Developing a Unified Commercial AI Strategy
Turning AI pilot projects into a scalable strategy
Developing a Unified Commercial AI Strategy
Turning AI pilot projects into a scalable strategy
That was the challenge we worked on with our partner. Despite initiatives to explore AI, the efforts were fragmented and rarely moved beyond pilot stage. Without a cohesive strategy, valuable opportunities risked being lost. To stay competitive in an increasingly contested rare disease market and deliver on its vision, our partner needed a clear approach to prioritize, scale, and align AI initiatives with business goals.
That was the challenge we worked on with our partner. Despite initiatives to explore AI, the efforts were fragmented and rarely moved beyond pilot stage. Without a cohesive strategy, valuable opportunities risked being lost. To stay competitive in an increasingly contested rare disease market and deliver on its vision, our partner needed a clear approach to prioritize, scale, and align AI initiatives with business goals.
That was the challenge we worked on with our partner. Despite initiatives to explore AI, the efforts were fragmented and rarely moved beyond pilot stage. Without a cohesive strategy, valuable opportunities risked being lost. To stay competitive in an increasingly contested rare disease market and deliver on its vision, our partner needed a clear approach to prioritize, scale, and align AI initiatives with business goals.
How do you overcome scattered pilot projects and align AI efforts across business units?
That was the challenge we worked on with our partner. Despite initiatives to explore AI, the efforts were fragmented and rarely moved beyond pilot stage. Without a cohesive strategy, valuable opportunities risked being lost. To stay competitive in an increasingly contested rare disease market and deliver on its vision, our partner needed a clear approach to prioritize, scale, and align AI initiatives with business goals.
How do you overcome scattered pilot projects and align AI efforts across business units?
That was the challenge we worked on with our partner. Despite initiatives to explore AI, the efforts were fragmented and rarely moved beyond pilot stage. Without a cohesive strategy, valuable opportunities risked being lost. To stay competitive in an increasingly contested rare disease market and deliver on its vision, our partner needed a clear approach to prioritize, scale, and align AI initiatives with business goals.
We worked closely withour partner to bring structure and direction to their AI journey. Through ahighly collaborative process, anchored in workshops with stakeholders,executive interviews, and industry benchmarking,we co-developed a strategy that balanced ambition with practicality, ensuringit was rooted in the partner’s broader objectives and organizational realities.
Our approach unfolded in three clear phases:
- Assessing AI maturity by benchmarking against industry leaders to highlight strengths and gaps
- Identifying high-value use cases mapped directly to strategic priorities, feasibility, and cross-functional synergies
- Designing a commercial AI roadmap to guide execution, governance, and capability building, ensuring the strategy could translate into tangible action
We worked closely withour partner to bring structure and direction to their AI journey. Through ahighly collaborative process, anchored in workshops with stakeholders,executive interviews, and industry benchmarking,we co-developed a strategy that balanced ambition with practicality, ensuringit was rooted in the partner’s broader objectives and organizational realities.
Our approach unfolded in three clear phases:
- Assessing AI maturity by benchmarking against industry leaders to highlight strengths and gaps
- Identifying high-value use cases mapped directly to strategic priorities, feasibility, and cross-functional synergies
- Designing a commercial AI roadmap to guide execution, governance, and capability building, ensuring the strategy could translate into tangible action
We worked closely withour partner to bring structure and direction to their AI journey. Through ahighly collaborative process, anchored in workshops with stakeholders,executive interviews, and industry benchmarking,we co-developed a strategy that balanced ambition with practicality, ensuringit was rooted in the partner’s broader objectives and organizational realities.
Our approach unfolded in three clear phases:
- Assessing AI maturity by benchmarking against industry leaders to highlight strengths and gaps
- Identifying high-value use cases mapped directly to strategic priorities, feasibility, and cross-functional synergies
- Designing a commercial AI roadmap to guide execution, governance, and capability building, ensuring the strategy could translate into tangible action
Partnering to Shape a Commercial AI Roadmap
We worked closely withour partner to bring structure and direction to their AI journey. Through ahighly collaborative process, anchored in workshops with stakeholders,executive interviews, and industry benchmarking,we co-developed a strategy that balanced ambition with practicality, ensuringit was rooted in the partner’s broader objectives and organizational realities.
