After widespread AI experimentation in 2024, companies will face pressure to show real returns on their AI investments in 2025. This will drive adoption of vertical AI solutions that are purpose-built for specific workflows. From industry-specific AI to the rise of AI agents, here are four trends set to disrupt pharma and healthcare in 2025.
AI helps pharma truly put patients and HCPs first
Over the past two years, companies across industries rapidly adopted ChatGPT and GenAI to gain a competitive edge. Pharma took a more cautious, measured approach, especially in commercial operations. But in 2025, the industry will aggressively adopt AI, driven by the need to better serve patients and healthcare professionals (HCPs).
To enable this patient-centric approach, companies will integrate well-engineered AI models within their complex ecosystem of data, partners, patients, and providers. Early AI adopters in pharma quickly recognized the risks and challenges of putting generic GenAI and large language models (LLMs) into production. Moving ahead, innovative leaders will abandon one-size-fits-all, plug-and-play generic AI models for industry-specific AI solutions with the proper engineering and guardrails to avoid hallucinations.
Companies will begin scrutinizing AI and digital initiatives for measurable ROI and business impact, investing in these verticalized solutions tailored to their data, sales models, and workflows. This will drive sophisticated omnichannel engagement strategies where AI optimizes communications across digital, in-person, and hybrid touchpoints.
With this AI-powered, patient-centric approach, the pharma industry will drive truly seamless, personalized experiences that reach HCPs and patients with the right message, at the right time, through the best channel. Companies will focus on deploying proven AI implementations with speed and agility to rapidly adjust on the fly, at a massive scale.
As a result, organizations will achieve a new level of commercial success and accelerate treatments for patients in a way that was never possible — all enabled by AI.
GenAI models will advance to deliver HCP and content recommendations
Pharma has yet to fully leverage GenAI to improve data quality for downstream, classical AI models to enhance recommendations on HCPs to engage and what content to send them. Next year, innovators will experiment with advanced GenAI models fine-tuned and trained for multi-modal recommendations, including doctors to target, information to share, and when to send it, to drive new levels of automation and productivity across sales teams.
Today, there is growing momentum to refine existing GenAI architectures to drive this new generation of multi-modal content and lead recommendations with advanced techniques such as the ability to understand cause and effect via causal inference. Imagine AI systems capable of not just analyzing content, but truly understanding it and aligning it with the right HCPs — a transformative leap for precision engagement that is more intuitive and human-like.
At the same time, the drive to embed GenAI into workflows will spark a transformation in data quality, enabling agentic automation to gather and enter data from every customer interaction. By improving the quality and accessibility of training data, these systems will further advance content and HCP targeting recommendations, bridging the gap between automation and the right actions to prioritize and take.
In five years, this will eventually pave the way to Large Concept Models (LCMs) that can process abstract concepts and act like humans. LLMs have limitations in reasoning and maintaining long-term coherence because they can only predict token sequences. It’s autocompleting the next word, not reasoning. If the wrong word is used upfront, the rest of the sentence goes off track. Meta’s groundbreaking research on LCMs will redefine AI’s ability to deal with abstract concepts and think like humans.
The impact in pharma will be significant. Companies will generate actionable insights with agents built on LCMs that can achieve deep understanding, just like a sales rep or marketer. Commercial organizations will scale engagement and personalization to hundreds of thousands of doctors with AI that can reason with abstract concepts and provide precision content and targeting recommendations.
AI agents interact with data and systems just like a human
AI agents can now tackle increasingly complex tasks by combining natural language understanding with programmatic design, powered by cost-effective, stable large LLMs and seamlessly combining function calls with natural inputs. As organizations adopt AI, their focus must shift from basic automation to building adaptable, scalable systems that align with their specific workflows.
Companies struggle when force-fitting generic AI tools into specialized, vertical workflows, leading to security risks, oversharing issues, and scalability problems. It’s like putting a Ferrari engine in a Toyota – a powerful component mismatched with the broader organizational infrastructure that will inevitably fail.
AI adoption is not binary, but an iterative process to improve capabilities. Successful organizations that use AI start by automating simple administrative tasks, then layer on increasingly complex workflows and gradually scale to higher levels of sophistication. This approach achieves true integration and builds symbiotic systems that complement business processes.
In the coming years, AI agents will redefine connectivity and workflows. Pre-built integrations will evolve, as agents navigate authorization processes more intelligently, streamline connections to tools and systems, and become more adaptive and seamless.
But true “agentic” systems that operate independently and autonomously remain aspirational. Current tools, from basic chatbots and work automation tools to custom AI systems, execute multi-step workflows rather than act independently. As the technology advances, tools will become increasingly autonomous and capable of understanding context, anticipating needs, and navigating between systems.
AI agents will mature over the next decade, unlocking fluid interoperability across tools and workflows while maintaining security and scalability. As organizations build AI capabilities iteratively, current siloed tools will be replaced with comprehensive systems that scale with the business to ensure security and strategic alignment.
For pharma companies and beyond, this shift will transform AI adoption into a scalable strategy — enabling systems that are tailored, secure, and agentic.
Things get personal as AI puts patients in control of their health
Pharma’s success with AI lies in combining high-quality data, deep domain expertise, and voice-enabled technologies. By 2025, this synergy will redefine healthcare, making it more personalized, accessible, and empowering for patients. This transformation will give individuals unprecedented control over their health journey.
AI thrives on data to identify patterns, uncover hidden relationships, and generate insights that human analysis may miss. The integration of deep industry knowledge ensures that AI-powered systems interpret and leverage health data in a way that is accurate and actionable.
AI assistants can now make complex health information more digestible and meaningful for patients and healthcare providers alike. Now voice-enabled AI agents are capable of engaging in natural, human-like conversations. This will transform healthcare delivery by offering personalized treatments, recommendations, and lifestyle adjustments based on a patient’s history and context, enhancing patient outcomes and ensuring that healthcare solutions are uniquely suited to individual needs.
Beyond personalization, AI will also democratize healthcare access, allowing patients to interact directly with their medical data. Patients will no longer have to rely solely on their healthcare providers to access vital health information. Decentralized models like blockchain will enhance data ownership, security, and trust, empowering individuals to control how their information is shared and used.
Expect AI-driven tools to put patients at the center of healthcare and equip them to make informed, proactive decisions that transform their health journey. The future of healthcare will be one where technology doesn’t just serve the industry but genuinely improves the lives of individuals, transforming how we interact with medical data, healthcare providers, and our personal well-being.
A big leap forward for AI in 2025
As patient-centric AI solutions mature, GenAI advances, autonomous agents evolve, and personalized healthcare becomes reality, we’re on the verge of a new era in medicine. These transformations won’t just optimize existing processes, but result in a more accessible, personalized, and effective healthcare system that truly puts patients first while empowering providers with unprecedented capabilities.
Photo: metamorworks, Getty Images
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