AI shaping Future of Workforce

The potential for AI to underpin and grow the world of work is unbounded. AI’s advances and impact on society cannot be stopped. While AI should not be hyped, it should never be underestimated. It plays an essential role in matching skills to employer, capital to investor and consumer to supplier. Growth in AI brings a digital value chain and commoditisation and automation of tasks – but comes with warnings.

According to Gartner by 2026, over 100 million people will engage with AI to contribute to enterprise work. By 2033, AI solutions, introduced to augment or autonomously deliver tasks, activities or jobs, will result in over half a billion net new human jobs. The path to AI adoption has been gradual, but now is occurring at a breakneck pace. In fact, ChatGPT set the record in early 2023 for the fastest growing application ever. AI is beginning to display signs of emergent behaviors, or behaviors that are unexpected or unusual.

AI is already displaying signs of agency or the capacity to act in a certain context. We are beginning to trust AI to make decisions for us, in an autonomous way. We should assess new advances in AI as actions that influence our environments and actions, not just processes and systems. We should embrace advances in AI, such as ChatGPT, and take a proactionary approach.

Through 2026, despite all the advances in AI, the global job impact will be neutral — there will not be a net decrease or increase. This is primarily due to enterprise adoption lags, implementation times and learning curves. We need address fears of potential job losses incurred from AI technology advances by emphasizing the goal of AI is to augment human capability, not replace it.

AI will continue to innovate, sometimes at a breakneck pace, making it challenging to control. Fundamental progress in AI combined with responsible and ethical use of AI will create a thriving marketplace.

And with AI pervasiveness comes vulnerability to cyber-attacks or wide-scale manipulation. We cannot foresee all consequences. We can learn only through development, experience and acceptance of making mistakes. We should work on cutting-edge use cases and AI governance simultaneously. Be aware of the risks that come with deploying advanced AI.