Our approach unfolded in three clear phases:
- Assessing AI maturity by benchmarking against industry leaders to highlight strengths and gaps
- Identifying high-value use cases mapped directly to strategic priorities, feasibility, and cross-functional synergies
- Designing a commercial AI roadmap to guide execution, governance, and capability building, ensuring the strategy could translate into tangible action
Partnering to Shape a Commercial AI Roadmap
We worked closely withour partner to bring structure and direction to their AI journey. Through ahighly collaborative process, anchored in workshops with stakeholders,executive interviews, and industry benchmarking,we co-developed a strategy that balanced ambition with practicality, ensuringit was rooted in the partner’s broader objectives and organizational realities.
Our approach unfolded in three clear phases:
- Assessing AI maturity by benchmarking against industry leaders to highlight strengths and gaps
- Identifying high-value use cases mapped directly to strategic priorities, feasibility, and cross-functional synergies
- Designing a commercial AI roadmap to guide execution, governance, and capability building, ensuring the strategy could translate into tangible action
"I value that our partners from Intellishore doesn’t just advise, they lead - driving structure, mixing strategic thinking with data and tech, and setting the direction while I focus on the big picture. Few partners bring that level of initiative."
The case in numbers
The engagement produced five concrete deliverables:
- A structured AI maturity assessment
- A comprehensive view of the data ecosystem landscape, clarifying feasiblity for AI adoption
- A prioritized portfolio of AI use cases tied to commercial objectives
- A governance model with well-defined roles, responsibilities and governance levels across strategic, tactical, and operational layers
- A unified,actionable AI roadmap outlining next steps for implementation and scaling
The engagement produced five concrete deliverables:
- A structured AI maturity assessment
- A comprehensive view of the data ecosystem landscape, clarifying feasiblity for AI adoption
- A prioritized portfolio of AI use cases tied to commercial objectives
- A governance model with well-defined roles, responsibilities and governance levels across strategic, tactical, and operational layers
- A unified,actionable AI roadmap outlining next steps for implementation and scaling
The engagement produced five concrete deliverables:
- A structured AI maturity assessment
- A comprehensive view of the data ecosystem landscape, clarifying feasiblity for AI adoption
- A prioritized portfolio of AI use cases tied to commercial objectives
- A governance model with well-defined roles, responsibilities and governance levels across strategic, tactical, and operational layers
- A unified,actionable AI roadmap outlining next steps for implementation and scaling
Delivering practical tools for execution
The engagement produced five concrete deliverables:
- A structured AI maturity assessment
- A comprehensive view of the data ecosystem landscape, clarifying feasiblity for AI adoption
- A prioritized portfolio of AI use cases tied to commercial objectives
- A governance model with well-defined roles, responsibilities and governance levels across strategic, tactical, and operational layers
- A unified,actionable AI roadmap outlining next steps for implementation and scaling
Delivering practical tools for execution
The engagement produced five concrete deliverables:
- A structured AI maturity assessment
- A comprehensive view of the data ecosystem landscape, clarifying feasiblity for AI adoption
- A prioritized portfolio of AI use cases tied to commercial objectives
- A governance model with well-defined roles, responsibilities and governance levels across strategic, tactical, and operational layers
- A unified,actionable AI roadmap outlining next steps for implementation and scaling
Delivering practical tools for execution
The project enabled our partner to move from fragmented AI experiments to a unified, value-driven strategy. The maturity assessment gave leaders a clear view of their current position against industry benchmarks along with concrete recommendations for operating model design, governance, and key roles. Combined with the data ecosystem assessment, this created a realistic foundation for prioritization. The resulting portfolio of use cases and unified roadmap gave teams clarity on where to begin, how to allocate resources, and how to build toward scalable impact, creating alignment across functions and turning ambition into actionable next steps.
The project enabled our partner to move from fragmented AI experiments to a unified, value-driven strategy. The maturity assessment gave leaders a clear view of their current position against industry benchmarks along with concrete recommendations for operating model design, governance, and key roles. Combined with the data ecosystem assessment, this created a realistic foundation for prioritization. The resulting portfolio of use cases and unified roadmap gave teams clarity on where to begin, how to allocate resources, and how to build toward scalable impact, creating alignment across functions and turning ambition into actionable next steps.
The project enabled our partner to move from fragmented AI experiments to a unified, value-driven strategy. The maturity assessment gave leaders a clear view of their current position against industry benchmarks along with concrete recommendations for operating model design, governance, and key roles. Combined with the data ecosystem assessment, this created a realistic foundation for prioritization. The resulting portfolio of use cases and unified roadmap gave teams clarity on where to begin, how to allocate resources, and how to build toward scalable impact, creating alignment across functions and turning ambition into actionable next steps.
