Artificial intelligence is changing everything in pharma and biotech. Drug discovery happens faster. Clinical trials reach more patients. Quality systems work more efficiently. But here’s a challenge the industry needs to address: Women hold less than 20% of the leadership positions making AI decisions in our industry.

I recently hosted a Lift Up: Women in Life Sciences broadcast with three senior leaders who are actively shaping how AI transforms healthcare. Erica Paine leads value and access at Chiesi USA. Sherrita Dorsey serves as the US Head of Patient and Professional Advocacy at Amicus Therapeutics, and Sandra Lopes Guerreiro heads global quality, safety, and data integrity at Esteve in Barcelona.

Together, they bring decades of combined expertise across pharma operations, patient advocacy, regulatory affairs, and digital transformation. Their message was clear: while companies rush to adopt AI, they’re overlooking the fact that successful implementation hinges as much on human skill as it does on tech.

Sandra shared research from McKinsey and MIT. AI’s biggest transformation won’t be technical. The real change will be human. It will affect culture, workflow, and leadership. That’s exactly where women can excel. Here are three strategies from my conversation with Erica, Sherrita, and Sandra that can help you lead AI transformation in life sciences.

Strategy #1: Leverage Your Natural Strengths as Strategic Advantages

The skills that women already possess are exactly what AI leadership demands. While many people worry about learning to code or mastering technical details, the real competitive advantage lies in abilities that women have been nurturing throughout their careers.

Erica Paine explained why working mothers have a built-in advantage. “I have never met a better multitasker than a working mother. The ability to hold all of these fast-moving parts all at once is something that I think women can really leverage as a skill to help set us up for success, to be leaders in this world,” she said. She’s right. Juggling school schedules, work deadlines, and family needs while keeping everything running smoothly builds exactly the sort of skills that AI Implementation needs in pharmaceutical companies.

Sandra Lopes Guerreiro took this further by connecting it to what makes AI transformation successful. “According to McKinsey and MIT, the biggest transformation will be human in terms of culture, workflow and leadership. We could excel at this human transformation. It’s part of our superpowers,” she explained. Guiding teams through change. Understanding different perspectives. Maintaining the human element during technical shifts. These define successful AI adoption.

Sherrita Dorsey shared advice about staying authentic in leadership roles. “I would tell my younger self to get comfortable with not shrinking. Understand that my superpower is my authenticity. Innovation and transformation will come from that,” she said during our conversation. In life sciences, where patient safety and regulatory compliance demand careful consideration, authentic leadership that balances speed with thoughtfulness proves essential.

These strengths apply directly to life sciences. Implementing AI tools for clinical trial recruitment requires juggling patient safety, regulatory requirements, data integrity, and team training. Adopting AI for drug discovery needs someone who can translate between technical specialists and business leaders while keeping patients at the centre. They require exactly the skills women have been building throughout their careers.

Strategy #2: Demand Representation That Creates Real Influence

Having women present in AI discussions isn’t enough. Real change requires women in positions where they can shape decisions, challenge assumptions, and redesign systems from the ground up.

Sandra Lopes Guerreiro shared a stark reality. “When it comes to AI leadership, we have less than 20% of women giving governance, making the decisions. So we are not leading it yet,” she said. But she also pointed out why this is critical. AI tools learn from the data and decisions we feed them. “We need to make sure that women are part of the steering committees, the governance bodies that are doing the design and the decisions, because it’s not a tool thing. It’s a design thing,” Sandra explained.

Erica Paine highlighted how deeply bias runs in current systems. She shared results from a recent LinkedIn experiment. “Women tried switching their LinkedIn gender to male and swapping their language to more bro coded language. Women saw a staggering increase. In one instance, a 1,600% increase in profile views, over 1,300% increase in impressions, over 400% jump in reach,” she shared. When algorithms favour masculine language patterns this dramatically, the impact on career advancement becomes massive.

Sherrita Dorsey “…saw a quote that representation is visual, but influence is structural,” she said. Having women at the table means little if they can’t speak up. It means nothing if their concerns get dismissed. “We have to ensure that the right people are at the table, having the right conversations,” Sherrita added. In pharmaceutical companies, this means women need seats on AI steering committees. They need to be part of procurement decisions for new tools. They need spots on governance boards setting data policies.

The practical application here is straightforward. Regardless of whether your company is implementing AI tools for quality control, regulatory submissions, or clinical operations, ask who sits on the decision-making committees, and push for equity audits on AI systems. As Sandra suggested, “We need something that is embedded to make sure that we are always checking who is impacted, who is invisible, who might be damaged by bias.” Life sciences companies that build diverse leadership teams for AI adoption create better tools that serve broader patient populations.

Strategy #3: Build Partnerships Beyond Your Organisation’s Walls

Solving AI equity challenges requires collaboration between pharmaceutical companies, healthcare systems, academic institutions, and the communities that our work ultimately serves. Individual companies can’t fix systemic problems alone.

Erica Paine shared what real partnership looks like. “We can imagine that we know what communities need, but we don’t. That’s why partnership and collaboration is so important. Open source tools that leverage AI, affordable cloud infrastructure, policies that incentivise equitable data sharing and working with NGOs, working with community health partners,” she explained. The most effective solutions emerge when multiple sectors bring different expertise to the table.

Sherrita Dorsey emphasised building trust as the foundation for any community partnership. “Trust is a huge component. It’s not a national game. It’s a boots on the ground approach that we have to deploy,” she said. Going back to churches, community organisations, and local healthcare workers creates the relationships that make clinical trial recruitment and patient advocacy effective. “It’s about building trust and being in those communities early and often,” Sherrita added.

For pharmaceutical and biotech companies, this means rethinking how we approach clinical trial recruitment. Sherrita shared specific examples. “Working with HBCUs, historically black universities, medical schools, nursing schools, beginning to say these could be internship opportunities where we’re exposing the academic institutions to industry and having use cases where they can problem solve and bring those solutions back,” she explained. These partnerships create diverse talent pipelines while also improving the quality of research data.

Clinical trials have historically excluded diverse populations, creating gaps in our understanding of how treatments work across different groups. As Erica pointed out, “Women’s hormones excluded them from clinical trials because it was something that couldn’t be controlled for. That leaves women trying to figure out, how does this medicine work for me?” Partnership with community organisations helps pharmaceutical companies reach populations that research has traditionally missed. Better data leads to better treatments for everyone.

Bringing It All Together

My conversation with Erica, Sherrita, and Sandra revealed something important. Women’s collaborative approach, emotional intelligence, and authentic leadership styles position us perfectly for guiding AI transformation in life sciences. We need to claim seats on AI governance committees where we can shape actual decisions. We need to build partnerships that extend beyond corporate walls into communities and academic institutions. This is how women can ensure that pharmaceutical innovation serves everyone equitably.

These three accomplished executives continue shaping the future of drug development, patient advocacy, and quality systems worldwide. Their approaches demonstrate that AI success depends more on human leadership than technical expertise. Life sciences organisations that recognise this reality will deliver better outcomes for patients. They’ll also attract the talent needed to thrive in an AI-driven future.

Finding the right leaders who can balance technical innovation with human insight has never been more important for pharmaceutical and biotech companies navigating digital transformation.

Want to hear more insights from Erica Paine, Sherrita Dorsey and Sandra Lopes? Listen to the full broadcast.