POV: Ensuring AI-Powered Omnichannel Strategies Deliver Expected Results

A recent Gartner Predicts report highlighted that by 2027, 40% of GenAI projects in Life Sciences will fail due to non-technology related reasons – such as high costs, poor change management & adoption, lack of proper governance and misaligned processes.¹  On the flip side, in  partnering with our clients, we’ve also witnessed the direct impact AI can have, such as utilizing AI-driven sales suggestions to boost TRx by over 20%.

So how do you ensure that your initiative is a success story? 

Bridging the gap between strategy and measurable impact demands thoughtful design and disciplined execution, particularly in the face of common technical and organizational challenges. These may include fragmented data sources, siloed cross-functional teams, manual segmentation processes, limited personalization, high-volume content libraries, and insufficient planning for adoption and measurement. To address these barriers and implement effective AI-powered omnichannel strategies that ultimately improve customer experience, we recommend focusing on the following foundational elements:

1. Data Strategy & Governance

With data scattered across various sources and often lacking in quality, it’s essential to establish a robust master data management program and governance framework to ensure accuracy and build trust. AI platforms can seamlessly unify these disparate data sources into a comprehensive 360-degree view of the customer. To truly leverage this unified data, it’s crucial to identify and thoughtfully store the information needed to answer key business questions, blending both business acumen and data expertise.  The investment in data governance provides the return of better customer insights, deeper personalization and effective micro-segmentation.

2. Clear Organizational Governance

AI-powered omnichannel initiatives introduce significant cross-functional complexity, requiring tight integration across:

• Omnichannel strategy from Marketing
• Data and intelligence from Insights & Analytics
• Technology implementation from internal or external teams.

To succeed, organizations must proactively address AI’s impact on operating models, processes and ways of working across cross functional teams.  Establishing clear governance frameworks – including defined roles, decision rights, and accountability structures are critical to drive sustained impact and improved cross-functional capabilities.

3. Opportunities to Improve AI-Omnichannel Initiatives Results

Our experience across AI-enabled commercial initiatives shows that while many organizations have invested in foundational tools and platforms, two areas consistently offer outsized returns when optimized: segmentation and content suggestions. These areas often determine whether AI-omnichannel strategies translate into real-world engagement and measurable outcomes.

• Dynamic Segmentation & Recommender Models: Manual segmentation often falls short in delivering personalized experiences. By leveraging clustering algorithms and machine learning-based recommender models, organizations can identify more nuanced micro-segments and dynamically create and adapt messaging and outreach based on behavior, engagement patterns, and preferences. This allows the company to transition from sending one message to one large segment, to developing multiple micro-segments and creating variable, personalized content for each.
• AI-Driven Content Optimization: High-volume content libraries can be overwhelming to teams. AI recommended models can cut through the noise, surfacing the most relevant content for specific HCPs or segments improving content utilization and engagement.

Together, these improvements can significantly enhance the precision, relevance, and impact of AI-powered omnichannel strategies, driving better engagement and business results across key audiences.

4. Roadmap to Results

Excellence in silos is not enough – real impact requires a unified, actionable roadmap that aligns teams, sustains momentum, and provides tactical guidance through every stage of execution, including:

• Defined use cases for embedding AI/recommender engines into omnichannel efforts, grounded in:
  • Key business questions
  • Pain points
  • Success metrics
• Governance and team structure scaled appropriately to support cross-functional execution and oversight
• Pilot, test, and enhance AI recommender results for iterative improvements
• Embedding AI recommendations within omnichannel workflows, with a clear plan for user adoption, measurement, and continuous refinement

Expected Results

After establishing the foundational elements above, expect impactful results such as the following:

• Customized, precise, higher impact customer- engagements leading to optimized patient outcomes and increased customer engagement such as a 30% improvement in engagement with healthcare professionals (HCPs).²
• Upskilled teams within the organization can identify opportunities to utilize AI within existing sales operations and omnichannel projects, resulting in faster speed to market initiatives.
• Earned organizational buy-in to evolve from AI-Powered Omnichannel being seen as a project to becoming the way of meeting business objectives such as increased customer engagement, increased revenue, and lower cost of marketing.

The Role of Vynamic

At Vynamic, we believe omnichannel and AI initiatives are not just about deploying technology, they’re transformative forces that redefine how your organization operates and leads to improved customer engagement. We tailor our approaches to meet you where you are, enabling role-specific use cases, fostering cross-functional team alignment, and delivering measurable results. Our Omnichannel, AI Mobilization, and Tech & Digital Transformation services are designed to scale programs that drive real value.  We partner with you to seamlessly manage teams, resources, and tactics, embedding these programs throughout your organization.

Vynamic core strengths include:

• Healthcare Expertise – We partner with clients across sectors and have developed a strong understanding of both HCPs and patients that informs our AI and Omnichannel approaches.
• Cross-Functional Team Management – Mobilizing and aligning brand, analytics, marketing, IT, and external partners around shared use cases and execution plans.
• Vendor & Ecosystem Coordination – Driving accountability and integration across a multi-partner landscape, ensuring delivery cohesion and business alignment.
• Risk-Based Delivery Planning – Identifying and managing operational, data, and technical risks before they disrupt progress.
• Change & Communications Strategy – Ensuring consistent messaging and intentional engagement to drive adoption across stakeholders, from senior leaders to end users.

We don’t just advise, we embed, execute, and enable your teams to sustain AI and omnichannel excellence.

Want to learn more? Get in touch

References

1. (2023). Gartner Predicts: 40% of GenAI projects in Life Sciences will fail by 2027 due to non-technology-related reasons. Retrieved from https://www.gartner.com/doc/reprints?id=1-2K7SLEU3&ct=250210&st=sb&submissionGuid=f692cdde-2406-4d85-99a7-b9152c9f9eb6
2. (2023). Gartner Document: Life Sciences GenAI Projects and Their Challenges. Retrieved from https://www.gartner.com/en/documents/5447063