There is widespread consciousness in the corporate world about the need to reskill employees and rethink the allocation of jobs as a result of AI\u2019s application in business. According to IBM<\/a>, business leaders expect that approximately 40% of their workforce will need to be reskilled in the next three years. The World Economic Forum<\/a> also forewarns of AI\u2019s disruption to current employment needs, predicting that automation will displace 85 million jobs while creating 97 million new ones, and that 1.1 billion<\/a> jobs will see a radical transformation in terms of what tasks they involve.<\/p>\n\n\n\n

Several businesses have already prepared themselves for this transformation by setting up reskilling initiatives for their employees. Notably however, these are for the most part private sector, multi-million dollar companies, including Walmart, JPMorgan, and Accenture, Amazon and Unilever.<\/p>\n\n\n\n

Amazon launched its Machine Learning University<\/a> back in 2016 to enable thousands of its employees to gain skills in tech, thus ensuring job security for its workforce while being able to embrace new AI technology and save costs by automating many workplace tasks.<\/p>\n\n\n\n

Unilever<\/a> launched a similar initiative in 2022, investing $77 million into the training and development of its employees. This focused especially on equipping them with future-oriented skills including data science, agile working, and digital expertise in manufacturing. The benefits of this investment were extensive, not only increasing the company\u2019s productivity by 41%, but also improving its employees\u2019 motivation by 49%.<\/p>\n\n\n\n

As these examples (and many more<\/a>) illustrate, there are significant and widespread benefits to be reaped from investment in reskilling. As well as reducing hiring costs, reskilling increases employee commitment and job satisfaction, and creates greater business agility by equipping its employees with broader and more flexible skillsets. This enables businesses to carry out new initiatives more efficiently by having an internal source of diverse talent.<\/p>\n\n\n\n

Nevertheless, according to Harvard Business Review<\/a>, only a small amount of businesses (17%) have embraced the reskilling challenge effectively. So what\u2019s hindering the rest?<\/p>\n\n\n\n

1. Reskilling initiatives are costly for businesses<\/h2>\n\n\n\n

Although there is a lot of evidence pointing to the economic benefits<\/a> of reskilling, costs<\/a> nevertheless remain the primary barrier preventing businesses from implementing retraining initiatives. The average cost of reskilling an employee in the financial industry is \u00a331,800<\/a>, which is nevertheless less than half the cost of the redundancy and rehiring process in this industry, averaging at \u00a380,900.<\/p>\n\n\n\n

However, in the majority of cases, the incentive to reskill isn\u2019t as clear cut as this comparison suggests. While there are countless statistics and articles pointing to the urgency of reskilling, and the economic benefits it can bring, the reality is that present demands nearly always take precedence over future ones. For the majority of businesses, this will mean that \u00a331,800 of their budget is going to go towards making profit in the short-term to keep the business afloat, rather than investing it in the reskilling of an employee who is satisfactorily performing all of their current duties. After all, investing in the future is wise, but it\u2019s also a luxury that many can\u2019t afford.<\/p>\n\n\n\n

The constant innovation of rapidly evolving technologies may also exacerbate the reluctance to invest in reskilling, as businesses leaders may think that by the time they see a return on their investment in reskilling, the technology will have advanced to a further level, rendering the reskilling they provided less up-to-date and useful. However, many business blogs<\/a> and articles highlight the importance of integrating AI into business as soon as possible, due to the cumulative benefits it can provide, and the time needed to build large, accurate datasets to feed the technology.<\/p>\n\n\n\n

Although approximately 75%<\/a> of businesses are estimated to benefit from reskilling their employees, this proportion is unlikely to have equal distribution over different business models, sizes, and sectors. Take the hospitality and retail industries, for example, which are known for high levels of staff turnover<\/a>. For many cases in these industries, there is less economic benefit to be had from widespread reskilling, especially since relatively few staff remain within one company long enough to make an investment worthwhile.<\/p>\n\n\n\n

This is reflected in the fact that young women<\/a> face the greatest threat to job displacement due to their high representation in customer-service based roles such as retail assistants, receptionists, and waiters. Similarly, entry-level roles<\/a>, which are typically filled by younger people, are more likely to be affected by automation than executive or senior management roles.<\/p>\n\n\n\n

Also, small to medium enterprises (SMEs) are disproportionately affected by the cost of reskilling, both in terms of paying for the training itself, and covering the workload of the employees while they are training. Compared to bigger businesses, which will have a larger talent pool and more expertise<\/a> to draw on, small businesses face greater costs because they have less access to resources, contacts, and accurate information. As well as this, they miss out on the benefit of having company-wide programmes that larger firms can use to increase efficiency and reduce the overall cost of reskilling per employee.<\/p>\n\n\n\n

The unequal distribution of the effects of automation across different sectors and demographics further complicates the issue of costs, particularly with employment diversity requirements. Indeed, with a long term view, businesses should prioritize the reskilling more vulnerable workers who are most at risk from automation, even if this does not directly benefit their economic interests.<\/p>\n\n\n\n

2. Lack of clarity surrounding present and future skillsets<\/h2>\n\n\n\n

Another barrier to reskilling is that many businesses do not currently have sufficient understanding of what skills their employees have, and, as a result, which areas reskilling should focus on. A recent survey<\/a> by McKinsey & Co on employees found that less than half of respondents say their companies have a clear sense of their current skills, and only 41% say that their companies have a good insight into which roles are prone to disruption.<\/p>\n\n\n\n

