pharma · 8 use cases
Top agentic AI use cases for Pharma and Healthcare in H2 2026
Since 2025, AI answers sit above the links patients click, Google’s AI Mode has reached India in several Indian languages, the FDA has stepped up action on drug promotion and India’s DPDP Rules have begun to phase in. These eight workflows respond to those changes.
What should pharma and healthcare leaders put agentic AI to work on in H2 2026?In H2 2026, pharma and healthcare teams should use agentic AI to check how AI answers describe their hospitals and brands, run multilingual booking and report conversations, route adverse event mentions to pharmacovigilance, sweep live promotion for compliance, and rebuild health advertising on consented, non-sensitive signals. People approve every rule and customer-facing change.
AI answer accuracy checks for your hospitals, doctors and brands
Patients now meet AI Overviews and AI Mode answers, including in Indian languages, before they reach your site, and Pew Research Center found Google users clicked a traditional result in 8% of visits with an AI summary against 15% without one. DRIS runs a fixed set of patient questions through the main answer engines each month, finds where your hospitals or brands are missing or misdescribed, and fixes the sources those answers draw on.
On the first Monday of the month, DRIS runs the tracked questions through Google AI Overviews and AI Mode, ChatGPT and Perplexity, in English and regional languages. It records cited sources and where the hospital’s doctors are missing or wrong, then traces each error to an outdated directory listing or old press page. The digital head and medical affairs approve the corrections. DRIS publishes them and re-runs the questions, so AI answer share is reported with evidence.
the workflow, in one room
- TriggerOn the first Monday of each month, DRIS runs the tracked question set, such as the best hospital for bypass surgery in Pune, in English and the regional languages you serve.
- It records which sources each answer cites and where your doctors, centres or approved product information appear, are missing or are wrong.
- It traces each error to its origin, such as an outdated directory listing, an old press page or a third-party article.
- It drafts corrections for your own pages and correction requests for directories and listings.
- Approved by Digital head and Medical affairsThe digital head and medical affairs approve the corrections and any new answer content.
- DRIS publishes the approved changes and re-runs the questions to confirm the answers changed.
Guardrail. Corrections state facts and approved information only, and never seed third-party sites with undisclosed promotion or prescription-drug claims aimed at the public.
Multilingual WhatsApp and voice agents for bookings and reports
Front desks spend the day on the same questions: is the doctor in, what does the health check cost, is my report ready. Convexa answers on WhatsApp and phone in the patient’s language, books and reschedules, shares report status after identity checks, and hands anything clinical or urgent to a person.
A patient messages the hospital’s WhatsApp number in Marathi, asking to move a cardiology appointment. Convexa verifies identity against the appointment record, offers open slots, books one and updates the hospital system. A mention of chest pain would instead bring the emergency number and a transfer to the duty nurse. Behind it sit scripts, a red-flag list and hand-off rules that the patient experience lead approves before launch. The front desk spends less time on repeat questions.
the workflow, in one room
- TriggerA patient messages the hospital’s WhatsApp number in Marathi asking to move a cardiology appointment.
- Convexa verifies identity against the appointment record and offers open slots from the scheduling system.
- It books the new slot, sends a confirmation and updates the hospital system.
- If the patient mentions chest pain or another red-flag symptom, Convexa gives the emergency number and transfers to the duty nurse at once.
- Approved by Patient experience leadThe patient experience lead approves the conversation scripts, the red-flag list and the hand-off rules before launch and after every change.
- Convexa reports unresolved conversations and hand-off reasons to the patient experience team each week.
Guardrail. Convexa never diagnoses, prescribes or gives medical advice, because India’s Telemedicine Practice Guidelines, 2020 reserve consultations for registered medical practitioners.
Adverse event capture from chat, email and social into safety
Patients and doctors mention side effects in chats, emails, social comments and calls, and commercial channels are rarely built to catch them. Convexa flags every possible adverse event in owned channels, collects the minimum details while the person is still engaged, and hands the case to the safety team with the clock already started.
