What has been your primary challenge in developing a business case for GenAI in your organization?

Generative AI

Accurately forecasting costs11%

Identifying realistic benefits34%

Scaling effectively23%

Getting executive buy-in14%

Training team members in GenAI use4%

Finding the right areas for deployment6%

Protecting against risks5%

Something else (please specify in comments)4%

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CIO in IT Services8 months ago

Choice of use cases by the business and corresponding choice of technology is also a blocker

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What are key ways in which your organization should hire affordable AI and data science talent? (Check all that apply)

Recruit talent from diverse or non-traditional backgrounds (e.g. different degrees, institutions, or work experience)32%

Recruit less experienced AI talent with a high aptitude to learn 52%

Communicate the intrinsic benefits of the role (e.g., mission, culture, resources, opportunity for impact) 39%

Build talent pipelines through partnerships with academia and professional societies35%

Hire and upskill internal talent39%

Use specialized AI recruitment agencies10%

Other (please share details in comments)

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Has anyone successfully implemented ChatGPT or Microsoft CoPilot for everyday IT tasks such as resolving service desk tickets or answering internal policy-related queries?

How well are you tracking and managing token costs for your org’s GenAI tools? Are you able to accurately predict usage, or have costs been difficult to estimate?

Should software teams have fewer restrictions on GenAI tool usage than other departments?

Yes, they need more flexibility48%

No, all departments should have the same restrictions39%

No, they need more restrictions13%

I'm undecided

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What’s the best way to push back against a leader or peer who’s overzealous about adding AI where it isn’t needed?

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