The current hype about AI has left many enterprise automation leaders feeling anxious about how they will integrate these rapidly evolving AI solutions whilemaintaining reliability and resilience. Hosts Dan Twing and Tom O'Rourke recommend taking a pause to recognize that there are more similarities than differences with past waves of integrations of new technologies into automation platforms. These integrations succeeded by following proven change management practices: start with small pilots, iterate based on learnings, collaboration with stakeholders, and maintaining production discipline. 

 

Key Points

·         AI agents are just another process type to be managed

·         Core automation principles remain unchanged, ensuring that the right actions happen at the right time applies equally to AI workloads

·         Technology adoption fails more frequently from coordination failures than from technical issues

·         Choose pilots based on readiness and suitability for an iterative, learning approach

·         Assess your observability capabilities, AI can introduce non-deterministic execution and outcomes, requiring a higher level of monitoring than traditional applications 

 

Takeaways for Automation Leaders

·         Invest in expanding your observability capabilities now, even there's no immediate need for AI integration.

·         Improve your teams cross-functional collaboration skills, focusing on business, technical and operations teams.

·         Be prepared, looking for your AI "learning candidate" automation use cases and platform touch points.

 

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