August 11, 2025

Strategic Patience in GenAI - A smarter path to AI leadership

As Generative AI accelerates across industries, life sciences firms must seek to adopt strategic patience, prioritizing long-term enterprise value over generating short-term media headlines.

Rethinking the GenAI Race

  • GenAI adopters face growing risks: tech immaturity, hallucinations, cybersecurity threats, and model collapse.
  • Despite the hype, many firms can struggle with data silos, lack of interoperability, and unclear data governance, which are all key facets required for AI to truly deliver value.
  • To successfully invest in GenAI, firms must embrace agile and ongoing risk management, with a strong emphasis on continuous learning and adaptation as the technology evolves.

Enterprise asset, not functional capability

  • Isolated GenAI experiments can generate short-term excitement, yet sustainable value is created when AI is designed to support core business objectives.
  • Treating AI initiatives as mission-critical, with robust oversight, clear decision rights and well-defined success metrics ensures that lasting value is captured.
  • By strengthening data quality, ensuring adaptable infrastructure and fostering cross-functional talent, firms can ensure scalable growth and avoid technical debt.

Lessons from Past AI Failures

  • Without a clear strategic roadmap, firms can face diminished returns, operational risk, and strategic missteps that ultimately undermine their long-term value.
  • High-profile missteps, including the case of a clinical AI oncology advisor tool that failed to perform, reveals the hidden cost of poor integration and setting unrealistic expectations.
  • By fixing weak links across the firm and not just for an individual function, GenAI can truly thrive.

The Opportunity: Leapfrogging with Maturity

  • Late movers can outperform by learning from early adopters’ mistakes and entering when technology stabilizes.
  • Firms can start exploring GenAI through lower-risk applications in well-established functions that have access to rich historical data for model training.
  • By applying strong data foundations and clear governance, firms can unlock value whilst keeping challenges in check.

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Authors

Tamara Kailas

Senior Consultant
New York

Nicholas Porter

Consultant
New York
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