GenAI Implementation in Life Sciences: Strategies to Ensure Adoption - Beghou Consulting

We understand both the hype and skepticism about GenAI adoption in life sciences. We’ve been involved in impactful, transformative GenAI implementations but also know many industry AI initiatives have faced challenges and stalled.

So, what’s the difference between success and the scrap pile? It’s often not the technology itself that fails, but flawed integrations into teams’ workflows and lack of meaningful insights and quantifiable results for executive teams limit end user adoption.

Based on our work with clients to implement AI solutions, we’ve observed that strategically involving your stakeholders in solution design and having a structured change management plan drive organizational adoption and momentum for AI project expansion. We’ve collated our experience into this six-step framework to help life sciences companies like yours avoid common mistakes in GenAI implementations and ensure adoption by their teams. 

The Solution: 6 Adoption and Change Management Accelerators 

Some of the most common challenges slowing adoption of new AI projects include tool overload and a distrust of “black boxes.” Teams can easily be overwhelmed by a new system with a steep learning curve and too many bells and whistles, while opaque, complex tools can contribute to skepticism and confusion.

In these six steps, we advocate a staged approach focusing initially on functionality that delivers real value and a strategic introduction of new features and tools, all while providing teams with visibility into the processes, systems, and outputs.

1. Establish User Buy-In

As the first step, we recommend engaging executives, key stakeholders, and the end users of the solution early. Without their buy-in, adoption and implementation will likely stall because the solution doesn’t provide what they need in terms of functionality, features, or clear documentation of its impact on KPIs or business goals.

• Engage cross-functional teams during the design phase to ensure the solution aligns with everyone’s needs and to gain their support from the start. 

• Form a steering committee with key end users and stakeholders to provide specific input about the solution and to encourage advocacy for the platform. 

One commercial ops team we worked with found that, although leadership was excited about implementing GenAI, field teams were skeptical. By focusing on quick wins that met the end users’ needs, like automating call summaries for the field teams, they quickly turned resistance into enthusiasm.

2. Develop a Brand

Consider creating a recognizable, cohesive identity for the AI initiative to build trust and familiarity, which, in turn, can encourage user engagement with the solution before and during implementation. 

• Use recognizable branding (such as a logo or tagline) from the very beginning of the initiative. 

• Maintain consistency by using the branding across your platform and all communications, reports, and training materials.

When one of our clients branded their AI-driven insights platform internally, the teams using it felt like it was an organic extension of their existing brand identity.

3. Identify Ambassadors

Hearing positive experiences from peers can be a powerful motivator for others to adopt a new solution. If a specific user group is excited about your proof-of-concept, recruit them as internal ambassadors to champion adoption by others.

• Ask power users to share success stories, train colleagues, and provide qualitative feedback.
• Provide your ambassadors with additional resources to foster enthusiasm and leadership.
  

The analytics and sales ops team at one of our clients became early GenAI champions after using it to automate data synthesis from market research and sales insights. By showing how AI-driven summaries saved time and improved speed to insight, the analytics and sales ops team helped drive adoption across commercial teams.

4. Choose Impactful Meta Use Cases

Identify your use cases (who will use the solution and how) that will provide the highest immediate value and the potential to quickly, easily expand to other scenarios. We’ve found that focusing on meta use cases—those that encompass a family of related use cases—with the potential to be easily scaled, such as medical insights or content creation, addresses significant business needs and drives early wins.

• Start with lower-complexity, high-impact use cases to gain traction and build credibility.

• Select high-priority use case clusters that showcase measurable results.

• Expand into more complex areas as foundational expertise and confidence grow.

One company began using GenAI to extract insights from market research reports, seeing quick efficiency gains. As its impact grew, they scaled it across competitive intelligence, executive summaries, and other unstructured data sources to speed decision-making.

5. Check Blind Spots

Incorporating a “soft launch” ahead of full GenAI rollout can help identify unforeseen risks that could derail adoption. This is the perfect time to have a small group test the solution, gather feedback, and improve the solution for the rest of the end users.

• Allow your internal ambassadors to test your implementation.

• Aim to identify potential resistance points or oversights, such as workflow integration issues, and address them proactively. 

• Gather feedback from the ambassadors and refine as needed before full-scale adoption.

A customer started with a limited rollout of AI to refine customer engagement strategies within their field engagement team. After incorporating their feedback and getting the field engagement team’s buy-in, the company successfully scaled the solution across the commercial and medical teams.

6. Make a Splash

We’ve found that a strong, company-wide rollout drives engagement and excitement. So, when it’s finally time for launch, we recommend making it a special event.

• Generate excitement through internal campaigns that highlight the initiative’s potential impact. 

• Host in-person demos or events to showcase the platform’s capabilities and encourage widespread engagement. 

One company created momentum when senior leadership started requesting AI-driven insights weekly instead of quarterly. As word spread about the faster decision-making, more teams sought access, turning an initial pilot into a broader rollout.

Create Organizational Momentum and Excitement

GenAI has the potential to transform workflows, deliver valuable insights, and meet business goals—when the implementation aligns with internal stakeholders’ expectations. The six steps outlined here can help you gain organizational buy-in as well as excitement from your teams for your initial rollout and future AI plans.

Want more insight on how to drive GenAI adoption in life sciences? Download the slides or see the webinar for a full look at how to bring your GenAI projects from proof-of-concept to production for long-term, organization-wide success. 

Create Organizational Momentum and Excitement

GenAI has the potential to transform workflows, deliver valuable insights, and meet business goals—when the implementation aligns with internal stakeholders’ expectations. The six steps outlined here can help you gain organizational buy-in as well as excitement from your teams for your initial rollout and future AI plans.

Want more insight on how to drive GenAI adoption in life sciences? Download the slides or see the webinar for a full look at how to bring your GenAI projects from proof-of-concept to production for long-term, organization-wide success.