So, what should we do with AI?
The near future will be dominated by a phase of rapid adaptability for the human workforce: either in implementing the technology of the AI revolution(“ the machine”), in architecting the workforce of the future(“ the human”), or in laying the foundations for this hybrid workforce( data, or“ the fuel” for the revolution).
Human oversight skills and roles will need to develop alongside the AI revolution.
As businesses configure operations around a hybrid workforce of humans working synergistically with AI and data systems against a vision, actioned through sophisticated hardware and software, businesses will need skills in these areas as part of a talent pipeline.
In some companies, entirely new job categories are emerging( think“ AI supervisors” or“ prompt engineers”) where employees spend their time steering AI systems and vetting their outputs. Existing roles in ethics, governance, and data validation will need to be part of that talent pipeline( as these roles change to encompass AI), there will also be roles that are exclusively for humans to interact with other humans( think“ coach” or“ mentor”).
Maintaining a human in the loop is often essential not just for quality control, but also for ethical and safety reasons, ensuring AI decisions align with societal values and readiness. Human oversight skills and roles will need to develop alongside the AI revolution. A good example is the technology capability for autonomous vehicles versus the societal and regulatory readiness to allow vehicles on the road without human drivers. Although it is possible, we are not ready to allow it to happen.
Despite the risks, AI can support the development of mental models and act as an accelerator for learning, and a catalyst for rapid upskilling, aiding human cognition, maintaining skills plasticity, and changing how we work, providing it is used to augment human capabilities and not only to replace them. 21
Actions for leaders
The challenge ahead is twofold: technological( integrating AI into operations) and organizational( reshaping the workforce and culture).
First, leadership must develop a clear AI vision that includes a complementary talent roadmap with purposeful transformation as a force multiplier for competitive advantage. Too many companies jump into AI projects without aligning their workforce strategy, leading to employee confusion or resistance. It’ s vital for executives to articulate a vision of how AI will be used and why, using technology acceptance and adoption research as a guide for managing change.
The Kyndryl Institute Journal 53