Twelve months ago, who would have predicted that we would be talking about AI as part of our everyday lives? This ground-breaking technology, characterised by its ability to create content, solutions and even artistic creations autonomously, is reshaping workplaces and industries in unprecedented ways.
References to the impact of generative AI are evident in industries such as marketing, where automated content creation has streamlined campaigns; and in design, where AI-driven tools assist in generating complex images. These applications highlight the efficiency gains and showcase the creative augmentation made possible by generative AI.
Generative AI presents Human Resource with evolving goals and challenges. As businesses adopt generative AI, HR departments are tasked with aligning talent strategies with the demands of an increasingly automated workplace. The goal: optimising the collaboration between human and AI counterparts.
Some of the trickier challenges in this domain include ensuring ethical and unbiased AI applications, upskilling the workforce to adapt to these new (and often foreign) technologies, and navigating the evolving landscape of talent acquisition and management in an AI-driven environment. By exploring these intersections of generative AI and HR dynamics, we gain valuable insights into how businesses are making this fusion of technology and human capital work most efficiently.
A statistic to put this into perspective: It took Chat GPT two months to reach 100 million users—it took Instagram thirty months to do the same… and we were impressed then!
How Did We Get Here?
The evolution of AI spans four generations:
First there were rule-based systems, such as Applicant Tracking Systems (ATS). These automatically screen resumes and applications based on predefined criteria such as keywords, skills, experience, and education; and they can be programmed to reject applications that do not have the ‘must have’ qualifications. This progressed to machine learning. These systems could learn from data and make predictions, rather than following a set of predefined rules. Next came Deep Learning, a type of machine learning that used artificial neural networks to automatically adapt and learn from experiences which gave us things like Chat bot interfaces.
And now we have Generative AI, the 4th generation that focuses on creating new content that resembles the data it was trained on. In HR, this has included automated content generation– writing global mobility policies, creating personalised emails, rewriting job descriptions, creating personalised messages for different employee cohorts, helping word that tricky performance review, formulating compelling pros and cons for tech investment, and even making a start on FAQs for any new process.
We are also seeing its application in Scenario Planning and Simulations. Generative AI can be used to stimulate different HR scenarios, such as changes in the workforce, shifts in hiring or skills needs or the impact of new HR policies. And it can even create Personalised Career Development.
What Does the Data Tell Us?
Kate Bravery, Global Advisory Solutions and Insight Leader at Mercer, shared insights with us from Mercer’s upcoming Global Talent Trends study (due to be released formally in the new year), covering 17 markets and 16 industries with over 12 thousand interviews. The study shows C-suite executives worldwide expect generative AI to drive business growth and workforce productivity, with 13% of executives believing that most of their workforce is ready to adapt if their jobs are fundamentally changed or eliminated by AI and automation. Perhaps more interestingly, over half believe their company will not survive if they don’t embed generative AI.
But do the employees agree with this perspective? The data shows that 1 in 10 employees believe that their jobs will be replaced by AI or automation in the next three years. This is where a challenge will present itself for businesses and therefore HR. This amount of change will impact roles and many are planning RIFs next year to adjust. The question now is how does an employee retain trust in their organisation’s leadership team that they will be re-skilled and redeployed if their role is eliminated?
But for many individuals, organisations, and HR leaders, there is a lot of information out there already. The concern is that many employees don’t rate their company’s efforts highly at keeping them informed about the technology and the potential impact on skills needed tomorrow.
But Where Do We Actually Start?
Noel Brown, Global Head of Talent Acquisition at HSBC, shared with us the innovative spirit and curiosity that employees and leadership teams alike have across HSBC. To keep track of possible ideas and implementation, they have set up an AI tracker that has over 1,000 use cases possible for AI across the business. With this are AI Ambassadors and AI Governance committees to keep the conversations and ideas flowing. They evaluate live uses before rolling out those out that “pass the test”. Equally, they dismiss the use of inappropriate AI, which is just as valuable an exercise.
One of the ideas was piloted in countries where spiking attrition levels were proving a problem. The usual review of performance levels and compensation benchmarking were conducted before it was decided to see if AI could offer a different perspective. The team attempted to manipulate the AI to help predict the whereabouts of the attrition so that with advance warning, necessary adjustments for the relevant individuals could be made. It would happen in real time so that they would be ahead of the curve. In one instance, the data showed that more men were leaving than women. In this case, had they adjusted compensation, the issue would have intensified further down the line.
The moral of the story is use the tools and look at the data, but harness the enthusiasm responsibly to ensure that decisions made are sound.
Can AI Ensure Inclusivity?
A challenge for any organisation is ensuring its DEI agenda is watertight. This is a tough ask, but AI could potentially help.
