Promega ChatGPT Adoption Case Study

Promega, a leader in life sciences, has implemented a top-down adoption of ChatGPT to accelerate the delivery of biological reagents and integrated systems to the biotech ecosystem. By deploying over 1,400 custom GPTs, the company has achieved high adoption rates—with 80% of the workforce utilizing the tool—to optimize complex manufacturing, sales, and marketing operations.

Manufacturing and Quality Assurance Optimization

Promega uses ChatGPT to manage the complexity of producing 4,000 products and meeting custom customer specifications. Key applications include:

  • Equipment Forecasting: General Manager Kristen Yetter uses ChatGPT to forecast equipment replacement timelines and costs, generating yearly investment projections based on modifiable assumptions.
  • Knowledge Retrieval: Research scientists use custom GPTs that call public APIs to fetch protein specifications from various databases in seconds, streamlining the design of custom assays.
  • Quality Assurance Automation: The Quality Assurance team uses a custom GPT integrated with Power Automate to handle over 250 quality surveys annually. This automation reduces internal workload by more than 600 hours per year while delivering certifications and quality policies to customers.

Sales and Marketing Efficiency

To manage a vast product portfolio and 60,000 accounts, Promega's sales and marketing teams have developed specialized GPTs to scale outreach:

  • My Prospecting Pal GPT: This tool analyzes prospects to identify research initiatives and common interests, reducing lead analysis time by 1 to 4 hours per prospect.
  • Email Marketing Strategist GPT: This tool has halved the time from content creation to campaign execution, saving 135 hours of work over several months for hundreds of marketing emails.

Strategic Framework for AI Adoption

Promega's AI adoption was managed by an AI Advisory Council consisting of senior leaders from various departments. The council established several key principles for driving enterprise-wide integration:

  • Resource Allocation: Provide sufficient licenses to encourage creativity, then shift resources toward the highest-impact use cases.
  • Data-Driven Tracking: Monitor enterprise usage to identify high-impact applications early.
  • Engagement: Use regular workshops and share-outs to make AI learning accessible and engaging.
  • Performance Validation: Use data to build employee confidence; Promega found that employees using basic prompts outperformed those not using the tool.
  • Leadership Example: Ensure leadership regularly uses ChatGPT to set a standard for the organization.

Long-Term Competitive Advantage

CEO Bill Linton views AI proficiency as a critical differentiator in the competitive life sciences market. The company's goal is to seamlessly integrate AI tools into all employee workflows to better support researchers in making meaningful advancements in research and discovery.

Sources