The AI tipping point in pharma marketing: balancing technology and trust

Taking a closer look at the opportunities and challenges AI offers pharma marketers

By Trevor Lambert

If 2024 saw an unparalleled acceleration in the wider public’s awareness of AI, then 2025 will be the year when its practical application becomes mainstream.

According to a 2024 Elsevier report, more than 80% of pharma marketing and medical affairs teams are either already working with AI or actively considering using AI technology.  It is perhaps unsurprising to see pharma ahead of the curve, given its track record of early adoption of technologies such as wearable devices, telemetry and interconnected electronic records. (Before we become too complacent, it is worth noting that the term ‘early adopter’ is relative here. The first neural network mathematical model was developed in 1943, and the birthplace of AI is widely considered to be the Dartmouth Conference held in 1956.)

The possibilities are endless, particularly in analytics and repetitive administrative tasks that must be completed quickly, consistently and accurately.

AI can also be used for more creative work. Content generation and optimisation, for example, can be easily automated, from copy and images to audio and video. This enables companies to maintain consistency, relevance and speed to market across channels. With the right AI, repurposing content and achieving regulatory approval becomes significantly quicker and less resource intensive.

AI is not an infallible replacement for the human worker. At Kanga, we believe that when used well and responsibly, AI can be a powerful tool in the modern pharma marketer’s arsenal. One of the most consistent pieces of advice in the often-inconsistent field of AI speculation is:

‘You will not be replaced by AI. But you will be replaced by someone who knows how to use AI.’

‘AI’s possibilities are endless, particularly in analytics and repetitive administrative tasks that must be completed quickly, consistently and accurately’

Consequently, organisations and individuals who don’t want to get left behind embrace AI with admirable but often unfocused enthusiasm. This can mean losing the caution necessary to use AI compliantly in a highly regulated industry such as pharma.

Here, we examine the opportunities AI offers pharmaceutical marketers and discuss ways to address some of the challenges.

The use of AI in pharma marketing is limited more by imagination than the technology itself – and the technology will only improve. Some of the more impactful applications we have seen include:

• Personalised marketing campaigns: AI analyses vast amounts of customer data to create tailored marketing strategies. By understanding individual patient needs and preferences, pharma companies can deliver customised content, enhancing engagement and improving treatment adherence
• Avatar-delivered presentations: computer-generated video training or presentation content delivered by avatars, with the built-in capability to switch languages at the click of a button, and update content as easily as editing a Word document
• Chatbots for customer engagement: AI-driven chatbots provide real-time support and information to patients and healthcare professionals. These chatbots can answer queries, offer controlled medical advice and guide users through medication use, improving customer experience
• Predictive analytics for market trends: AI enables pharmaceutical companies to analyse market data and predict drug demand and market shifts. This allows for proactive adjustments in marketing strategies, ensuring companies remain competitive and responsive to market dynamics
• Identification of rare disease patients: AI algorithms analyse electronic health records and claims data to identify patients with rare diseases more efficiently. This capability allows for targeted marketing and educational initiatives, ensuring that information reaches those who need it most
• Social media monitoring: to track real-time patient feedback, allowing companies to address concerns, respond promptly and tailor content to build stronger relationships.

1. Data privacy and compliance
AI relies on data, but the risks are high in pharma, where sensitive patient and product information is at stake. Mishandling data can lead to legal violations, reputational damage and erosion of public trust.

Existing regulations such as GDPR require organisations to implement data protection by design. More recent legislation, such as the EU’s Artificial Intelligence Act, is being introduced in a phased approach with high-risk applications, such as pharma, prioritised and subject to the most stringent requirements.

We can soon expect a flurry of healthcare-related AI guidelines and regulations, with the MHRA, BHBIA, the European Medicines Agency, the World Health Organization and others all working on new or updated compliance documentation.

Solution:

• Use closed, licence-based AI tools to prevent proprietary data from entering open ecosystems
• Follow best practice in data protection, such as GDPR, and stay updated with new regulations like the EU’s Artificial Intelligence Act
• Implement robust internal AI policies, training and checklists to ensure responsible and confidential use of AI.

• Use diverse and representative data sets to reduce bias
• Conduct routine audits to detect and correct bias in algorithms
• Promote transparency and ethical standards in AI systems.

• Interrogate AI outputs to understand the reasoning and data sources behind decisions
• Don’t always accept the first answer and demand reasoning and data sources
• Disclose when and how AI is used to build trust and avoid misunderstandings
• Ensure human oversight to validate outputs and provide necessary context.

Alan Turing’s 1950 test asked if a machine could mimic human behaviour convincingly enough to fool its audience. Today, pharma marketers face a variation of this question: can audiences distinguish between AI-generated and human-crafted content?

While AI excels in efficiency and consistency, it often lacks the nuance and empathy to create genuine connections. For example, Kanga Health uses avatar-based video for multilingual training, offering rapid translation and localisation. However, even advanced avatars can fall into the ‘uncanny valley’, where their delivery feels almost human, but not quite human enough.

AI’s predictable and reliable delivery is invaluable for tasks like regulatory and compliance training, where word-perfect repetition of material in an interactive, personalised and yet predictable way is highly valued. Yet, human input remains critical when emotional depth, cultural sensitivity and humanity are essential.

At Kanga Health, we blend AI-led and human-led approaches, allowing clients to harness the strengths of each. We always disclose when AI is used and provide transparent pricing for both options. This ensures that content doesn’t just inform – it connects.

The future of pharma marketing isn’t about choosing between AI and human expertise, but integrating the two.

Companies that embrace this hybrid approach will lead the charge, ensuring both innovation and accountability.

Trevor Lambert is a Senior Strategist and AI Consultant at Kanga Health