Enterprises are increasing AI spending for customer engagement but seeing limited returns due to fragmented data architectures. A significant portion of companies report their data is not ready for AI, citing data silos and integration difficulties as major obstacles. The proposed solution involves re-architecting the end-to-end customer value chain to integrate AI intelligence, ensuring that AI models are trained on complete fulfillment and billing outcomes, not just initial engagement metrics. This approach aims to improve decision-making, create seamless customer experiences, and accurately measure AI's business value. AI
IMPACT Highlights how fragmented data architectures hinder AI's effectiveness in customer engagement, suggesting a need for integrated systems to realize true value.
RANK_REASON The item is an opinion piece by an industry expert discussing challenges and solutions in AI customer engagement.
- Capgemini
- Customer Experience Optimization
- customer relationship management
- Forbes Technology Council
- Hemant P Soni
- OSS/BSS
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →