AI is advancing the life sciences industry into an innovative future.
But with AI’s promise comes risk. Learn how strategic governance can enable responsible AI adoption.
Article summary
- AI is rapidly transforming the life sciences industry, enabling faster drug discovery and more personalized treatment. However, AI also introduces risks around data privacy, bias, explainability, and regulatory compliance.
- Key AI use cases in life sciences include early cancer detection, disease prediction, and accelerated drug discovery and development. AI models can find patterns in vast datasets that humans cannot.
- To mitigate risks, organizations should take a strategic approach to AI governance with four steps:
- Create an AI inventory and reporting process
- Document AI policies and procedures
- Implement controls and training
- Conduct ongoing monitoring and assessments
- AI governance establishes guardrails for the responsible use of AI, balancing innovation with privacy, fairness, transparency, and reliability. With careful governance, companies can realize AI’s benefits.
- The future of healthcare depends on successfully deploying AI tools while proactively addressing their potential downsides. AI governance helps enable the prudent adoption of this transformative technology.
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