Question 1

AI is moving faster than anyone can track. How do I stay current without chasing every announcement?

Accepted Answer

You stop reading and start sitting with people who have shipped. AI for Pharma is a recurring room: three to four editions a year where commercial leaders and the engineers building for them work through what is actually in production, what failed, and what is still hype. Between editions the conversation continues in a private group, so a question you have on a Tuesday gets answered by someone who solved it, not by a newsletter. The point is signal from practitioners, not coverage of every model release.

Question 2

How do I adopt AI inside a large pharma company, not just run another pilot that goes nowhere?

Accepted Answer

Most stalled pilots fail for the same reasons: no clear owner, no clean data underneath, and a model chosen before a workflow was named. The editions are built around exactly that. A session opens with a commercial leader naming a workflow they are trying to improve, paired with an engineer who has built for it, so you leave with how a peer moved something from proof of concept into the field, not a vendor pitch. You also meet the CIO and data leaders who had to make it work, on the same day as the commercial team.

Question 3

Build or buy? I get a different answer from everyone I ask.

Accepted Answer

Because the honest answer depends on your data foundations and how core the workflow is, and most people answering have only done one side. The room has both: teams who built in-house and teams who bought, discussing where each paid off and where it did not. We do not sell you a conclusion. You leave able to reason about your own case with evidence from people who have shipped both ways.

Question 4

Our commercial data is a mess. SMSRC, IQVIA, and our own sales numbers never agree. Where do I even start?

Accepted Answer

Here, usually. Getting your data onto one footing is the most common real starting point, and it is a working session in its own right: bringing your sales and prescription numbers onto one shared map of your territories, deciding which source you trust for which decision, and what it means when they disagree. You will sit with people who have done this at peer companies and can tell you what is worth fixing first.

Question 5

My field force is skeptical of AI. How are other companies actually getting MRs to use it?

Accepted Answer

Adoption is a people problem before it is a model problem, and it is discussed here as candidly as the technology. Expect specifics: how a call plan re-ranked from Rx trend and stock-out signal earns a Territory Manager's trust, what keeps a tool in use after the novelty fades, and where rollouts quietly died. Failures are on the record here, which is the part most conferences leave out.

Question 6

How do I measure ROI on AI in sales and marketing when attribution is already hard?

Accepted Answer

By being honest about what is measurable and what is not. A working session covers attribution directly: how a Brand Manager ties a change in sales back to a specific intervention, with and without the IQVIA market data, and where the measurement breaks down. You leave with how peers actually report value to their boards, not a vendor's ROI slide.

Question 7

Agents, copilots, foundation models. What is real for pharma commercial today, and what is still hype?

Accepted Answer

The fastest way to tell is to watch a real system run against real data, which is what the live demonstrations are: AI applied to an actual commercial problem, not slideware, with the failures shown. Pair that with senior people from foundation-model companies, cloud platforms, and pharma-focused startups in the same room, and you can calibrate what is shippable now against what is still a roadmap promise.

Question 8

Who is actually in the room?

Accepted Answer

From pharma: Chief Commercial Officers, VPs of Sales and Marketing, National and Regional Sales Managers, Brand Managers, Heads of Sales Excellence and Commercial Analytics, and the CIOs and data leaders behind their systems, all from operating pharma companies in India. From technology: senior leaders at foundation-model companies, cloud platforms, data vendors, and pharma-focused AI startups. Both sides go through the same application review and sit at the same table. We invite by role and contribution, not by logo.

Question 9

What actually happens at an edition?

Accepted Answer

Four working sessions across sales-force effectiveness, brand and marketing analytics, commercial data foundations, and forecasting, two live demonstrations against real data, and a curated dinner. There is no main stage, no sponsor hall, and no general ticket. It is conversation-shaped, measured by who is in the room and what they argue about, not by attendee count.

Question 10

Who convenes it, and is it just a vehicle to sell me something?

Accepted Answer

It is convened by the team behind PharmaOS, a Super AI product that lets pharma companies query their own commercial data in plain language. The consortium grew out of conversations that team was already having with commercial leaders and CIOs across Indian pharma. It is editorially independent of the product: PharmaOS is one demonstration among many at any edition, and the room includes its competitors. The intent is an honest senior conversation, not a sales funnel.

Question 11

Has AI for Pharma run before, and when is the first edition?

Accepted Answer

Not yet. The consortium is in its founding period and the first edition has not been held. Applications for the founding edition are open and reviewed weekly. The date and an Indian-city venue are being finalised and will go to invited applicants first, with enough notice to plan around. Future editions are intended to alternate between Indian cities, three to four times a year.

Question 12

I am a working practitioner, not yet at director level. Can I still be involved?

Accepted Answer

The application is reserved for senior decision-makers because the format depends on a small, high-trust room. If you are a practitioner (a regional sales manager, a brand executive, a commercial analyst, or an engineer building for commercial teams) write to room@aiforpharma.ai and we will route it. Several adjacent formats for practitioners are being considered, and we will publish them as they exist.

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