Caroline Vanovermeire, Global Director of Talent, Leadership and Organisational Development at dentsu and Founder of Effra Consult has done a lot of work looking at how AI can work within all stages of the talent acquisition cycle. In her view,
Use AI to automate as much as possible, process-wise, so you can make the interactions better from a UX, from skills and culture add, not fit, add perspective. Use AI to ensure that human bias cannot slip in at the sifting stage and is subsequently used in accelerating performance through a hyper-personalised onboarding once they start, especially if they are currently representing an underrepresented group in your organisation and therefore might currently still be an “outlier” as you are lucky to have them and the focus should therefore switch to retention and engagement.
This will then also have a direct impact on the learning and development of the team. Caroline explained how she has worked with organisations that have combined bots and real-life humans to create a hybrid coaching experience. She has used AI to customise and hyper-personalise the learning offering, which ironically includes upskilling on AI.
The benefits of AI-enabled learning are significant. Some may also say that AI can make learning and education more accessible for all and create a fairer society.
Around 15 per cent of the world’s working population live with visible or invisible disabilities (and that number is increasing sharply). These people represent the world’s largest minority. Can AI help organisations to employ people with disabilities? Hopefully, as the biggest obstacles typically are the traditional processes and approaches of the past.
Employee Data and Generative AI
As a custodian of substantial employee data, HR naturally accumulates and manages a wealth of sensitive information. This data, historically stored across various platforms, is now intersecting with the impact of generative AI. With the exponential growth of ChatGPT’s usage and the subsequent creation of new content globally, there is a growing awareness that all input and shared data could potentially enter the public domain.
Governments worldwide are progressively formulating legislation for companies to adhere to in their handling of data. However, these regulations have yet to catch up with the rapid integration of generative AI into business operations. In this context, how can HR teams ensure robust regulations to safeguard employee data?
Kirsty Jucker, ChapmanCG’s Managing Director for Operations, has this topic high on her agenda. In her perspective, a combination of regular training and awareness programs, technical safeguards, and policy development emerges as a fundamental strategy. Educating the global team about the limitations of generative AI and security considerations, irrespective of their position or role, stands as a cornerstone. Firm policies have been established, emphasising a critical principle – no personal or confidential information should ever be shared through a public generative AI application. Regular review of policies and practices is also conducted as the technology landscape evolves. Moreover, when assessing potential partners and service providers, how generative AI is integrated into their platforms and how it interacts with data in the public domain is fully scrutinised.
Leadership and Employee Alignment
Buying full access to ChatGPT for US$20 a month was one of the first changes Noel made on arrival at HSBC. He has encouraged all his team to do the same, giving them full access to the possibilities of AI. Trying things for yourself and experimenting is crucial. He also remarked on a speaker that shared insights on changing the dynamic of leadership teams. As a general rule of thumb, Boards consist of individuals in the latter stages of their career. Sometimes these individuals are less inclined to embrace the dynamism of generative AI. How can boards incorporate more thirty- and forty year-olds who could also be learning from their own offspring (who have gotten to new technology before them)?
What about reverse mentoring? As Caroline suggests, this concept has been around for decades, and it is well known that if the more senior individual is open to learning and curious, they can gain the most from the so-called “lower-scale” in the organisational hierarchy.
From the Mercer data, we have seen that employees expect to be re-skilled if their job is at risk. That is a challenge as one would expect employees to proactively look to their futures. In HSBC, they have started to look at where there is potential for automation, and therefore, where there is job risk. They have created a workflow and documentation clearly for all potential employees to look into. Again, using the real-time data, they are able to understand where some roles may have to be adapted earlier than others. It is a larger workforce management process that AI is influencing but can also assist, always ensuring that there is a sense of human intervention to ensure that the decisions are sound.
Where Do We Go Next?
There are different platforms to investigate such as ChatGPT and even Microsoft recently launched their AI assistant known as MS Co-Pilot. The terminology used here is interesting: As a “Co-Pilot”, AI can and should be seen as a collaborator. If you watch Kate’s presentation below, you will see how Mercer has used it as an avatar/panellist.
Through these examples, we hope that the seeming “sudden emergence” of generative AI can now be viewed as a potential support pillar for businesses. Generative AI should be perceived as another valuable tool at our disposal. It is important to reiterate that genuine human interaction and collaboration remain at the core of progress and decision-making—this is what will remain indispensable. New technology can streamline processes and enhance efficiency, but the true wizardry and power unfold when this is combined with human creativity, empathy, and critical thinking. Ultimately, generative AI stands as a facilitator, but it is the collective synergy of human minds that will continue to steer organisations and employees towards greater heights of achievement and innovation.
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