The future of the workforce depends on many factors, including those derived from demographic shifts and generational expectations. Among all the factors, however, technological advancements hold a particular place, as they have the power to change, not only the way we work, but also the way we live. While technology has progressed at an exceptional pace over the last several decades, continually introducing new innovations, the arrival of OpenAI's ChatGPT in 2022 caught many - including policymakers - by surprise.
The international community was divided, with some welcoming the progress for its potential benefits, while others pointing to the risks.One thing, however, was common for everyone. The breakthrough sparked widespread curiosity about what it might all mean and what might come next. Predicting future technological trends with certainty is challenging, as it depends on numerous factors and circumstances that can change over time. However, in a simplified scenario, the future depends to some extent on the choices we make today. In other words, where we focus our attention, what we work on and where we invest. For example, looking back, we can see that AI was a focus of attention long before ChatGPT was officially introduced to the wider public. Compared to 2010 September, Google searches for 'Artificial intelligence' and 'AI' had increased by almost 4 times by 2022 September, indicating growing public interest. News platforms mirrored this trend, as the number of articles and reports on AI increased fivefold over the same period. Academic publications on AI tripled, showing significant focus on AI research and development. Finally, since 2016, AI investment has increased more than six times. All these figures suggest that there was reason to expect innovation to take place in this field.
Predictions suggest that interest in AI continues to grow. Google searches are increasing, news platforms consistently report on AI and academic publications on AI and related topics are steadily rising. As of 2024, the AI market, including the development, production and implementation of AI technologies and services, was valued at over USD 184 billion. Projections suggest this growth will continue, with the market expected to surpass USD 826 billion by 2030.
These trends are clear indicators that new advancements and technological solutions should be expected in the field in the coming decades. But what does all this mean for the employment market in practical terms?
In simple terms, AI is a technology that allows machines to learn, think and make decisions like humans, performing tasks that typically require human intelligence. These tasks include learning, reasoning, problem-solving, understanding natural language and recognising the environment. Due to its ability to mimic human intelligence, AI will impact almost all aspects of our lives, including the way we work. Many routine and repetitive jobs, such as those in manufacturing, data entry or basic customer service, will be automated by AI. According to 'The Future of Jobs Report 2023' from the World Economic Forum (WEF),47 42% of business tasks will be automated by 2027. However, whilst AI is expected to eliminate some jobs, it will also create new opportunities. Nearly half the companies surveyed by WEF (around 49%) expect that the adoption of AI will create new jobs. Roles in AI development, data analysis, AI maintenance and oversight will become more prominent. Jobs that require creativity, critical thinking and complex decision-making will also see increased demand, as these are still areas where humans excel compared to machines. However, AI is not only here to displace our jobs or create new ones. It is here to complement our daily work routines, increase our productivity by releasing us from repetitive tasks and open space for us to engage in more creative or complex work. According to the WEF's 'The Future of Jobs Report', AI is expected to be adopted by nearly 75% of surveyed companies by 2027. Widespread implementation of AI will impact various dimensions of our lives, and the employment life cycle is no exception.
Just in relation to recruitment, it can streamline hiring by screening résumés, conducting initial interviews and helping with performance tracking and identifying training needs. Beyond that, it can help with the management of work processes; employee progression and performance management; dismissal decision; and selection for individual and collective redundancies – and it will do so either by performing tasks that used to be done by us or simply replacing them with more efficient processes.
All this has been aided by the recent rapid development of certain aspects of AI, such as Natural Language Processing (NLP) and Machine Learning (ML). NLP is a subset of AI that focuses on the interaction between computers and humans through natural language. It enables computers and digital devices to recognise, understand and generate human language, both text and speech. NLP is used in applications such as language translation, sentiment analysis, chatbots and voice assistants. ML involves algorithms that learn from data by identifying patterns and making predictions based on statistical associations. These algorithms can perform tasks such as generating summaries, performing translations, answering questions and classifying texts. In other words, ML allows computers to learn from data and make predictions or decisions without being explicitly programmed to perform the task in question.
Advances in NLP and ML promise sophisticated algorithms that can perform complex analyses and predictions with a high level of accuracy. This will impact the employment life cycle by offering predictive analytics to forecast workforce needs, optimise talent management and enhance decision making processes across various HR functions. Businesses that want to stay ahead will need to keep their hand on the pulse of these trends if they want to stay ahead.
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