Inside a Biotech People Leader’s Bold Experiment with Custom GPTs to Spark Creativity
By
Faye Wai
Faye WaiTechnology Analyst
Faye Wai is a HR Technology Analyst and contributor to People Managing People, with a background in branding, public relations, and content marketing. She has vet vendors as an end-user in both consultancy and in-house capacities, providing her with a unique perspective on the challenges and opportunities within the people operations sector.
Erin McCann, Head of People at Genomenon, shares how she leverages AI to amplify human creativity, redesign leadership roles, and build high-performing, AI-augmented teams while focusing on the uniquely human skills that drive culture and innovation.
AI Amplifies Human Creativity — It Doesn’t Replace It: AI is a thought partner that enhances problem-solving, messaging, and innovation. At Genomenon, Erin uses AI to support sales training and leadership development, showing how technology can accelerate creativity rather than diminish it.
Leadership Is Being Redefined in an AI-First World: The future of leadership isn’t about having all the answers — it’s about asking better questions and guiding both humans and AI toward better outcomes. Erin emphasizes influence, adaptability, and emotional intelligence as the differentiators for tomorrow’s high-performing leaders.
Freeing Up Bandwidth for High-Value Work: By delegating repeatable, low-value tasks to AI, Erin is aiming to create more space for her People and HR team to focus on strategic priorities like strategic people programs, alignment, and organizational health. Her approach shows how leaders can redesign their roles to focus on what only humans can do best.
There is no straight line in leadership
My path to executive leadership in People and HR has certainly not been a straight line. The curves and turns I've taken have given me a broad set of experiences.
I began my career in Sales and Marketing, with a focus on the hospitality industry. That world taught me the power of human connection, the value of hard work, and how every company is its own small ecosystem. After several years of selling, I transitioned into a small sales training consultancy. Unlike many leaders who are thrown into management without preparation, I had the benefit of learning leadership fundamentals early. I implemented training programs, grew marketing journeys, and built a strong foundation in learning and development.
Through that work, I met a startup founder in New York and leaped into the world of Customer Success. I designed onboarding journeys and got my first taste of the tech sector. I also discovered how deeply internal operations shape employee experience — so much so that I pivoted into People and HR work. I intentionally stepped back a few rungs in my career to join a 13-person marketing tech startup, where I built the People function from scratch. When we grew past 100 employees, which resulted in a successful acquisition, I was hooked.
Today, I lead HR and People for a 175-person global biotech organization that is using AI alongside our team of scientific experts to organize the world's genomic knowledge and connect clinicians and researchers to make genomic evidence actionable — simplifying complex genetic data into insights that advance patient diagnosis and the development of precision medicine. Every chapter of my career, — from hospitality to sales to startups, — has shaped how I lead, build teams, and create environments where people and businesses thrive.
My biggest takeaway: There is no straight line to leadership and every step on your journey is valuable.
Knowing when to lean on AI vs. human judgment
People and HR work will always revolve around one constant: Humans are unpredictable.
AI is getting better at anticipating and even reasoning through some of that unpredictability, but truly understanding nuance and context still takes time, conversation, trust and overcoming fears of AI. I don’t see that changing.
What is changing is how People and HR teams deliver support.
At Genomenon, I’ve built custom GPTs designed to handle the routine, repeatable questions and processes. The goal isn’t to replace the human touch; rather, it’s to give my small-but-mighty team more bandwidth to focus on the nuanced, high-value partnership work that drives culture and engagement by simplifying their work with AI.
In a way, AI is pushing leaders to let go of the idea that being “hands-on” means touching every task. It’s about being intentional and knowing when to lean on technology, and when the human connection matters most.
First, sales training. We’ve integrated AI into our L&D training programs so sales professionals can practice scenarios, test messaging, and get instant feedback alongside traditional training methods. It’s made skill-building more interactive and scalable.
Second, I’m beta testing a leadership GPT designed to help managers navigate tough conversations and frame feedback effectively. It’s not about giving them a script alone, but about offering prompts, perspectives, and language that help them approach situations with clarity and empathy.
