AI may be developing at a fast pace, but global workforces are currently not skilled enough to handle such rapid changes.
The technology holds great potential to transform the global business landscape, boosting productivity and improving workplace efficiency. However, whilst companies are keen to invest, they do not have the skills required to handle AI, so it is not utilised to its full potential.
Research conducted throughout 2023 found that many employees feared being replaced by AI, contributing to workplace anxieties. However, HSBC found at the start of 2024 that most businesses are considering how AI could advance employee skillsets, with 83% surveyed planning to re-train their workforces to better utilise the rapidly developing technology.
As AI continues to play myriad roles moving forward, one thing is absolutely certain - it will impact nearly every job.
Big tech companies are already starting to enact transformational changes in favour of boosting AI. SAP, for instance, recently announced plans to focus on upskilling workers and driving growth in AI business areas.
In a rapidly changing digital landscape that sees businesses continue to be impacted by threat actors exploiting business infrastructure, the need for employee upskilling is crucial. As a result of AI technology developing at such a fast pace, there are ever-increasing talent shortages within the technology sector that need addressing.
IBMs Global AI Adoption Index found that a lack of relevant skills was the top barrier to AI adoption among UK enterprises. Jon Lester, VP of HR Technology, Data and AI at IBM explains that this is why upskilling for AI is arguably the most critical development area for the workforce moving forward.
Employees who are seen as domain experts will still be highly sought-after as they are the ones who will help to develop and train AI, he says. We have seen some of our support desk employees who have the highest customer satisfaction when answering phone calls or responding to emails, reskill to become conversational specialists who design chatbot interactions that provide a great end-user experience.
Those same people are now learning to become prompt engineers who are training large language models to generate responses to questions. AI is measurably moving domain experts to higher value work.
In recent months, the business landscape has changed beyond measure, with AI-related skills no longer considered desirable - but necessary, across the majority of job sectors. AI has ultimately opened up new opportunities and challenges by development teams, as businesses must retain their employees to satisfy AI demands.
Research conducted by ServiceNow found that the majority of office workers already use generative AI (Gen AI) for tasks like drafting content (69%), transcribing meeting notes (66%) and reviewing documents (65%). However, ServiceNow also found that almost half of workers still dont understand how AI can best support them in their role, suggesting that employers are still not making the most of the technology.
In the future I predict that we will see all jobs be categorised into two buckets: sunrise jobs and sunset jobs, the companys Area VP of Solution Consulting, Simon Morris, says. Sunset jobs are at risk of being significantly disrupted by AI and may eventually be replaced. Sunrise jobs will also change as they are enhanced and supported by AI.
In the future your job will involve training, supervising and correcting the algorithm rather than completing the task yourself.
As Akhil Seth, Head of Open Talent at UST, explains, AI is no longer simply a piece of innovative technology. In the maturity curve, it is now an implementation technology, he says. Companies should be looking to acquire a workforce that knows how to implement AI based solutions.
Having a workforce that is well acquainted with deep machine learning infrastructure skills as well as the critical thinking required to apply the technology to business initiatives will be critical in maintaining a competitive edge.
In line with such rapid AI advancements, business leaders are now seeking to develop new strategies that adopt an AI-as-copilot approach. Put simply, this means having AI work alongside human employees.
IBMs Jon Lester identifies three key emerging areas within AI that are already driving new skillsets, citing code generation, customer engagement and the concept of a hybrid workforce.
These emerging areas for AI are driving speed of task completion, improving decision-making for managers and leaders, and enabling significant productivity gains for employees, he says. What educators and professionals need to think about is how to ready the organisation for this seismic change.
Simon Morris, meanwhile, envisages a future where it will be normal for AI to suggest ways to develop employees or even assign workers to projects, tying employee learning closely to workforce planning, all while also ensuring they feel more fulfilled in their jobs. This will in turn not only result in talent retention, but also more satisfying customer experiences, creating a positive ripple effect on a business bottom line.
What is becoming clearer is that the human element to AI will remain integral to business developments, with companies working to address ethical challenges. With this in mind, ensuring that workforces can fully harness AI will be necessary, particularly when it comes to sectors like cybersecurity.
Increasing numbers of business leaders around the world have called for AI risk training in a new age of digital threats, in addition to ensuring that employees can handle the technology when things go wrong.
So, how can companies best upskill their workforces in the age of AI?
Jon Lester says that understanding the difference between traditional and generative AI will be key for businesses, so that employees can develop skills from a clear benchmark.
The pace of change that AI is creating means that the AI skills you learn today may have a half-life of less than three years and so a mindset of continuous development will be required to keep skills up to date, he says.
Ultimately, the onus is on the employer to ensure that their workforces are up-to-date with existing AI strategies and are adequately trained to propel the company forward to enact real technological business transformation.
This can be in the form of regular training courses and workshops with external organisations that can provide industry-leading expertise. It is also important that employees are given the opportunity to gain practical experiences and implement real-world AI projects, Morris comments.
As Seth concludes, organisations need to establish ongoing training programmes for employees. Workshops and online courses allow workers to acquire new skills and update existing ones. Another priority should be around customised training, ensuring that the courses are tailored to the companys specific needs, given that the applications of AI can vary widely from industry to industry.
Companies need to get the workforce comfortable with playing with AI tools and nurture a sense of curiosity around them. Companies that enable workforces to play with large language models (LLMs) will undoubtedly stumble upon market-defining use cases for the technology.
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