Workforce possibilities and implications

The successful adoption of generative artificial intelligence (AI) is highly dependent on the path the business takes, one that includes the company being highly cognizant of the need for the right skills, new approaches and effective stakeholder engagement. Generative AI will impact businesses and their workforces, but the scale thereof, and whether it will be positive or negative, will depend on how well the company understands the change and navigates it.

In our recent survey of 411 middle market businesses about their views on generative AI, 32% thought the technology would improve the business to a ‘great extent’, and 45% to ‘some extent’. Only 17% said ‘very little’ and only 4% said ‘not at all’.

The middle market obviously sees generative AI as a boon.

But, these businesses need to be prepared for the considerable task of fully understanding and incorporating this complex technology into their operations to an effective and impactful level, and being prepared for the organisation change needed.

Workforce impact in the age of generative AI

From a ‘general’ workforce perspective, when a new and transformative technology arrives in the market a consistent debate resurfaces, ‘will the technology replace or enable workforces?’

The debate was played out during the Industrial Revolution in the 18th century, when the Luddites protested against the mechanisation of their work, and many lost their jobs. It resurfaced in the 1930s, when some blamed engineers and scientists for causing mass unemployment during the Great Depression. And it continued into the 1960s, when the introduction of computers and machine tools reduced the demand for human labour in factories.

The digital information age is no different, with much debate already having taken place about the impact of AI on workforces. But the debate has being especially intense since the launch of easy-to-use and extremely powerful generative AI tools.

What’s interesting though is that only 7% of the survey’s respondents believed that the technology would lead to a reduction in their headcount, with 16% saying that there would be a significant increase and 45% expecting to see a slight increase. While we know that ‘base processing’ functions can be performed by generative AI, for example, preparing discussion material ahead of a client engagement and leaving the more creative recommendations to the team, the survey results could indicate that companies recognise the value of more people performing the more creative, higher margin roles that are enabled by efficient generative AI, and will therefore recruit into those areas.

It’s worth mentioning that we did not survey employees for their opinion of the opportunities or threats of the technology. We can’t be naïve to the fact that some employees may feel that the technology will be ‘replacing’ certain areas. Companies need to recognise this concern and should be prepared to help employees go through this change. This would ideally include skilling up those workers to perform the higher, more value add functions, but firms need to recognise that not all employees would be able to, or even want to make that transition.

But for those that do, what are the skills needed to effectively leverage these new generative AI tools effectively?

Building technical capabilities and a new approach to technology deployment

It’s one thing to use publicly available large language models (LLMs) like ChatGPT and Bing Chat Enterprise. Lots has been discussed on social media about the best prompts to use and how it can help to manage small tasks. But, it’s a much greater task configuring the technology where the tool is being applied to companies’ proprietary data and playbooks, where biases are being addressed, where ‘hallucinations’ are identified and ignored, and where the use of synthetic data is carefully managed to avoid possible pollution of the input data used to teach the AI machine.

As an initial phase, the enterprises of tomorrow will need to up-skill or recruit in the skills necessary for them to master these challenges and build the technology into their processes. They will likely need specialists that can augment existing systems to create new applications, to help them develop whole new workflows and operating models that, until now, have been impossible or even unimagined.

Skilling up leadership

Senior leadership, including board members, will need to get to grips with the technology if adoption is being driven from within the operations of their companies. To make the best decisions on proposals submitted by those teams, they’ll need to make sure they have the technology brainpower to understand the opportunities that can be enabled, and the threats. The latter are certainly on the agenda of executives, as shown by our survey where 23% of the respondents believe that generative AI can be a threat to a great extent and 40% to some extent. Only 22% felt very little and 13% not at all. There’s power in understanding, and there’s likely to be much ground to be made up that must be addressed.

But be careful of altering what makes organisations unique

Critically, while generative AI is available to all companies and it will enhance key operations and replace some others, Joel Segal, RSM UK’s head of business transformation notes that, “companies should not loose site of the unique chemistry of people, processes and culture that may be making them a great place to work or do business with”.

Sometimes that chemistry is not fully understood and can’t be articulated, yet it’s there and it works. Economist David Autor named this struggle “Polanyi’s Paradox”. The paradox is derived from the work by Michael Polanyi (1891-1976) captured by this quote, “We know more than we can tell”. Put another way, people often can’t explain what they intuitively know i.e. they can’t codify it. If a widely transformative technology is introduced into a complex environment that’s not fully codified then it can have unintended consequences. Companies looking to enhance that chemistry to understand the unique formula as deeply as possible and appreciate how it can be enhanced.

Companies embracing generative AI need to be aware that they will need to go on a carefully orchestrated journey to make a success of it. They need to understand what they want to impact, what they don’t want to impact and who it impacts, secure or develop specialist technical skills, and take key stakeholders on a journey that won’t necessarily be straightforward. This is not just about a configuration of the technology but rather a recipe that needs careful and considered hands successfully bringing all key stakeholders on the journey.