Hiring comeback ahead? Gartner says one in three jobs cut for AI could return by 2029 as firms face new reality

For the last few years, artificial intelligence (AI) has consistently made headlines for its ability to automate jobs away. From businesses discussing their ideas to adopt AI innovations and cut costs in favor of machines, to boardrooms contemplating how AI could be strategically integrated, AI has featured heavily on the agenda panels in discussions around layoffs.


But according to a Gartner prediction, there is a chance that many of these jobs will come back. Gartner predicts that at least 30% of the jobs lost due to AI automation could be created by 2029.

This is a surprising projection that suggests many firms could realize, sometimes painfully, that the jobs they laid off were more valuable than they thought.

Gartner highlights that the real value proposition lies not in simply being able to automate and reduce costs but rather how AI can augment the productivity of an organization. The implications of this prediction could have a deep impact on employment practices in coming years.

Every successful technology adoption has involved early adopters who realized the financial benefits of being ahead of the market. The promise of AI was faster, more efficient processing of information, which translated directly into higher revenues and/or lower costs.


For a business executive, this meant the ability to streamline operations and boost profits by reducing staffing levels.

For example, the introduction of chatbots in the customer service sector may have been heralded as a way to cut costs. While it may make financial sense to do so at first, the implications of this decision could hurt the firm in the long run. Some customers may still require assistance with complex issues, or they may expect to speak with a person for matters of emotions.

This can result in understaffing issues as the management would not have accounted for these specific applications of AI automation.

While it is often easier to measure the short-term financial benefits of layoffs, it is more challenging to estimate the long-term costs. Losing experienced staff means also losing hard-earned tacit knowledge of the business that can be difficult to replicate.

This could be extremely detrimental to the bottom line as inexperienced staff will require several months to acquire the same level of tacit knowledge as those who have been working in the firm for a while.

These expenses will need to be factored into the initial cost-benefit analysis of AI-driven automation that firms undertook before laying off staff. Additionally, any resumption of employment will incur additional costs to the employer as they will need to hire, train and on-board new staff from scratch.


For instance, in cases of mass resignations at a news media, marketing firm or tech organization, the remaining staff may struggle to meet the minimum requirements due to loss of tacit knowledge.

One of the aspects that Gartner’s prediction overlooks is the possibility of change in job titles. While it is possible that some firms may simply reverse any job losses they have incurred at one point, others could change roles to incorporate more technology. For instance, a company that had removed certain analyst positions from its payroll may realize the need to augment its AI analyses capabilities and hire several people to analyze the insights produced by AI.

Some roles may also require modification, such as hiring people to oversee how AI is used within the organization. Meanwhile, other firms may end up hiring extra workers to increase productivity after streamlining their processes using AI technologies.

These new changes could require an entirely different set of skills, as opposed to the ones that the laid-off workers had. New technologies usually require new sets of expertise; meaning firms that integrate AI into their business processes will likely need to recruit people able to operate and manage AI technologies.


Some of the primary reasons why organizations may find themselves in the position of having to re-hire staff involve the phenomenon of burnout, which has become a near-obsession among many leaders as it saves them tons of money.

Burnout happens when employees that have been retained following layoffs are forced to do more work than before. Not only is this a sound reason to be wary of AI automation, but it is also a sobering showcase of the risks of blind speculation in business decision-making. While it may make perfect sense to reduce staff by up to 50%, in some instances, the retained employees (those that were not laid off) may have a higher risk of burnout as they would have to do the work previously done by their counterparts that were downsized. This could significantly affect staff retention, as most workers are likely to walk out if they feel the workload is unsustainable.

Meanwhile, when companies are under pressure to complete more work, there is bound to be an eventual staff increase as a result of insufficient manpower. Firms that rushed to adopt AI technologies such as robotic automation may end up spending more on hiring than they saved when initially downsizing.

In the end, it can be stated that Gartner’s prediction suggests that companies could learn some critical lessons regarding the value of their employees and how best to realize the potential of AI innovation to support business objectives. If the prediction is correct, the next phase in the AI era could be significantly different from the one we are currently experiencing as businesses rethink their strategy, values and vision for the next decade.