In your opinion, what’s the biggest risk of using generative AI for coding?

Software Development Machine Learning (ML)

Poor quality code20%

Cybersecurity problems48%

IP/copyright concerns22%

Disrupted processes2%

Lack of attribution1%

Data leaks2%

Budget creep

Something else3%

No risks

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Has your organization had to modernize legacy systems in order to integrate with GenAI tools or capabilities?

Yes89%

No11%

Do you believe that (RPA, Automation, and intelligent Automation), coupled with clear guidelines, robust process mapping, and effective monitoring and control capabilities, can serve as a key enabler for successfully integrating AI and GenAI into an organization's operations and strategies?

Strongly Agree25%

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Disagree15%

Strongly Disagree1%

View Results

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.

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Software Engineers often get pegged as the team that says “no” or “that’s impossible”. How do you maintain a strong and trusting relationship with the product team while continuing to reset their expectations?

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