A caregiver writes on the consumer care chat that a parent developed a rash after starting a medicine. Convexa recognises a possible adverse event and asks the standard intake questions: product, reaction, onset and how to reach the reporter. It opens a case in the safety intake queue with the transcript, time-stamped from the first mention. The pharmacovigilance officer decides whether it is reportable. More cases arrive with complete minimum information, and none wait in a commercial inbox.
the workflow, in one room
- TriggerA caregiver writes on the brand’s consumer care chat that a parent developed a rash after starting a medicine.
- Convexa recognises a possible adverse event and asks the standard intake questions: the product, the reaction, when it started and how to reach the reporter.
- It creates a case with the full transcript in the safety intake queue, time-stamped from the first mention.
- Approved by Pharmacovigilance officerThe pharmacovigilance officer reviews the case, decides whether it is reportable and owns all follow-up with the reporter.
- Convexa tells the person their report has gone to the safety team and records the hand-off.
- Each month it reports adverse event mentions by channel so the safety team can check nothing was missed.
Guardrail. The agent captures and routes but never assesses causality or advises on the medicine; reporting decisions stay with the marketing authorisation holder’s safety team under CDSCO’s pharmacovigilance guidance.
free guide and deckEvery pharma use case on these pages, with its workflow drawn, to share with your team.Get it free ↓Live promotional asset sweeps for risk information and old claims
In September 2025 the FDA said it was sending thousands of letters to drug companies and roughly 100 cease-and-desist letters over misleading ads, and that it was already using AI to monitor promotion. Brand teams need to know what is live today. CREA and the Pharma Strategist sweep websites, social posts, ads and influencer content for missing risk information, expired approvals and claims that drifted from the approved version.
Every fortnight the sweep begins again. CREA crawls the brand’s websites, social channels, live ads and partner influencer posts, matching each asset to its approval record in Veeva PromoMats and flagging any expired approval or missing code. The Pharma Strategist checks live claims against the approved version and looks for risk information hidden behind a link. CREA ranks what to fix or pull. The regulatory lead approves each decision and, for once, knows exactly what is live today.
the workflow, in one room
- TriggerEvery fortnight, CREA crawls the brand’s websites, social channels, live ads and partner influencer posts.
- It matches each asset to its approval record and flags any with an expired approval or no approval code.
- The Pharma Strategist checks each live claim against the approved version and, for US assets, checks that risk information appears with the benefit claims rather than only behind a link.
- CREA produces a ranked list of assets to fix or pull, with the corrected approved text where one exists.
- Approved by Regulatory leadThe regulatory lead approves which assets are pulled, corrected or left live.
- CREA tracks each takedown until the asset is confirmed removed or replaced.
Guardrail. The sweep flags and proposes but never edits approved material; US promotion must be truthful and balanced under FDA rules, and Indian promotion must meet the Uniform Code for Pharmaceutical Marketing Practices, 2024.
Consent-aware audiences and measurement for health advertising
Meta began more proactive restrictions in September 2025 on custom audiences that suggest health conditions, and India’s DPDP Rules, 2025 phase in standalone, purpose-specific consent notices. NIA audits audiences, conversion events and consent records, then rebuilds targeting and measurement on signals that reveal nothing about anyone’s health.
When a restriction notice from Meta arrives, the ad accounts are reviewed. NIA lists every custom audience, lookalike, conversion event and tag, flagging anything that reveals a condition, such as a booking event on a diabetes clinic page. It checks each source against consent records, then proposes neutral event names and broad or contextual targeting. The marketing head and the data protection officer approve before anything changes. Measurement now rests on signals that reveal nothing about anyone’s health.
the workflow, in one room
- TriggerA quarterly audit or a restriction notice from Meta triggers a review of the ad accounts.
- NIA lists every custom audience, lookalike, conversion event and tag, and flags names, rules or URLs that reveal a condition, such as a booking event fired on a diabetes clinic page.
