3. Manage expectations
Although AI adoption is increasing rapidly, research shows that executives are less confident in harnessing the power of these intelligent technologies, says Fawad Bajwa, global head of AI practice at leadership consultancy Russell Reynolds Associates. Bajwa believes this decline is partly due to the gap between expectations of AI and what it can actually deliver.
Additionally, he advises CIOs to educate themselves on where, when, how, and to what extent AI can add value. „Having that alignment across the organization on what you want to achieve will allow you to measure trust,” he says. That, in turn, can prevent workers from searching for AI solutions on their own in hopes of finding a panacea for all their problems.
4. Review and strengthen access controls
One of the biggest risks surrounding AI is data leakage, says Krishna Prasad, chief strategy officer and CIO of digital transformation solutions company UST. That risk certainly exists in planned AI deployments, but in those cases CIOs can work with business, data and security colleagues to mitigate risks. However, when workers use AI without their involvement, they don’t have the same opportunities for review and risk mitigation, increasing the chances of sensitive data being exposed.
