AI-Powered Pharma Marketing: Key Trends, Common Challenges & Strategic Opportunities

No matter where you browse, you are sure to come across discussions about AI and its latest advancements. I too wrote a couple of articles and posts about artificial intelligence, focusing on how it impacts the pharmaceutical industry.

Moreover, yesterday, Manuel Mitola, MBA and I hosted an engaging session on AI. You can watch the recording of the webinar here: "Future-Proof Your Marketing with AI"

Inspired by this webinar, in today's piece, I want to take a closer look into the practical benefits and strategic opportunities of AI in pharma, as I not only see a great potential of this technology, but also already know what it can do for pharma marketing processes, based on hands-on experiences. Let's dive in.

Evolution of AI in Pharma Marketing

At first, AI found its home in the labs. Around 2012, we saw a boom in startups using AI for drug discovery and development. More than 80% of the AI-powered new pharma startups in the BiopharmaTrend database popped up around this time or later. AI was a game-changer in R&D, speeding up how we find new drugs, making clinical trials smarter, and getting better at predicting how well drugs would work and how safe they'd be.

As AI demonstrated its value in R&D, the pharmaceutical industry began to explore its potential in other areas. Marketing emerged as a natural next step, given the industry's long-standing reliance on data-driven strategies.

Use Сases for AI in Pharmaceutical Marketing

When it comes to marketing, many pharmaceutical companies have only scratched the surface of what AI can do. Statista confirms that mere 2% of pharma and healthcare companies adopted AI technologies for sales and marketing efforts. There are a lot of possible reasons why the adoption is so low: regulatory challenges, resistance to change, lack of skilled talent, data quality and integration issues, and so on. But let me concentrate on one of them for a moment – limited understanding of AI capabilities in marketing. I want to paint a clear picture on where exactly you can apply AI and what it'll bring.

Organize your data and search smarter

Pharma companies manage vast amounts of data and content, often struggling to efficiently reuse previously approved materials. AI offers a solution by auto-tagging content, creating detailed metadata, suggesting research-based updates, and simplifying version control. For one of our clients, these AI features reduced manual tagging by 60% and increased content reuse rates.

AI technology also reshapes content searches. It understands context, intent, and user preferences while processing various media types and interpreting natural language queries. This makes finding specific content within your organization as easy as asking a knowledgeable colleague.

Expedite MLR process

In 2022, U.S. companies lost a whopping $9.8 billion due to slow MLR reviews that kept marketing campaigns behind closed doors longer than they should've, especially when launching new drugs. That's what slow medical legal and regulatory review can do for you, unfortunately. MLR acceleration engines powered by AI can check everything against the rules, from text to audio. They can even guess how likely your content is to get approved and give you tips to make it compliant before you send it out for an official review.

Personalize and streamline content creation

Traditional methods can't keep up with the demand of modern pharma marketing. That's because now we use multiple channels to reach our audiences, and we're moving away from basic messages and toward personalized communication (at least that's the hope). Turning to generative AI is a way to resolve our growing needs.

Gen AI can quickly produce various marketing materials tailored to specific needs, from texts and images to videos and voiceovers. These flexible large language models adapt well to pharmaceutical tasks, excelling at creating multilingual promotional materials and assembling content modules for fast, compliant marketing.

Generative AI truly shines in personalization and can help you monitor HCPs' interests and interactions live. Using these insights, you can tailor your web pages and rep-triggered emails even within strict regulatory frameworks. What's also important is that this user behavior data is then fed to your CRM system, hence, helping your sales force efficiency.

Strategic Opportunities for AI Pharma Marketing

MLR acceleration, gen AI tools, content tagging, and organization – are truly amazing capabilities of AI for content marketers but let us take a look at the big picture. How can AI boost your competitive advantage, help you anticipate market shifts, and allow you to deliver value to your audience across every touchpoint of the customer journey?

Getting to know your customers (really know them)

First up, customer insights. AI is taking our data to a whole new level. We're talking about analyzing massive amounts of data on healthcare professionals' prescribing habits, patient behaviors, and treatment outcomes. What's more, AI algorithms can identify complex patterns in customer data, leading to a more nuanced and accurate market segmentation. This means we can target our campaigns with laser precision, making sure we're reaching the right people with the right message at exactly the right time.

Hiccupless launches

Product launches are the most critical and stressful periods for life sciences companies, and a successful launch takes a whole lot of strategic planning, coordination, and on-the-fly adaptability. AI can help you forecast the product's success by analyzing market trends and historical data, which you can then leverage for more informed decision-making. What healthcare marketers will certainly appreciate, is that AI helps with information distribution: pinpoints relevant audiences, identifies key opinion leaders in the niche, and suggests the most fitting communication channels.

Always-on analytics

AI tools can monitor social media and other digital channels in real time, tracking conversations around our products and healthcare topics. This means we can jump into relevant discussions as they're happening, fostering genuine two-way communication with our audience.

Marketing automation

Technology taking care of repetitive tasks while we focus on the bigger picture is real, we can do that right now. From scheduling campaigns to managing customer interactions, AI is making workflows smoother, freeing up people to take on strategic initiatives.

Mastering the omnichannel game

AI solutions can analyze data across all our digital channels, helping us create a seamless, integrated journeys for our customers. No more disjointed campaigns – we're talking about a cohesive strategy that meets our audience wherever they are.

What are the Key Trends & Common Challenges?

I recently did a poll asking you all about the most common AI mistakes that pharma companies make, and "overestimating AI" came out on top.

This brings me to a potential key trend – I think we'll start having more realistic expectations about this technology. For instance, the business world's perception of generative AI has evolved from initial hype to a more nuanced understanding. Real-world AI integration often differs from popular perception. Rather than standalone tools like ChatGPT, the most impactful applications are often integrated into existing services, enhancing rather than replacing current tools (e.g. Photoshop's "generative fill").

Insufficient staff training took "the silver", and low AI literacy may actually not be the issue here. As Benjamin Post thoughtfully reasoned in the comments, it's more about motivational and cultural shift. And I agree. Another key trend I see with AI is its democratization. It's increasingly more accessible and user-friendly, allowing people to learn how to work with it relatively fast. Employees may be hesitant to embrace AI due to fears of job displacement or skepticism about its effectiveness, and that's valid. Company leaders must do their best to help their people transition to new technology and encourage them by openly discussing how it will benefit them.

The third challenge, poor data quality, brings me to my last key trend prediction – data scientists and analysts will be in high demand to help pharmaceutical companies bolster their data infrastructure.

AI in healthcare marketing excels at analyzing vast data sets, revealing hidden trends and making accurate predictions. However, without high-quality, integrated data, it's not effective. Many organizations struggle with fragmented data and poor tracking, hindering true omnichannel marketing. If you want to unleash AI's full potential, and I think you do, make sure your customer data is accurate, collect information directly from your customers, and track how your marketing efforts work across all channels.