And as an honorable mention, we are building a GPT to help our employees get quick answers to day-to-day questions. So far, the impact has been encouraging.
Erin's Tip
AI isn’t replacing human judgment, but it’s speeding up preparation and boosting confidence in the moments that really matter.
Custom GPTs for HR
Let's dive into the custom GPTs I mentioned. We’ve built two of them within our enterprise account to support employees and managers as thought partners—not replacements.
"Genomenon Genie" is our real-time policy concierge, designed to help employees quickly get answers to day-to-day questions like “What’s our parental leave?” or “How do I submit an expense?” It pulls directly from our handbook and documentation, links the source, and is currently in beta.
"Ask Geno" is a manager coach grounded in our job architecture, manager training, and internal best practices. It helps managers work through tough situations, set 30/60/90-day plans, map feedback to competencies, and navigate conversations like compensation or performance reviews. Because it's based on our internal frameworks, it nudges users toward consistent, equitable language.
Both tools are built to extend the People team's reach, supporting thoughtful, timely, and aligned decisions across the company.
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Custom GPTs for sales
I also built two sales-focused GPTs. Each Sales GPT was designed around the specific personas and markets Genomenon targets. Instead of slicing the sales process into separate bots, I took a persona-first approach.
Each GPT is tuned to “think like” the ideal sales coach for that particular audience. For example, one focuses on pharma/biotech prospects and helps reps frame outreach in the context of drug discovery and variant interpretation. The other is designed for diagnostics customers, tailoring messaging to labs and clinicians who care about accuracy, turnaround time, and clinical impact.
Both GPTs can generate persona-appropriate outreach, anticipate likely objections, and prep talking points for discovery calls, all grounded in our approved messaging and case studies. Marketing partnered with me to ensure the tone stayed on brand, while Sales validated that the prompts were practical and usable in the field.
As a result of these GPTs, we’ve seen faster ramp times, more consistent messaging across the team, and sales executives reporting that they save 30–40+ minutes per prospecting approach because they’re no longer starting from a blank page. So far, in a short period of time, we've already had one lead come in after using the GPT to generate messaging.
How to build custom GPTs
This was entirely low code and self-taught, built inside an Enterprise GPT account, so our data stayed secure. Here’s the build recipe I followed:
Step 1: Frame the problem
I wrote one-sentence “contracts” for each GPT to start. Example:
“Draft outreach to pharma R&D personas that highlights our variant interpretation platform in the context of clinical trial acceleration.”
“Guide a rep in tailoring a discovery call for diagnostic labs, surfacing the top three lab-specific pain points and relevant case studies.”
Step 2: Set security & access
Enterprise GPT meant we could:
Keep our data out of public model training.
Limit access (sales-only for these bots).
Shut off access if someone leaves the company.
Step 3: Curate the library
I avoided connecting Google Drive wholesale — too much risk of pulling in sensitive data like salaries. Instead, I hand-selected a “golden set” of docs: messaging houses, case studies, ICP notes, objection/response sheets.
Step 4: Write the “system brain”
Each GPT had specific instructions on:
Voice and tone (concise, credible, audience-aware).
Boundaries (no guessing pricing, roadmap, or competitor claims).
Formatting rules (bullet points for call prep, 120-word cap for emails).
Step 5: Test and iterate
I ran tests by feeding in edge-case scenarios (rare objections, unusual job titles). Whenever it hallucinated or went off-message, I added rules or tightened the document set.
Step 6: Launch and train
We piloted with our sales team, gave a 60-minute training, and created a Slack feedback channel. From there, I rolled out updates based on real usage.
Integrating AI into skills and sales training
I remember the moment when I realized that AI was changing the way I lead.
I was building those custom GPTs for our sales team. Initially, the idea was purely practical: Give them quick access to product details, case studies, and competitive positioning without digging through endless files. But it quickly became something bigger.
We paired the rollout with sales training that blended traditional methods, like a prospecting process, with AI as a real-time support tool. Instead of replacing the fundamentals, AI became an extension of them. Reps could practice a message, then immediately ask how GPT might make it better. GPT can come from the buyer's perspective and teach along the way.
