Is your process for evaluating business use cases different for GenAI than for other technologies? If so, in what ways?

276 views3 Comments
Sort By:
Oldest
Chief Data Officer in Media5 months ago
Our approach is to find high-value use cases and opportunities, evaluate how much value different technical solutions will deliver, estimate the costs and timeline for each solution, and then choose the best technology or technology roadmap. GenAI has different strengths and weaknesses than other technologies, so the evaluation is different. However, looking at use cases in a binary way can lead to overengineering solutions. Just because we can use GenAI doesn't mean it's the right choice.
Chief Data Officer in Software5 months ago
GenAI is a productivity / efficiency tool.  I would evaluate the potential benefits of any tool to deliver process automation the same across use cases regardless of the tool I use to do it.  That said, GenAI solutions are not the best fit for some use cases.  Would I consider GenAI to automate portions of our customer support function?  Absolutely.  Would I consider GenAI to automate any legal or compliance-driven process?  Probably not - or at least - not yet.  
lock icon

Please join or sign in to view more content.

By joining the Peer Community, you'll get:

  • Peer Discussions and Polls
  • One-Minute Insights
  • Connect with like-minded individuals
VP of Data5 months ago
In our evaluation of business use cases, we prioritize assessing their alignment with strategic goals and their potential to increase revenues, reduce costs, or enhance productivity. We adhere to the 'Keep It Simple, Stupid' (KISS) philosophy, initially exploring straightforward solutions. This approach enables us to implement solutions faster and establish benchmarks for assessing more complex alternatives. Consequently, GenAI technologies have hardly ever made it to the evaluation stage, often because they may not be directly applicable to the use case, or because simpler solutions already meet our objectives effectively.

Content you might like

Extremely11%

Moderately70%

Slightly19%

Not at all

View Results
227 views
Director of Data4 days ago
In our implementation of Master Data Management (MDM), we primarily adopted a centralized approach using Microsoft Dataverse. This was key to resolving data quality and consistency issues in our Power Platform solutions, ...read more
1
61 views1 Upvote1 Comment
Director of Data4 days ago
In my opinion, Advancements in AI and related data field have significantly enhanced our Master Data Management (MDM) strategy by automating data quality, integration, and governance processes. AI algorithms help identify ...read more
1
32 views1 Comment

Cost of RPA products27%

Lack of developers who can code RPA applications44%

Amount of customization needed to automate business processes24%

Lack of RPA code maintenance resources4%

View Results
11.7k views5 Upvotes8 Comments