Does generative AI offer a positive ROI for your software team?

EngineeringMachine Learning (ML)

Yes, we’ve already proven it does27%

No, it’s not a good fit for us42%

Not sure, it’s difficult to tell25%

N/A — we’re not using it5%

55 PARTICIPANTS
501 views

Content you might like

How would you characterize your organization's current strategy for AI adoption?

Leading the charge within my organization13%

Following innovative vendors or verified case studies from my industry57%

Taking an employee driven/grassroots approach20%

Taking a cautious approach9%

Not currently focused on AI initiatives

View Results

Is your EDI in house or outsourced?

In house67%

Outsourced33%

What specific cloud storage features do you look for when designing AI or ML pipelines, such as indexing, metadata management, data processing integration, and high-throughput performance?

What advice would you give to a senior software engineer/developer who is on the fence about transitioning into leadership?

Read More Comments

I am interested in people who have tried generative AI coding projects.  In your experience, are there project attributes that make generative AI coding capabilities a "good fit"?  Are there project attributes that are likely indicators that generative AI will not result in something useful?  I would think complexity of requirements is a big factor.  If the complexity of the project or its requirements is low - I assume genAI coding can get you within the ballpark.  For instance, logic stores: if your project has critical business logic spread out all over the place and not centralized I think that generative AI would not be able to make sufficient sense of that.

Read More Comments