Instead of replacing the fundamentals, AI became an extension of them.
The transformation was in how the team started thinking. They weren’t just using AI as a faster search engine; they were using it as a strategic thought partner.
For me, this was the turning point; I realized my leadership wasn’t just about enabling the right human skills, but also about building the muscle to integrate technology into those skills seamlessly.
The freedom of using AI as a thought partner
That's really the most surprising thing I've found: how quickly AI “learns” when you feed it the right context, and how valuable it is to have a sounding board that isn’t a colleague or a boss.
There’s a freedom in exploring half-formed ideas with AI, testing different angles, and refining your thinking without worrying about hierarchy or judgment. It’s like having a tireless, unbiased thought partner who’s always ready to workshop the next iteration.
Why AI can’t replace human creativity
On the same thread, the biggest disconnect I see is the assumption that AI can replace creativity and strategic thinking.
It can spark ideas and accelerate execution, but it can’t fully replicate the human process of connecting disparate insights, challenging assumptions, and shaping a vision that truly resonates.
My concern is that some teams are starting to lean on AI as the source of ideas, rather than a tool to refine and expand them. For me, AI’s promise is best realized when it amplifies human creativity; not when it tries to replace it.
Erin's Tip
AI’s promise is best realized when it amplifies human creativity and not when it tries to replace it.
An AI tool every HR leader needs
Currently, for HR tools we use Gusto for payroll and Greenhouse for our ATS (Applicant Tracking System), but our performance management system is still manual. Our People team built a job architecture for each department, creating the framework ourselves and then leveraging GPT (especially GPT-5 Reasoning) to evaluate and analyze the market. This is a great tool for that type of work because it can scan job openings and publicly available resources on your behalf.
When evaluating vendors, I focus on a balance of strategic alignment, quality, and value. I look for partners who understand our business priorities, can scale with our growth, and demonstrate a commitment to compliance and ethical practices. I consider their track record, customer service responsiveness, and ability to deliver innovative solutions. Cost matters in context — not just the lowest price, but the total value and long-term partnership potential as we grow. Integrations are also key; I’m not interested in stitching together a patchwork of tools but in building an interwoven system.
Finally, I lean on references and trusted networks to validate reliability, because a vendor relationship is ultimately about trust and consistent delivery. Experience has taught me that sometimes the promise isn’t the reality!
Advice for an AI-first world
My advice is to lean in and experiment; don’t hold back from change out of fear that it will make your role obsolete.
The reality is that AI is reshaping work whether we engage with it or not. Leaders who approach it with curiosity and a willingness to test, learn, and adapt will be the ones who find ways to amplify their impact; not diminish it.
How AI will redefine leadership and organizations
In the next five years, I think leadership will shift from being defined by who has the answers to who can ask the best questions — and guide both humans and AI toward the right ones.
Leadership will shift from being defined by who has the answers to who can ask the best questions — and guide both humans and AI toward the right ones.
As AI takes on more of the data gathering, synthesis, and even first-pass decision-making, the leaders who thrive will be those who can interpret, contextualize, and inspire action from that information. Influence, adaptability, and emotional intelligence will become the real differentiators in an AI-first world.
Influence, adaptability, and emotional intelligence will become the real differentiators in an AI-first world.”
Right now, my focus is on using AI to take as much manual work off my plate as possible. With an HR team of one full-time and two part-time employees — plus me — we need that bandwidth before we can think about bigger strategic shifts.
In the future I can see HR and People teams having dedicated resources to maintaining, building, and optimizing their AI tools, replacing manual data work that is now being done. Our Engineering team is leading the way in using AI in an effective way and I take a lot of inspiration from them. I expect those capabilities will eventually become embedded in how we design and deliver our People strategy.
For now, it’s about creating the space to think and operate more strategically by letting AI handle the repeatable, time-consuming work, and by becoming a thought partner for those tough-to-solve challenges that humans create!
Follow along
You can follow Erin's work on LinkedIn as she continues to implement and experiment with custom GPTs. And check out the company she's doing it for: Genomenon.
More expert interviews to come on People Managing People!
