Enterprise AI leaders from C3 AI, Resolve AI, and Scale AI reveal how Fortune 100 companies are successfully scaling agentic AI from pilots to production and share secrets for successful AI transformation.
Topics Include:
- Panel introduces three AI leaders from Resolve AI, C3 AI, and Scale AI
- Resolve AI builds autonomous site reliability engineers for production incident response
- C3 AI provides full-stack platform for developing enterprise agentic AI workflows
- Scale AI helps Fortune 100 companies adopt agents with private data integration
- Moving from AI pilots to production requires custom solutions, not shrink-wrap software
- Success demands working directly with customers to understand their specific workflows
- All enterprise AI solutions need well-curated access to internal data and resources
- Software engineering has permanently shifted to agentic coding with no going back
- AI agents rapidly improving in reasoning, tool use, and contextual understanding
- Industry moving from simple co-pilots to agents solving complex multi-step problems
- Spiros coins new concept: evolving from "systems of record" to "systems of knowledge"
- Democratized development platforms let enterprises declare their own agent workflows
- Semantic business layers enable agents to understand domain-specific enterprise operations
- Trust and observability remain major barriers to enterprise agent adoption
- Oversight layers essential for agents making longer-horizon autonomous business decisions
- Performance tracking and calibration systems needed like MLOps for reasoning chains
- CEO-level top-down support required for successful AI transformation initiatives
- Traditional per-seat SaaS pricing models completely broken for agentic AI solutions
- Industry shifting toward outcome-based and work-completion pricing models instead
- Real examples shared: agent collaboration in production engineering and sales automation
Participants:
Further Links:
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