How are you exploring Generative AI in your business?

Business Applications Strategy Machine Learning (ML)

Working with our data science team31%

Working with a vendor58%

Not at all8%

Other (Leave a comment)3%

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Director of IT in Softwarea year ago

Via our AI CoE and across the business based on interest and need

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What are some less obvious or downstream opportunity costs you’ve encountered with AI implementation?

When it comes to a generic Enterprise Service Desk, what percentage of Tier 1 issues will be solved by AI bots rather than humans in 4-5 years?

>90%13%

50-90%54%

25-50%22%

<25%11%

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How successful have your AI agents been at meeting the goals your organization has set for them?

Highly successful 14%

Moderately successful 43%

Minimally successful 20%

Not successful9%

N/A — we haven’t deployed AI agents14%

Other (comment below)

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What is the one business pain point / challenge that you regularly face, that you wish AI had solved it? The problem could be a time consuming, routine task that is frustrating to handle. It may happen daily / weekly / monthly, and you may lose many hours on it which results in delays / added cost.

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‘AI’ Business Model – With many components flowing into the AI domain (cost, data, E&C, people, value, strategy, duplication of everything, etc.), I’ve started to think about splitting out ‘AI’ from the operating model and putting it into a separate legal entity. This way, I could manage a) risk and compliance, b) cost, c) resource allocation, d) governance, e) IP, f) revenue generation, etc.

Of course, this isn’t new in general, but I’m especially interested in how this approach could help with the ongoing challenge of ensuring compliance with data privacy and regulations related to LLMs and data access/usage over time.

My question: Is anyone else thinking about this, or has anyone already done it? I know there are examples in the literature, but I wanted to float this here for general comments and discussion.

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