October 2025 · Agentforce
Common adoption challenges
- Unclear business objectives — deployments stall without specific KPIs
- Poor data quality — AI agents perform poorly on incomplete or inconsistent data
- Complex integrations — connecting to legacy systems increases cost and timeline
- Change resistance — teams resist without sufficient training
- Underestimating governance — risk of data exposure without clear policies
- Insufficient post-go-live optimization — agents need continuous tuning
Proven best practices
- Secure executive sponsorship across IT, ops, and end-users
- Invest in data readiness before rollout
- Leverage MCP and low-code tools for integrations
- Run a phased rollout — pilot first, then scale
- Prioritize role-specific training
- Establish governance frameworks from day one
- Iterate continuously using Command Center metrics
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