AI and Asia: What Pharma Marketers Need to Hear Right Now 

In today’s Pharma Talks episode, Nataliya Andreychuk welcomes two fascinating guests from a company specializing in digital systems, diverse languages, different regulatory realities, and the challenges of Asian pharma markets.

Gwenael Meneux is an expert who spent 15 years in pharma, including six years in commercial pharma in Asia, before joining the agency side just over a year ago.

Bruno Senuci, co-CEO and co-founder, has lived in Asia for over 30 years, including 18 years in Vietnam where he lives today, based in Saigon. His focus is on operations and innovation, complementing Gwenael’s more strategic and pharma-facing role.

AI in Pharma: What Is Happening on the Ground

Artificial intelligence is becoming omnipresent. Teams use it across drafting, adaptation, translation, content repurposing, and MLR readiness. But in pharma marketing, speed alone is not the goal. “Mostly accurate” is not enough in a highly regulated industry like life sciences, where even small errors can carry serious consequences. Bruno puts it:

The question isn’t whether AI can create content, it clearly can. The question is whether that content can be trusted in a heavily regulated environment.

AI cannot guarantee scientific accuracy. It neither carry all the regulatory nuance that is needed, nor always have the right context or tone for the right market.

The most common mistake is treating AI as a shortcut. It is rather a multiplier of whatever process already exists. If the process is weak, AI scales inconsistency or low-quality output. Without human oversight, quality control, compliance control, and risk management all suffer.

AI’s Place in Localization

AI can help translate, but it does not ensure cultural relevance or local sensitivity. Humans remain accountable for trust, especially in markets with constraints around channels, operating models, and systems.

We are entering a very interesting phase of AI adoption, Gwenael says, where with current LLMs there are almost no limits in certain fields. Drug development is a striking example. AI is accelerating timelines from 8 to 10 years down to 2 to 3 years, which he calls a caliber change.

But in content production the limits show clearly when there is no human monitoring or touch. For Gwenael, the benefit of AI is in summarizing, aggregating, and consolidating data, a major help for medical affairs and marketing.

But when it comes to creating emotion and creativity, adding something meaningful to clinical data still requires human input. He notes that world models are evolving but for now the limits are palpable.

How High-Performing Teams Are Approaching MLR

You can now generate content at the lightning speed, but at the end of the day it must be validated by MLR review. This validation is still a human review. AI can help and ease decisions, but it does not remove that step.

The winners of the AI race will be companies that build the intersection of human and AI, creating AI-native services where human teams collaborate with AI agents as part of their workflow.

Every element of the content supply chain, either it is localization or regulatory work that differs market to market, requires preparation, curation of knowledge bases, and human accountability at each stage.

Nataliya references a conversation from the Reuters US Pharma Forum, where marketers were imagining a future where they could speak to an AI agent and see a finished campaign appear in Salesforce Marketing Cloud. But she also stresses that this black box vision is the wrong approach. You cannot blindly trust the model when you don’t know how it arrives at its decisions.

Why Asia Cannot Be Treated as One Market

Asia is huge, concentrating more than half of the global population, yet accounting for only around 20% of global healthcare spending. The untapped opportunity is significant and the demand is growing, but the diversity should be taken into account.

The medical needs across the region are not the same. Gwenael points out that within the same geographic block, you have some of the oldest populations in the world, like Japan, Hong Kong, Taiwan, sitting alongside some of the youngest, such as the Philippines, Cambodia, and India.

Some markets should almost be treated like Europe, with high cancer prevalence driven by aging populations. Others, particularly across Southeast Asia, still carry a heavy burden of communicable and infectious diseases, like dengue, tuberculosis, respiratory disease linked to air quality. You cannot cluster these markets the same way, Gwenael says. You have to be more sophisticated in how you address them.

He also highlights the very different health and reimbursement systems. China has a near-universal insurance scheme covering close to 100% of the population, including drugs listed on a national scheme. India, by contrast, has a highly fragmented system with significant out-of-pocket costs. Access to innovative medicines differs enormously as a result, and this shapes everything, from your targeting and messaging to your entire communication approach.

Launch timing is another dimension. Singapore, for example, has early access programs that can make it faster to market than some European countries for certain innovations. Other markets in the region may have access to the same oncology or rare disease drugs three to four years later. A single aligned global launch plan won’t cut it.

Bruno also takes the channel fragmentation. Vietnam has its own platforms, China has its own internet isolated from the rest of the world, and Thailand and Japan have distinctive online behaviours. The campaign logic built around Western channels cannot be replicated, and tactics must be adapted market by market.

The fragmentation, he explains, goes deeper than channels. Brands may be managed directly or via distributors, while marketing standards, execution models, and tech stacks vary widely. DAM platforms, CRMs, and approval systems, whether local, global, or in-house, often differ even within the same company, including between HCP and healthcare communication teams. The result is silos, which makes integrated execution much harder than it appears on paper.

Data regulation is fragmented too. Europe has the AI Act and GDPR governing most countries, but in Asia each country has its own rules. And layered on top of everything, Asian markets generally operate with more limited budgets than Europe or the US. Teams are asked to adapt across more fragmented ecosystems with fewer resources. Bruno says his team has become an expert at doing a lot with a lot less.