From exploration to alignment and action
The project enabled our partner to move from fragmented AI experiments to a unified, value-driven strategy. The maturity assessment gave leaders a clear view of their current position against industry benchmarks along with concrete recommendations for operating model design, governance, and key roles. Combined with the data ecosystem assessment, this created a realistic foundation for prioritization. The resulting portfolio of use cases and unified roadmap gave teams clarity on where to begin, how to allocate resources, and how to build toward scalable impact, creating alignment across functions and turning ambition into actionable next steps.
From exploration to alignment and action
The project enabled our partner to move from fragmented AI experiments to a unified, value-driven strategy. The maturity assessment gave leaders a clear view of their current position against industry benchmarks along with concrete recommendations for operating model design, governance, and key roles. Combined with the data ecosystem assessment, this created a realistic foundation for prioritization. The resulting portfolio of use cases and unified roadmap gave teams clarity on where to begin, how to allocate resources, and how to build toward scalable impact, creating alignment across functions and turning ambition into actionable next steps.
From exploration to alignment and action
The new AI strategy laid the groundwork for scaling use cases into adjacent areas such as market access and medical functions. By creating a repeatable approach to evaluate and prioritize opportunities, the company can now generate more consistent, data-driven insights across functions.
In rare diseases, where data points are often limited and fragmented, this alignment is especially powerful. It enables a deeper understanding of markets and treatment landscapes, helping to raise awareness among healthcare professionals and improve visibility of therapeutic options. Beyond efficiency gains, the strategy positions the company as an innovator while ultimately supporting faster access and better outcomes for patients.
The new AI strategy laid the groundwork for scaling use cases into adjacent areas such as market access and medical functions. By creating a repeatable approach to evaluate and prioritize opportunities, the company can now generate more consistent, data-driven insights across functions.
In rare diseases, where data points are often limited and fragmented, this alignment is especially powerful. It enables a deeper understanding of markets and treatment landscapes, helping to raise awareness among healthcare professionals and improve visibility of therapeutic options. Beyond efficiency gains, the strategy positions the company as an innovator while ultimately supporting faster access and better outcomes for patients.
The new AI strategy laid the groundwork for scaling use cases into adjacent areas such as market access and medical functions. By creating a repeatable approach to evaluate and prioritize opportunities, the company can now generate more consistent, data-driven insights across functions.
In rare diseases, where data points are often limited and fragmented, this alignment is especially powerful. It enables a deeper understanding of markets and treatment landscapes, helping to raise awareness among healthcare professionals and improve visibility of therapeutic options. Beyond efficiency gains, the strategy positions the company as an innovator while ultimately supporting faster access and better outcomes for patients.
Creating a sustainable path for AI at scale
The new AI strategy laid the groundwork for scaling use cases into adjacent areas such as market access and medical functions. By creating a repeatable approach to evaluate and prioritize opportunities, the company can now generate more consistent, data-driven insights across functions.
In rare diseases, where data points are often limited and fragmented, this alignment is especially powerful. It enables a deeper understanding of markets and treatment landscapes, helping to raise awareness among healthcare professionals and improve visibility of therapeutic options. Beyond efficiency gains, the strategy positions the company as an innovator while ultimately supporting faster access and better outcomes for patients.
Creating a sustainable path for AI at scale
The new AI strategy laid the groundwork for scaling use cases into adjacent areas such as market access and medical functions. By creating a repeatable approach to evaluate and prioritize opportunities, the company can now generate more consistent, data-driven insights across functions.
In rare diseases, where data points are often limited and fragmented, this alignment is especially powerful. It enables a deeper understanding of markets and treatment landscapes, helping to raise awareness among healthcare professionals and improve visibility of therapeutic options. Beyond efficiency gains, the strategy positions the company as an innovator while ultimately supporting faster access and better outcomes for patients.
Creating a sustainable path for AI at scale
What we learned
Clear ownership and alignment across business and data functions ensured that use cases moved beyond pilots.
Comparing maturity with industry leaders galvanized leadership to prioritize and invest in AI strategically.
A fit-for-purpose roadmap translated ambition into concrete steps, unlocking adoption across teams.
Success depended as much on shared vision and collaboration as on technical capability.
Want to incorporate a unified AI strategy? Let's talk.
Feel free to reach out to one of our team members with expertise in this area. Whether you're facing a similar challenge or exploring where to start, we’re ready to help you turn ideas into action.
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