Assessing the practices of a responsible AI provider

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Responsible AI programs “must encompass both in-house and third-party AI tools,” the report’s authors urge. “The same ethical principles should apply regardless of where the AI ​​system comes from. Ultimately, if something goes wrong, it won’t matter to the person who is negatively impacted whether the tool was built or purchased.”

They warn that “there is no silver bullet tMany IT leaders feel their infrastructure and IT teams are not ready for AI
16.06.2023
Equinix's 2023 Global Tech Trends study found that enterprises plan to increase IT hiring and adopt digital twin technology, but most say meeting environmental regulations is a challenge, ITPro Today reports.

The research builds on a global survey of 2,900 IT leaders this spring on technology trends, sustainability, IT hiring plans and the top threats to their organizations' business success.

Many businesses are adopting artificial intelligence to azerbaijan mobile database their IT and business operations, but research shows that a significant percentage of organizations do not have the necessary IT infrastructure or in-house expertise to take full advantage of AI.


Today, 85% of global IT leaders are already using or planning to take advantage of AI. However, 42% doubt that their existing IT infrastructure can handle AI demands, and 41% are unsure about their IT team’s ability to handle the growing use of AI.

IT leaders in Europe, the Middle East, and Africa (EMEA) are the most unsure about their infrastructure’s readiness for AI, with 49% doubting their infrastructure can handle AI workloads, followed by 44% of IT leaders in Asia Pacific and 32% in the Americas.

How to Prepare Your Infrastructure for AI
o mitigate third-party AI risks or any type of AI risk” and that a multi-pronged approach must be taken to ensure responsible AI in today’s wide-open environment.

Such an approach may include the following:

contract language requiring adherence to responsible AI principles;
pre-certification and supplier audit (where possible);
internal product-level checks (when a third-party tool is integrated into a product or service);
compliance with relevant regulatory requirements or industry standards;
Including a comprehensive set of policies and procedures, such as guidelines for the development of ethical AI, risk assessment systems, monitoring and audit protocols.
The specter of legislative and government mandates could make such actions necessary as AI systems become more widely deployed, the researchers warn.