Understanding how well an employee\u2019s skills map onto a business\u2019 goals and needs is imperative to making any strategic decision<\/a>, particularly when this decision involves investing time and money for long-term benefits. It is also of critical importance for the overall integration of AI into the business world, with lack of skilled talent being cited<\/a> as the biggest barrier hindering AI integration and MLops. Given that AI is a tool to increase human productivity, the full benefits of the technology can only be reaped when employers take a more employee-centric view, understanding of what skills their employees have, what skills they need to develop, and thus how AI can enhance their performance.<\/p>\n\n\n\n

Most businesses will have an awareness of the growing skills mismatch, and the increasing demand for technology skills over the next 5 years. This is why there is already an unmet, and only increasing demand for tech professionals. The effect of AI does not stop here though, but is forecasted to disrupt practically all skills areas. According to McKinsey & Co<\/a>, there will be an overall increase in the need for emotional\/social skills and higher cognitive skills such as creativity, critical thinking, and decision making, but a decrease in demand for physical labour\/manual skills and lower cognitive skills such as data processing and basic literacy and numeracy.<\/p>\n\n\n\n

While these general trends might provide some insight for businesses in terms of what to expect in the near future, the impact of AI on employees and the forecasted skills mismatch will nevertheless vary between industries and individual companies. For example, despite the overall decline for physical labour and manual skills, they are expected to see an increased demand in the healthcare sector<\/a>, due to occupations such as physical therapy and nursing, where human touch is an intrinsic part of the service provided.<\/p>\n\n\n\n

Such discrepancies highlight the need for employers to take the initiative<\/a> to evaluate the skillsets of their workforce and decide for themselves how AI is best integrated, and where reskilling would be most beneficial. However, the rapidly evolving technology and insufficient understanding of it, as well as an uncertain economic climate may be hindering leaders\u2019 confidence to do this.<\/p>\n\n\n\n

3. Lack of centralized support for responsible reskilling<\/h2>\n\n\n\n

The final barrier considered in this article is the insufficient support provided by governments for reskilling initiatives. The recent Conference Board<\/a> Measure of CEO Confidence\u2122 for Europe by ERT found that 57% of CEOs are not optimistic that policy makers will take robust policy actions to address the growing skills shortages in the European labour force. Another 37% percent of CEOs said they are somewhat optimistic about it, and only 4% were very optimistic about it. This indicates that European businesses feel largely unsupported by governing bodies in addressing the skills gap in the labour force that is increasing as a result of AI integration.<\/p>\n\n\n\n

While some businesses might have been spurred on to take up the reskilling initiative themselves by the governments\u2019 lack of direction, the need for accessible and centralised reskilling programs is widely recognised. This would not only benefit employers, but also employees who might be reluctant to embrace new AI tools without official training and legislation to ensure its safe usage and data compliance. <\/p>\n\n\n\n

In the legal sector, for example, 40%<\/a> of professionals feel uneasy and unequipped to use generative AI in their daily tasks. According to Bernadette Bulacan, Chief Evangelist at Icertis<\/a>, this results from a lack of training and upskilling. She is hopeful that \u20182024 will be the year of change management, where enhanced training programs will ensure that seasoned legal experts stay agile in this digitally driven age\u2019. But so far, effective change management from the UK government has yet to be seen in practice.<\/p>\n\n\n\n

The Business, Energy, and Industrial strategy (BEIS<\/a>) committee has called on the government to address AI-driven skills shortages by reviving a taskforce similar to its Green Jobs Taskforce,<\/a> which advised businesses in various sectors how to develop skills and meet targets needed for a transition to net zero. Arguably, this guidance has now been provided, with the passing of the EU AI Act on the 8^{th<\/sup> of December. This has set out the first cross-sectional legislation for AI usage, calling for data usage transparency and human oversight of the technology.<\/p>\n\n\n\n}

In the opinion of Harry Yates, founder of BuildPrompt<\/a>, this will have \u2018tangible implications for reskilling as employees must understand the ever-evolving regulations and how to integrate compliant AI\u2019. This certainly represents the hoped for impact of the Act. However, in reality, it may simply make businesses slower and more cautious in their adoption of AI technology so as to ensure their compliance with the new laws. Overall, the Act only provides guidelines for AI use that any responsible employer would already be following; there still remains a lack of visible centralised support for reskilling, such as financial incentives or publicly funded training programs.<\/p>\n\n\n\n

However, centralised reskilling is certainly possible. For example, in 2017, the UK Government passed the Apprenticeship Levy<\/a> to upskill the UK workforce. This initiative funded employment-focused training through a tax on businesses who paid a wage bill of over \u00a33 million a year, thus making apprenticeship programmes accessible to a wider range of businesses, particularly SMEs<\/a>. While critics<\/a> highlighted the limitations of this scheme, and the Recruitment and Employment Confederation (REC<\/a>) found that over 50% of businesses would benefit from a reform of the Levy, this initiative was nevertheless an effective first step to addressing the anticipated skills shortage following Brexit<\/a>.<\/p>\n\n\n\n

A similar scheme, or a reform of the Levy that had particular focus on equipping employees with a working understanding of AI technology could be effective in providing concrete support for reskilling. This would help to ensure that businesses of all sectors and sizes can prepare themselves to safely and effectively reap the benefits of AI.<\/p>\n","protected":false},"excerpt":{"rendered":"

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