resistance trends are tracked nationwide, making diagnostics more impactful for public health management,” Chadha said.
 
The CII-EY report highlighted that 60 per cent of hospitals are directing investments towards IT capability building, 50 per cent towards business intelligence tools and data lakes, and a significant share into AI-led use cases such as clinical documentation (72 per cent), decision support systems (64 per cent), and imaging (60 per cent).
 
Looking ahead, AI will increasingly play the role of a co-pilot in healthcare, predicting disease risks, flagging anomalies invisible to the human eye, and personalising care pathways, Chadha said. However, algorithms must be validated on Indian population data, not just western cohorts. 
Leading the way
  • Hospitals across country planning to raise IT innovation spending by 20–25%  over next 2-3 years
  • Apollo Hospitals and Aster implementing tech initiatives like LLMs for clinical decision support
  • Emergency incidents reduced by up to 80%, claims Apollo 
  • Aster dedicated subsidiary driving digital transformation with AI at core
  • Aster’s AI pilots in radiology and neurology reducing turnaround times significantly