Bridging the AI Gap: Overcoming Barriers to Generative AI Success in Enterprise

Why Only 10% of AI Projects Succeed—and How to Bridge the Gap

The Promise and Challenge of Generative AI

Generative AI (GenAI) holds massive potential to transform enterprise operations, from improving customer engagement to automating internal workflows. Yet, despite widespread enthusiasm, most organizations find themselves stuck in the proof-of-concept stage. According to our latest survey, only 10% of AI projects progress to production, and barriers like unclear ROI, data quality issues, and leadership hesitation continue to slow progress.

So, what separates successful AI initiatives from stalled experiments?

Our new white paper, “Bridging the AI Gap: Overcoming Barriers to Generative AI Success in Enterprise,” dives into the challenges enterprises face—and more importantly, the proven strategies that help organizations move from exploration to impact.

Key Insights from the White Paper

1. The State of AI Adoption
   Most organizations are actively exploring AI, but scaling projects remains a challenge. Enterprises are making progress, yet only a fraction of initiatives achieve measurable outcomes.
   
   
2. Top Barriers to Success
   Enterprises face recurring challenges, including:
   • Lack of a clear business case or measurable ROI
   • Poor data quality and fragmented knowledge systems
   • Limited internal expertise and leadership support
     
     These hurdles often delay large-scale adoption, leaving organizations struggling to unlock AI’s full potential.
3. Success Story: 30% Reduction in Help Desk Workload
   One insurance sector organization demonstrates the power of combining structured knowledge engineering with Generative AI. By building a strong content foundation before deploying GenAI to power customer chatbots, they reduced manual help desk operations by 30%. The result? Fewer resources spent on routine tasks, more focus on solving complex customer issues, and sustained ROI through ongoing governance and monitoring.

What’s Next: Turning Barriers into Opportunities

Enterprises ready to scale their AI initiatives can start with a few critical actions:

• Develop clear, measurable business cases for AI investments.
• Prioritize data quality and governance to build a strong foundation.
• Engage leadership and foster a culture of AI adoption.

These steps, paired with tailored strategies for scaling AI projects, can help organizations achieve measurable success and realize the full value of Generative AI.

Get the Full White Paper

For a deeper dive into the challenges, strategies, and real-world case studies, download our white paper. Discover how your organization can overcome the barriers to AI adoption and turn experimentation into measurable business impact.