In the media

Are Friends Electric?

By Dean Collins, Adam Bertelsen

HR Director

16 January 2024

GenAI will undoubtedly disrupt jobs and careers. Yet it is hard to envisage a scenario where ‘AI can do everything’ in 2024. In the short to medium-term, significant human intervention is still needed to design and use most GenAI systems, particularly in cases where ethical judgement is needed. This is particularly true of the Diversity, Equity & Inclusion agenda, where GenAI has already been proven to exacerbate existing biases when deployed without human oversight.

As the relationship between technology and humans evolves, management structures and team working styles also need to adapt with it. For HR teams it will be these individuals also acting as the frontline to the business, making it imperative that they have the knowledge to critically evaluate decisions and the experience to handle potentially sensitive topics delicately.

We can expect to see two different scenarios start emerging in 2024 that will become embedded as divergent AI workforce models over the next five to ten years. Some organisations will move towards replacing predictable and repeatable tasks – and eventually roles – with GenAI. Introducing GenAI systems that can interface directly with customers, automate processes and deliver short-term cost savings holds a clear appeal.

In the year ahead, these organisations will likely start using GenAI to target the creation of a more intelligent organisation – the ‘Intelligent Enterprise’ – where key operations and core business processes will be entirely AI-powered. For HR teams, process-driven functions such as Talent Acquisition and Operations could be pre-determined by GenAI to speed up decision-making, with select groups of experts still required to ensure no bias is reflected in its decisions.

Towards the other end of the spectrum, many organisations will increasingly focus on ‘augmented intelligence’ in 2024. In other words, empowering employees from the bottom up to utilise GenAI and carry out new AI-enabled tasks that can deliver additional value directly to both consumers and themselves.

This is a more likely scenario for many organisations, given advanced GenAI systems will continue to be prohibitively expensive – both economically and environmentally – for the near future. For a wide range of use cases, humans will continue to deliver more efficient value, whether that be across social work such as in hospitality or the care sector, or unpredictable physical jobs such as in maintenance and repair.

Where GenAI offers tremendous opportunities for organisations such as these is in augmenting existing workforces by delivering new 'additive' products and services – for example, for field force technicians to be able to complete advanced diagnosis of issues using GenAI and computer vision, or for nursing staff to provide new services, such as technical advice on insurance claims using GenAI assistants. We’ve seen this before with the introduction of computing and the internet into the workplace; the switchboard operators of yesterday became the contact centre agents of today. For many, GenAI will become an additional tool that enables them to focus on the more creative and advanced elements of their role. A counterpart, not a replacement.

This type of 'augmented workforce’ will require organisations to upskill their workforce and give employees a real say in how they use GenAI technology – both next year and beyond. Instead of eliminating jobs, this scenario could see even larger teams of mixed frontline, knowledge and GenAI workers ingeniously collaborating with GenAI agents and co-pilots to deliver new products and services. Teams of highly skilled people to maintain the technology will be required, whilst every person in the organisation will need a baseline understanding and skillset in utilising GenAI. Training and skills development in areas such as Prompt Engineering will therefore be critical to an organisation’s success at adopting GenAI into their ways of working.

The global fight for top technical talent is unlikely to slow with GenAI in 2024, however, it won’t be won on reward alone. Whilst the demand for deep technical GenAI and Machine Learning specialists is likely to increase, organisations need to determine how they are going to attract the skills and experience they need to fully adopt and exploit the benefits of GenAI. HR leaders should define a compelling Employee Experience (EX) and Employee Value Proposition (EVP) over the next 12 months that attracts the right talent and plays to their organisation’s strengths and cultural values.

Looking beyond 2024, as advanced GenAI models become increasingly common and commoditised, the demand for skills will likely shift away from technical expertise towards how GenAI can be applied to products and services. Demand for adjacent roles and skills – such as Product Management – is likely to increase such reward and lead to further focus in those disciplines.

There is a real opportunity for lower-skilled workers to use this commoditisation of intelligence to their advantage by retraining and building their experience in relevant disciplines. People currently going through higher education could learn and adapt to new GenAI skills and, as a result, bring their own advantages to the workplace. Rather than planning long-term careers, future applicants should focus on building a set of transferable skills which enable them to work collaboratively with GenAI.

In 2024, workforces have a chance to use the knowledge and power of GenAI to springboard new ideas into reality faster and more accurately than ever before. The steps that HR teams take today will ultimately shape the direction of the workforce tomorrow. For human-centred AI adoption to thrive, organisations must build a culture that fosters innovative thinking, nurtures new ideas, and attracts the right talent. HR leaders will need to think creatively to adjust to this new world: the stakes are high but it’s all to play for.

This article was first published in the HR Director, January 2024, and has been reproduced with permission. Read the full and original article.

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