From automation to augmentation: HR’s role in the generative AI revolution

Why do we work? What do we get out of it? These two questions need to be at the heart of decisions about the use of generative AI if we want to flourish as humans, says Lynda Gratton, professor of management practice at London Business School.

Productivity gains may be driving CEO and shareholder excitement about generative AI but if we lose sight of the fact that, for many, work transcends the fundamental necessity to earn a living, then in a generative AI world it becomes entirely transactional and devoid of meaning.

In an insightful webinar for MIT Sloan Management Review, Gratton said: “The reason you go to work is because you have a friend at work. So we have to understand that this new technology is going to give us a fantastic opportunity to be more productive and to find things more quickly, but it doesn't take away from the fact that we humans love to be with other people. We care about other people.”

So how is generative AI impacting HR today? Here are five key insights from the webinar and some lessons for HR leaders:

1. Generative AI as an augmentation tool
   Unlike predictive analytics, generative AI offers unprecedented opportunities for creativity and innovation in the workplace. Its accessibility on personal devices democratises technology, enabling a broader spectrum of employees to leverage its capabilities. Gratton argues against viewing Generative AI solely as a substitute for human labour. "It would be a big mistake if we saw generative AI simply as a substitution technology," she says, advocating for its role in enhancing human capabilities and fostering a symbiotic relationship between workers and technology.
    
2. The impact on work at task level
   A model by David Autor, Ford professor in the MIT Department of Economics, suggests that the impact of technology on work should be assessed at the task level rather than the job level. This perspective reveals that while routine tasks have been widely automated, the real challenge – and opportunity – lies in automating non-routine tasks, where generative AI can play a pivotal role. Focusing on the impact of AI at the task level, Gratton emphasises the nuanced effects on employment, stating: "Think about it at the level of the task... everything in the routine area has already been automated." This insight challenges the narrative around job displacement, advocating for a deeper understanding of AI's role in augmenting human work rather than replacing it.
    
3. Organisational response to generative AI
   Generative AI has catapulted to the forefront of organisational priorities. Gratton observes. "The real excitement about generative AI is that it is on your phone. It is on everybody's phone. Anyone can use it." This democratisation of technology signifies a radical shift from hierarchical IT implementations to a more inclusive, experimental approach across various sectors. Organisations are at various stages of integrating generative AI, from mere awareness to full-scale implementation. Gratton’s research at HSM Advisory finds 52% of organisations saying generative AI is a CEO priority where leadership is discussing the impact, with 21% saying it is on the agenda for business units but not a top priority and 13% that it is not on the agenda in any meaningful way yet. The creation of new roles, such as head of Generative AI, signifies the strategic importance of overseeing this integration to foster collaboration and innovation across departments.
    
4. The effect on skilled workers and productivity
   Generative AI opens up new vistas for skilled workers by automating non-routine analytical tasks. This shift not only enhances productivity but also necessitates a focus on reskilling and upskilling the workforce to keep pace with technological advancements. With Generative AI evolving rapidly, Gratton notes the significant claims on productivity improvements, especially for skilled workers. “It's the first time, really, that non-routine, analytical work can actually be done by a machine. And that's because of the large learning programs that are behind generative AI. Tthere are enormous claims made on productivity. If you take a look at productivity measures for the US, for most of Europe, it's been relatively static. And one of the points we're making is, why aren't we getting any productivity gain even though companies are investing in technology? And so there's a view that actually this is the thing that is going to increase the productivity of skilled workers.” But she cautions: “This is very fast, It's moving extremely quickly in a relatively unpredictable way," highlighting the importance of continuous learning and adaptation in this fast-paced technological landscape.
    
5. Human-centric skills remain paramount
   Despite AI's advancements, Gratton underscores the unique contributions of human judgment, critical thinking and empathy. "There are things that generative AI does and there are things that humans do. And they are different things: contextual knowledge, memory, association, time, outer reach.” However, she notes that Ai will take many tasks we think of as ‘creative’ in the next five years, though adds: ”It is just a machine, a very clever machine that we're all very excited about. But there's nothing in the universe we've discovered that's like the human brain. So let's try and do the very best we can with that in terms of creativity, humour, empathy, all the other things that make life worth living.”

Lessons for HR professionals

1. Foster a culture of lifelong learning
   To navigate the challenges posed by generative AI, HR professionals must cultivate an organisational culture that prioritises continuous learning and development. Encouraging employees to engage with AI tools for augmentation rather than substitution will be key to maximising their potential.
2. Strategise for task level automation
   HR should identify opportunities for AI to automate specific tasks within jobs, thereby freeing employees to focus on higher-value, creative and strategic activities. This task-level focus can guide reskilling initiatives to ensure that the workforce is prepared for future demands.
3. Develop a strategic framework for AI Integration
   The creation of roles dedicated to overseeing AI integration highlights the need for a strategic approach. HR should work closely with these leaders to ensure that AI adoption aligns with broader business goals and workforce development strategies.
4. Emphasise reskilling and upskilling
   As generative AI transforms the nature of non-routine tasks, HR must lead the charge in reskilling and upskilling efforts. Identifying future skill requirements and investing in targeted training programmes will be critical to maintaining a competitive and innovative workforce.
5. Champion human-centric skills
   In an increasingly automated world, HR professionals must champion the development of human-centric skills such as empathy, critical thinking and creativity. These skills not only differentiate human workers from AI but also contribute to a more innovative, adaptable and cohesive organisational culture.