AI governance

For telecom CIOs, the case for reinvention is no longer theoretical. The pressure is immediate, the expectations are rising, and the cost of delay is growing every quarter. AI has moved from promise to practical necessity, and with increasing demand for AI soutions, the need for governance is only increasing.

Keeping track

CSP IT architectures typically contain hundreds or thousands of significant components. Managing AI at this scale requires accountability, audit trails and guardrails to be in place. 

Standards and best practices are needed

Organizations need to know that their solutions are:

• Effective – do the job they are intended to do
• Safe – predictable and can be controlled
• Proportionate – achieves their role without undue effort or costs

Organizations can ensure that these objectives are met by adopting standards that help to provide a framework that demonstrates proper control of AI to the satisfaction of internal stakeholders, external regulators and customers.