- It checks each audience source against consent records and the purpose stated in the consent notice.
- It proposes replacements: neutral event names, aggregated conversions and broad or contextual targeting.
- Approved by Marketing head and Data protection officerThe marketing head and the data protection officer approve the changes before any audience or tag is altered.
- NIA implements the approved changes and compares campaign performance before and after.
Guardrail. No audience, event or tag may reveal or infer a person’s health condition, and data is used only for the purpose consented to under the Digital Personal Data Protection Act, 2023 and its Rules.
OTC and pharmacy service listings ready for AI shopping agents
Google is adding agentic features to AI Mode, and its April 2026 policy update lets LegitScript-certified online pharmacies, once approved by Google, promote prescription drug services in India, though never the drugs. Consumer health brands and e-pharmacies need product and service data that shopping agents and answer engines read correctly. NIA keeps feeds, product pages and pharmacy service ads accurate and inside the rules.
An OTC pack size launches, and its price arrives from the ERP export. NIA updates the Google Merchant Center feed and product page with the approved name, pack, price, directions and warnings, and checks that no prescription-only product appears in anything targeting India. The regulatory and e-commerce leads approve the feed rules and product copy. NIA then watches disapprovals and how AI shopping answers describe the product, so product data accuracy in AI answers is checked, not assumed.
the workflow, in one room
- TriggerA new OTC pack size launches, or a price or stock change arrives from the ERP.
- NIA updates the Merchant Center feed and product page with the approved name, pack, price, directions and warnings.
- It checks that no prescription-only product appears in feeds, ads or landing pages targeting India.
- For certified pharmacies, it drafts service ads for prescription upload and delivery that name no drug.
- Approved by Regulatory lead and E-commerce leadThe regulatory and e-commerce leads approve the feed rules, product copy and service ads.
- NIA monitors disapprovals and how AI shopping answers describe the products, and fixes errors at the feed.
Guardrail. Prescription drugs are never promoted in ads or landing pages targeting India, only LegitScript-certified pharmacies run prescription service ads, and Schedule H and X medicines are dispensed only against a valid prescription.
Follow-up and preventive check reminders for consenting patients
Hospitals and diagnostics chains lose patients between visits: the post-discharge review never booked, the annual check that lapsed. LIPI drafts reminders from approved templates for patients who opted in, timed from the care plan, and replies go to Convexa or the front desk for rebooking.
A patient’s annual health check falls due. LIPI checks the consent record for WhatsApp reminders, then drafts a message from an approved template with the doctor’s name, the due date and a booking link, and no diagnosis. Before anything runs, the patient experience lead approves each template and the reminder schedule. SERA sends the reminder, and replies route to Convexa or the front desk. Lapsed checks no longer go unnoticed, and repeat health check bookings are tracked by department.
the workflow, in one room
- TriggerA discharge summary records a six-week follow-up review, or a patient’s annual health check falls due.
- LIPI checks the patient’s consent record for reminders on the chosen channel.
- It drafts the reminder from an approved template with the doctor’s name, the due date and a booking link, and no diagnosis in the text.
- Approved by Patient experience leadThe patient experience lead approves each template and the reminder schedule before it runs.
- SERA sends the reminders, and replies route to Convexa or the front desk for rebooking.
- LIPI reports booked follow-ups and opt-outs by department each month.
Guardrail. Reminders go only to patients who consented, carry no diagnosis in the message, never promote a medicine, and in the US stay within the HIPAA Privacy Rule’s limits on marketing.
International patient enquiries from facilitators and partners
Hospitals serving patients from the Gulf, Africa and South Asia receive enquiries through facilitators, partner clinics and direct messages, each with reports attached and an expectation of a fast estimate. CORA organises each enquiry, chases missing documents and routes a complete file to the right specialist, so the patient gets a timely, reviewed answer.
