The challenge

AI is increasingly recognized as a tool for improving efficiency, uncovering insights, and driving innovation in the pharmaceutical industry. However, for many organizations, efforts to implement AI remain fragmented and exploratory.

For this global pharmaceutical company, various departments had begun piloting AI initiatives, but very few use cases made it to production. Despite awareness of industry-leading use cases, the company lacked a unified approach to prioritize and scale the AI initiatives that could deliver the greatest business impact.

To overcome these challenges, we engaged in a project to evaluate their AI maturity, benchmark it against industry leaders, and define a plan to mature capabilities and implement high-impact AI use cases in alignment with the company’s strategic objectives.

The Solution

Intellishore developed and executed a tailored approach to address these challenges, focusing on three key phases:

1. Assessing AI Capabilities and Gaps:
Intellishore conducted a benchmarking exercise to assess the company’s AI maturity compared to leading industry peers. This exercise focused on identifying gaps and opportunities across AI domains, providing clarity on existing strengths and areas requiring improvement in order to stay ahead in the competitive landscape.

2. Identifying High-Value Use Cases:
The next phase involved identifying and evaluating AI use cases. This included mapping use cases to strategic goals, assessing maturity and feasibility, and uncovering synergies with and across existing initiatives.

3. Developing a Commercial AI Roadmap:
To ensure the findings could be translated into action, Intellishore created a clear and actionable roadmap. This roadmap outlined how to implement and scale the prioritized use cases, including key steps for addressing data readiness, aligning teams, and integrating new tools and processes.

The Results

The engagement empowered the pharma company to shift from ad hoc exploratory AI efforts to a unified and focused approach, setting a foundation for long-term AI success.

Key outcomes include:

• Enhanced Decision-Making: A clear understanding of AI maturity and capabilities relative to competitors enabled better prioritization of resources.
• Strategic Focus: Identification of AI use cases with the highest value, ensuring alignment with both short-term needs and long-term goals.
• Actionable Roadmap: A step-by-step guide to implement, scale, and monitor AI initiatives, maximizing ROI and fostering collaboration across domains.

Leaders within the organization reported immediate benefits, including a clearer vision of AI’s potential and improved alignment between technical capabilities and business priorities.

Future Opportunities 

The potential of commercial AI in pharma extends far beyond the initial roadmap. Future opportunities could include:

• Developing a clear AI operating model to structure future AI use case intake & prioritization to ensure continued favoritism of use cases tied to strategic goals.
• Scaling identified use cases across additional business functions, such as market access and medical functions.
• Building a continuous benchmarking process to adapt AI strategies to evolving industry standards and opportunities.

With a clear strategy and actionable roadmap, the global pharma leader is now positioned to capitalize on AI’s transformative potential, driving innovation and efficiency across the organization.