Why 85% of AI Projects Fail?
How Pharma Can Beat the Odds

Introduction

AI is reshaping pharma, from drug discovery to regulatory workflows, yet 85% of projects fail due to data gaps, compliance hurdles, and safety risks. This whitepaper explains why and introduces Straive’s Pharma AI Success Framework, designed to ensure reliable, scalable, and regulator-ready AI that delivers measurable impact.

About the Whitepaper

This whitepaper discusses why 85% of AI projects in pharma fail and how organizations can overcome these challenges. It explores key barriers such as data fragmentation, compliance, and talent gaps, while presenting Straive’s Pharma AI Success Framework to enable reliable, scalable, and regulator-ready AI adoption across the pharmaceutical value chain.

85% of pharma AI projects fail due to fragmented data, compliance hurdles, and safety risks.

Straive’s Pharma AI Success Framework enables regulator-ready, scalable, and domain-aligned AI adoption.

60% faster safety signal detection achieved with AI-driven pharmacovigilance.

99.5% accuracy in trial document curation, reducing compliance errors.

50% lower literature review costs through automated scientific content mining.

A clear roadmap to scale AI beyond pilots, ensuring measurable business and patient impact.

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