With all the hype on AI comes a lot of noise, as you have probably seen with the number of IT security vendors emerging. How do you filter out signal from noise successfully with the vendors you choose to work with?

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Director in Finance (non-banking), 10,001+ employees
Reputation and recommendations from friends and contacts in the industry.  We spend a lot of time asking each other "Have you heard anything about this company? Do you know anybody using this?"
Chief Information Officer in Manufacturing, 10,001+ employees
Where are they in the market, their reputation, recommendations, and talk to their customers. Find out what their experience has been with a particular vendor. In the end, it boils down to your gut as to whether you want to partner up with them unless budget dictates the selection process. At that point gets the best bang for your buck.
IT Manager, Self-employed
On the AI universe there is not such thing as one size fits all. The first approach is to focus on those vendors that have reached the necessary development maturity and then filter them under the ones that have accomplished projects on your scope of work. The current AI advances are decent but is just the beginning.  
VP of IT in Manufacturing, 1,001 - 5,000 employees
Reputation and recommendation are the stable requirements.  However I also want to hear not just what technology they use but also how they use it, and why they use it.  Understanding their approach and way of thinking tells me a lot about whether they can do the job or not.
Assistant Director IT Auditor in Education, 10,001+ employees
The best approach is if you can test the AI vendor application that will allows your employees to run the application through the basics, find logic fails and other errors and give  large sample size for the AI to rebuild off of.  This will give you the confidence if the application is meeting your business objectives and goals.

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High policy intervention: AI is a serious threat and should be controlled even at the expense of accessibility27%

Moderate policy intervention: AI has the potential for misuse, and policy interventions are the only way to ensure safety72%

Low policy intervention: Developers and users of the technology can be trusted to implement most of the required safety measures1%



Cost structure26%

Lack of in-house skills to migrate / deploy / manage workloads on cloud51%

Security / governance compliance concerns17%

Lack of performance or features that you have on-prem but not the cloud4%


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