Making Global-to-Local Work: Practical Recommendations

Bruno and Gwenael’s approaches differ to some extent and reflect their unique backgrounds.

Bruno’s approach

Teams need to focus on reducing friction across the full workflow. His practical framework starts with an audit of local market readiness: technology, talent, regulatory stage, execution capability, and budget. From there, build agile localization pipelines instead of one-size-fits-all content factories, which he believes have largely failed in Asia.

Content needs to be easier to adapt, validate, and approve. AI can reduce rework and make drafts more review-ready, but this also requires changes to approval workflows, including tiered approval processes.

Roadmaps need to be market-specific. Leave tactics and execution details to local teams. They know how to do it and do not need global guidance for that level of detail.

Technology stacks that exist at HQ level often do not exist locally, or if they are implemented, they are underutilized because local teams lack the budget, headcount, or skills to integrate them properly. Invest in local digital talent, people who understand how local platforms work and who are needed to adapt campaigns meaningfully.

Finally, do not wait for the perfect model. Pilot, learn fast, sometimes fail fast, and build iteratively. In Asia, that approach works better than a complex global model. What works is something realistic, flexible, and pragmatic, close enough to the market to spot opportunities others will miss.

Gwenael’s approach

Gwenael brings a complementary set of lessons shaped by years inside global pharma, particularly in China. The first trap he warns against, drawing from his China experience, is assuming that what works in China works everywhere in Asia. You need the de-averaged view.

However, some clusters that are not geographically obvious can work together, like South Korea, Taiwan, Hong Kong, and Singapore share enough commonality to operate together even though they are spread across the map.

On content factory models, Gwenael says he has seen the highly centralized global models up close and there is a high correlation between distance from the global decision center and how poorly equipped a market is. He is a strong supporter of regional-scale content factory models with unified global templates to avoid duplication and maintain a consistent USP, clustering around ten markets rather than trying to govern a hundred.

His third recommendation is to leverage local expert communities, like HCPs, patient groups, whatever form they take locally. His observation from experience is that global pharma affiliates tend to spend much of their medical budget bringing in global key opinion leaders (KOLs) or sending local KOLs to international congresses.

With the benefit of hindsight, he would redirect part of that budget to uplifting local experts and raising their voices, because those local digital opinion leaders (DOLs) are the ones who will change practice at the local level. An Australian or US KOL may be scientifically authoritative but will have far less impact than a trusted local voice when it comes to shifting behaviour in that community.

Talent and Test-and-Learn

Even large pharma companies outsource to distributors and vendors but invest in a strong local expert team rather than trying to manage everything centrally. Companies that have succeeded in Asia, Gwenael says from his China years, were the ones full of local talent.

Bruno highlights the test-and-learn point as perhaps the most important practice for Asia, even more so than in European markets. He recalls arriving in China wanting everything to be perfectly structured, and it simply did not work. Better to go in slightly imperfect and iterate or improve, than to pursue perfection before acting.

Hot or Not: Rapid-Fire Verdicts

The episode closes with a quick-fire round where Natalia offers statements and the guests respond with hot or not.

AI will solve the localization problem in pharma — Bruno declines to give a clean yes or no:

It will help. It’s not a magic bullet and the answer is not entirely no. It’s in between.

If your content works for Europe, it will work for Asia with a good translation — Gwenael:

Absolutely not. Culture is even more important than language. Understanding how emotion works in Asia, in South Asia versus North Asia, is more important than translation. Translation can be easy with AI. But not. Absolutely not.

Human oversight of AI in pharma is non-negotiable — Bruno:

Very hot on that principle. Humans trust humans. We are not there yet at trusting machines blindly.

Digital channel fragmentation in Asia is a competitive advantage for companies that learn to navigate it — Gwenael:

100% hot. It requires a lot of effort and humility being surrounded by the right local experts, and also having the humility to recognise when it is not the right time to enter a particular market.

Global pharma teams understand aging markets well enough to navigate and lead digital strategy from headquarters — Bruno: “Not. Absolutely not.” He adds that global teams work from a different tech stack and different principles from the start, skewed towards a Western ecosystem. The fragmentation in Asia requires adaptation that headquarters is simply not equipped to lead.

The biggest barrier to AI adoption in pharma is technology — Gwenael:

Not. It can be a technology barrier in some cases, but the main one is human adoption and usage. It is a wide change management challenge. You have to convince users of the benefits they will get. The main current barrier is about usage and human adoption.

Final Words

Think of AI as a multiplier rather than not a perfecting tool. It amplifies what already exists in your content and processes. Humans, on the other hand, provide the judgment needed to keep things up to standards in highly regulated industries like pharma.

When it comes to Asia, it should not be treated as a single market. The key is to de-average and bring in local expertise. Investing in native talent will help you create the competitive edge. The region also rewards pragmatism and fast learning over a “perfect” upfront plan.

Found this useful? Follow Nataliya Andreychuk, Bruno Senuci, and Gwenael Meneux on LinkedIn. They share regular insights on pharma marketing, AI, and navigating the Asian market.

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