HBA Central New Jersey and HBA Digital Innovators Event: AI At the Helm: Leading the Intelligent Enterprise in Pharma

Article written by Aparajita Verma, Jennifer Postelnek, Elizabeth Dolgos 

The Healthcare Businesswomen’s Association (HBA) Central New Jersey chapter, in collaboration with the Digital Innovators Affinity Group, recently hosted AI At the Helm: Leading the Intelligent Enterprise in Pharma on 11 May 2026. This engaging, in-person program focused on the evolving role of artificial intelligence in the pharmaceutical industry. 

Held at Bristol Myers Squibb in Lawrenceville, New Jersey, the event brought together professionals across functions and career stages. It offered an evening of learning, networking, and thought leadership centered on how organizations can responsibly and effectively integrate AI into enterprise decision-making. 

Opening Remarks: A Human-Centered Perspective on AI 

The program opened with remarks from Fernando Salinas, Chief Talent and Inclusion Officer at Bristol Myers Squibb, who established a distinctly human-centered foundation for the evening’s discussion. He reminded attendees that gatherings like this are not about competition but about supporting one another as professionals navigating shared industry challenges. 

Fernando spoke candidly about his own everyday use of AI tools while acknowledging that the rapidly expanding AI landscape can feel overwhelming. While the future trajectory of AI remains uncertain, he emphasized that the qualities needed to succeed are clear: curiosity, empathy, adaptability, and authentic leadership. These human attributes, he noted, will ultimately determine how effectively organizations harness technological advancement. 

Guiding the Conversation: From Possibility to Practice 

The panel discussion was moderated by Vicki McColley, Chief Operating Officer at Atlas, who framed the conversation around a central question facing many organizations today: how do companies move AI from experimentation into sustainable enterprise capability? 

Panelists included: 

Alexandra Decknick, VP, IT Risk & Resilience, Bristol Myers Squibb  

Anvita Karara, VP, Commercialization AI Strategy & Analytics, Bristol Myers Squibb  
Sarah Blendermann, VP, Learning & Development, AI & Tech Fluency, and Digital Foundations, Pfizer 

Tracy Ring, CDO and NA Head of AI and Data-Life Sciences, Accenture 

Vicki encouraged a candid dialogue, emphasizing that innovation requires learning through mistakes, recalibration, and continuous improvement. Under her guidance, the panel explored both the successes and challenges organizations encounter when operationalizing AI, for a discussion that addressed real-world limitations alongside opportunities. 
Together, the speakers shared practical insights drawn from real-world implementation experiences across strategy, operations, data science, and organizational leadership. 

Key Themes: Adoption, Readiness, and Responsible Scale 

Progress Over Perfection 

A recurring theme was the importance of iterative progress and not waiting for perfect conditions. Panelists noted how dramatically AI capabilities have evolved even within the past year, enabling faster decision-making and operational efficiency. However, waiting for the “perfect” model or flawless application won’t get you where you want to go. Organizations must instead adopt a mindset of experimentation, learning quickly, and improving continuously. Don’t be afraid to fail and learn from it. 

Bridging the Human Adoption Gap 

While technological capability continues to accelerate, human adoption remains one of the largest challenges. Speakers acknowledged the cognitive dissonance many professionals feel between the speed at which AI is moving and personal comfort levels with change. Leaders were encouraged to meet employees where they are, drawing parallels to earlier technological transitions such as the introduction of the internet and smartphones. Successful adoption occurs when AI is positioned as an enabler of human work rather than a replacement for it. 

Building Learning Cultures 

Creating environments where employees can safely experiment emerged as a critical success factor. Panelists emphasized leader-led, peer-amplified learning models that encourage curiosity and shared ownership. Building a culture where change can take root, coaching people, and not managing through metrics alone is important. Adoption works best when individuals see clear benefits to their work, rather than being given a top-down mandate to adopt AI; i.e. a “pull” versus “push” approach. 

Data Quality, Governance, and Trust 

Speakers reinforced that AI will expose legacy data quality gaps, ultimately constraining its effectiveness. Poor or outdated data leads to unreliable outcomes that will erode organizational trust. Discussions also highlighted the importance of governance, appropriate permissioning, and providing secure, sanctioned AI tools to employees to reduce risk while enabling innovation. 

Scaling with Readiness and Resilience 

Several panelists cautioned against scaling too quickly. Pilot programs often succeed under focused attention, but infrastructure and governance gaps are revealed when those programs are expanded. Readiness, not enthusiasm, should guide scale decisions. Design pilots with the assumption they will be scaled. Organizations must build strong operational foundations and redesign workflows rather than simply layering AI onto existing processes. 

The Emerging AI Talent Archetype 

The conversation also explored how AI is reshaping workforce expectations. Individuals must take accountability to change along with technology. Future-ready professionals will combine technological literacy with resilience, sound judgment, adaptability, and curiosity. AI is addressing legacy challenges in new ways, making business domain expertise just as important as technology. Panelists stressed that AI will make mistakes, just as humans do, and organizations must manage expectations while remaining flexible as tools rapidly evolve. 

Responsible and Sustainable AI 

The discussion concluded with reflections on responsible innovation, including environmental considerations associated with AI usage. Panelists agreed that AI should be deployed thoughtfully, where it creates meaningful business value and improves outcomes rather than used indiscriminately. Drawing comparisons to past industrial transformations, speakers expressed confidence that more efficient and sustainable approaches will continue to emerge. 

Key Takeaways: 

• Start with scale in mind: decisions made during pilots shape long-term success. 
• Strong data foundations are critical as AI quickly exposes gaps in quality and governance. 
• Successful AI adoption depends more on people, culture, and leadership than on tools alone. 
• Psychological safety and honest leadership enable experimentation, learning, and innovation. 
• Responsible AI requires resilience, transparency, and planning for failure scenarios from the start. 
• Leaders must balance where to build differentiated capabilities and where to leverage existing solutions. 

Advancing Community and Leadership 

Beyond the insights shared on stage, the event fostered meaningful networking and peer exchange among attendees across the life sciences ecosystem. Participants discussed career development, leadership growth, and the evolving role of AI in shaping the future of work. 

The evening reflected HBA’s mission to advance and amplify women leaders while cultivating inclusive spaces for collaboration, mentorship, and innovation across healthcare and life sciences. 

HBA Central New Jersey and the Digital Innovators Affinity Group extend sincere gratitude to Bristol Myers Squibb for sponsoring and hosting the event, and to the speakers, volunteers, and attendees whose engagement made the program impactful and inspiring. 

Special thanks to our HBA and Bristol Myers Squibb volunteers, whose dedication and teamwork made this event possible: 
Anjali Bharadwaj, Aparajita Verma, Bahar Demirdirek, Bruna Suk, Caterina Musetti, Charmi Patel-Kamdar, Elizabeth Dolgos, Farah Fermin, Gunjan Aggarwal, Jennifer Postelnek, Jignasa Rana, Julie Zaidler, Leia Akre, Lisa Yates,  Maria Fermin, Mariane (Molly) Brillantes Pepino, Nicole Febles, Nisha Mittal, Poorna Ashok, Priyanka Jain, Silvi Chacko, Sultan Gursoy, Sumathi Madadi, Vasanti Anand, Worlue Korkro,