From 30% to 99% AI accuracy in production | Allen Jeter (Lattice)

In this episode of The AI Adoption Playbook, Allen Jeter, Director of IT at Lattice, describes how his team transformed internal operations by strategically implementing AI assistants across multiple departments. Starting with a clear focus on reducing manual work and response times, Allen walks Ravin through how Lattice built their first AI solutions, from an experimental chatbot using Okta Workflows and Pinecone to production-grade systems serving their People Operations and security teams. What sets Lattice's approach apart is their pragmatic focus on solving real business problems rather than chasing AI for its own sake. By identifying specific pain points, implementing security guardrails from the beginning, and deploying AI directly within existing workflows like Slack, they've achieved impressive adoption across the organization. Allen also shares invaluable advice for IT leaders looking to implement AI, emphasizing early experimentation, stakeholder involvement, and the importance of understanding your business problems before attempting AI solutions. Topics discussed: Implementing AI assistants for People Operations that provide 24/7 support for employee questions about benefits and company policies. Building a security bot that helps sales teams respond to customer security questionnaires faster, reducing bottlenecks and accelerating sales cycles. Evaluating the crowded AI vendor landscape with specific requirements rather than getting caught up in marketing hype. The importance of integrating AI tools into existing workflows like Slack channels to maximize adoption without changing user behavior. Creating effective prompt engineering strategies to help teams customize AI responses and maintain accuracy across different domains. Implementing proper governance and permissions structures that respect existing data access controls to ensure compliance. Measuring success through concrete metrics like reduction in manual work hours and decreased time-to-answer across departments. Using AI to enrich support ticket metadata automatically, enabling better insights without manual categorization work. Balancing experimentation with security guardrails to enable innovation while protecting sensitive company and customer data. Resources Mentioned: Credal’s blog post, “The Enterprise Adoption Curve: Lessons Learned So Far”