A partner facilitator emails a patient’s reports, asking for a cardiac surgery estimate. CORA confirms consent to share records, logs the enquiry and chases missing documents until the case file is complete. It routes the file to the rota specialist and drafts an estimate from the hospital tariff master. The treating specialist approves the medical opinion, and the international desk head approves the estimate. SERA sends both, and enquiry to estimate turnaround becomes something the desk manages.
the workflow, in one room
- TriggerA partner facilitator emails a patient’s reports and asks for a cardiac surgery estimate.
- CORA confirms the patient’s consent to share records, logs the enquiry and lists missing documents.
- It requests the missing items from the facilitator and assembles a complete case file.
- It routes the file to the specialist on the international desk rota and drafts an estimate from the approved package tariffs.
- Approved by Treating specialistThe treating specialist approves the medical opinion and the international desk head approves the estimate before anything is sent.
- SERA sends the approved opinion and estimate, tracks visa letter requests and logs the partner channel in the CRM.
Guardrail. No clinical opinion or outcome promise leaves without the treating specialist’s sign-off, records move only with recorded consent, and partner payments never become referral incentives for doctors.
Frequently asked questions
Why do AI answers matter more for healthcare in 2026?
Google brought AI Mode to India in 2025 and has since extended it to several Indian languages, so many patients read a summary before they see a link. Pew Research Center found Google users were less likely to click a result when an AI summary appeared. If the answer is wrong about your doctors, services or products, patients may never reach the page that is right.
What do the DPDP Rules mean for hospital and pharma marketing?
The Digital Personal Data Protection Rules, 2025 were notified in November 2025 and phase in over 18 months. They require a standalone consent notice that explains the specific purpose of collection, and PIB notes that some failures, such as not reporting a personal data breach, can attract penalties of up to ₹200 crore. Consent records, purpose limits and opt-outs need to be in place before agents act on patient data.
Can an AI agent talk to patients about medicines?
It can share approved product information, book appointments and route questions, but it does not give medical advice or promote prescription drugs to the public. Any mention of a side effect goes to the pharmacovigilance team, which owns the case and the reporting decision. Clinical questions go to a registered medical practitioner.
How do we start without adding risk?
Start with workflows that produce findings rather than messages: the AI answer audit and the live promotional asset sweep send nothing to patients or doctors. Automated first-pass checks ahead of medical, legal and regulatory review work the same way, because reviewers still approve every piece. Move to patient conversations once scripts, red-flag lists and hand-off rules have been approved and tested.
sources
- Pew Research Center: Google users are less likely to click on links when an AI summary appears in the results (2025)
- Google India Blog: Google Search, introducing AI Mode in India (2025)
- Google India Blog: Supercharging Search for India, new languages in AI Mode and Search Live (2025)
- Google: AI Mode in Google Search adds personalization, agentic features (2025)
- US FDA: FDA Launches Crackdown on Deceptive Drug Advertising (2025)
- PIB: Government notifies DPDP Rules to empower citizens and protect privacy (2025)
- PIB: DPDP Rules, 2025 notified, backgrounder (2025)
- Meta for Developers: Custom Audiences, Marketing API guide
- Google Ads: Update to Healthcare and Medicines Policy (April 2026)
- CDSCO: Pharmacovigilance Guidance Document for Marketing Authorization Holders, Version 2.0 (2024)
- McKinsey: Reimagining life science enterprises with agentic AI (2025)
free guide
18 AI agent use cases for Pharma & Healthcare
Every workflow on these pages as a designed guide and a presentation deck, ready to share with your team: a scene from the week, the workflow drawn with its approval gate, the systems it connects to and how to measure it. Light and dark editions, updated every month.
- Top 10 sales and marketing use cases for AI agents in Pharma and Healthcare
- Top agentic AI use cases for Pharma and Healthcare in H2 2026
- Who is in the room: your AI team for pharma and the people who approve
- The guardrails and the rules they come from, with sources
