Genesys Casual

Dear community,

Came recently across this read: The Never Normal: When Change Becomes the New Normal and interested in your point of view and experience with continuous change and continuous improvement practices in your organisations. And specifically on how you manage to continue experimenting with AI while also achieving a consistent adoption of new and improved AI enabled workflows? Is this something being discussed in your teams? And how does it work in practice, what are the new routines or systems you have put in place to support the process of changing while walking together?

Thanks,

Valentina 

#General #AITransformation #ChangeReadiness #AdvisoryServices

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Valentina Postelnicu
VP Advisory Services
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Hi Valentina,

Great topic.

Yes, this is something we have been discussing as a team. One practice we have been using is having each team member share real situations where AI has helped in their daily work.

I think this is important because it moves the conversation away from theory and brings it into practical examples: what worked, what saved time, what still needed human review, and what could become part of a standard workflow.

In my experience, AI adoption becomes more consistent when it is organized by workflow, not used only as a generic tool.

One approach that has worked well for me is creating specific AI agents or prompt configurations for different activities, such as meeting summaries, functional documentation, test scenarios, client-facing emails, discovery questions, flow reviews, and technical explanations.

Each prompt or agent has a clear context, expected output, tone, restrictions, and validation criteria. This helps make the AI output more consistent and easier to review.

In practice, AI saves time by reducing the "blank page" effort, organizing scattered information, improving documentation structure, and helping identify points that need validation before development or go-live.

But I still see human review as essential. AI supports the workflow, but the business context, technical validation, and final decisions need to remain with the team.

For me, the key is continuous improvement: share practical use cases, define the task, create a reusable prompt or agent, test the output, adjust, validate with the team, and then make it part of the routine.