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Written by Jordi Sánchez, Pharma Executive Manager at SDG Group.
Artificial Intelligence (AI) has played a key role in the pharmaceutical industry for years, transforming areas such as research, drug development, and commercial data management. However, 2025 is shaping up to be a turning point in this evolution thanks to the emergence of a new approach: Augmented Intelligence. This advancement not only expands the possibilities of traditional AI but also redefines the relationship between humans and machines, marking the beginning of a more collaborative and strategic era in the sector.
In this article, we explore what this new concept of Augmented Intelligence means, how it differs from traditional AI as we know it, and how it is transforming the pharmaceutical landscape.
A Change of Perspective: Augmented Intelligence vs. Traditional AI
Traditional AI automates tasks and processes data without human intervention, while Augmented Intelligence complements human judgment. It combines human intuition, experience, and empathy with the power of Artificial Intelligence.
The result is a tool that does not replace professionals, but rather amplifies their skills, enabling faster, more informed, and more effective decisions. The differences between Augmented AI and traditional AI can be observed in the following examples of projects where Artificial Intelligence is used:
|
Initiative |
Traditional AI Approach |
Augmented AI Approach |
|
Chatbot for HCPs |
A completely autonomous chatbot that responds to medical questions without human intervention. |
A virtual assistant that suggests responses to the sales team, allowing for personalization prior to sending them. |
|
Predicting Medication Demand |
A Machine Learning model that automatically adjusts supply based on historical data and trends. |
A forecasting tool that generates estimates using AI for supply chain teams to review and adjust with additional insights. |
|
Detection of Adverse Effects |
A system that analyzes patient reports and generates alerts automatically without the need for human validation. |
A platform that prioritizes the most relevant reports and suggests possible risks while requiring validation from experts prior to producing official alerts. |
|
Commercial Recommendations for Sales Reps |
An algorithm that automatically decides the best commercial action without the possibility for sales team intervention. |
A system that suggests the best commercial actions based on data while leaving the final decision in the hands of the sales reps. |
|
Selection of Patients for Clinical Trials |
A software that automatically identifies the most qualified candidates without the need for human intervention. |
A system that recommends possible candidates for researchers, who can then adjust based on additional clinical criteria. |
As we can see, traditional AI is based on models that operate autonomously, without human intervention in decision-making, with the main objective of automating tasks and optimizing processes. It is applied in scenarios where massive data processing is required without human interpretation. Its main advantage is its speed and ability to handle large volumes of information, although it has a key disadvantage: its limited flexibility in the face of unforeseen changes. In contrast, Augmented AI combines automation with human supervision and judgment, enhancing decision-making and improving user efficiency. It is used in strategic contexts, such as recommending the next best action, where human participation is active in the interpretation and final decision. Its main advantage lies in its adaptability to dynamic scenarios, although it depends on interaction with specialists to function effectively.
Below are some of the most relevant applications that are defining this transformation:
1. Analytical Calculation of a Physician's Potential
By analyzing prescription histories and local trends, AI can measure a physician's potential impact on medication adoption. The system can rank different HCPs based on their potential to adopt a new product, and with this information, sales teams can better organize themselves, allowing them to focus on those professionals with the greatest potential.
2. Next Best Action: Optimized Strategies
With real-time data—from HCP preferences to market dynamics—Next Best Action (NBA) suggests the ideal next sales step, such as sending a study by email or conducting an in-person visit. Sales representatives take this recommendation and, guided by their experience, adjust and execute it, achieving more precise interactions and greater engagement with HCPs.
3. Advanced Virtual Assistants
With the support of generative AI, sales representatives can consult specific details about an HCP—such as their clinical history or interests—and receive detailed answers that enrich the preparation of their visits. By leveraging these insights, they plan each encounter with greater precision, maximizing the quality and impact of their interactions.
In 2025, Augmented Intelligence is positioned as a transformative reality in the pharmaceutical sector. Far from replacing people, this technology enhances their capabilities, facilitating smarter decisions and increasing efficiency. In this transformative scenario, we at SDG Group position ourselves as AI experts, leveraging the most advanced and relevant technologies on the market. This experience makes us a strategic partner for the adoption of Augmented Intelligence in the pharmaceutical industry, facilitating its integration into key processes and business strategies, thereby helping human-machine collaboration translate into tangible results.
Original article published in Spanish on PM Farma, here.