Navigating the Inter-generational Divide in Senior Leadership
As artificial intelligence reshapes the world of work, there are real opportunities for organisations and people to become more creative and productive.
According to a report published this year by Mercer, a workforce, retirement and health consultancy, 57 per cent of CEOs and CFOs are planning to increase their use of artificial intelligence.
That’s not surprising. We’ve all grown accustomed to using products and services that are – at least in part – enabled by AI. Amazon recommends a product for you. AI is working away in the background. An insurer provides a quote for a motor policy. It’s increasingly likely that AI has played a part. A recruiter matches a CV to an employer’s requirements. The list goes on. Artificial Intelligence is being deployed to good effect across just about every industrial sector.
But something more profound is happening. The same report finds that one-third of companies are planning to redesign their working practices. AI will increasingly perform at least some of the tasks that human beings carry out today.
There is, naturally enough, a degree of concern about future employment prospects. But while AI will certainly disrupt the workplace, what it’s not going to do is remove the need to employ large numbers of human beings. In fact, the historical precedents point in the opposite direction. New forms of work will emerge.
New Forms of Work
This point was ably illustrated in a recent Economist article. As the author explained, when the printing press arrived in the German city of Augsburg in the 15th century, wood engravers feared for their jobs and staged mass protests. In fact, as the printing industry grew more productive, their skills were more in demand than ever. The job had changed but the work proliferated.
If handled well, the AI revolution could result in a similar and positive reshaping of the modern-day working landscape.
There is no single roadmap. AI technology comes in many forms. Some systems compile and analyse data as an aid to decision-making. Others wenable the autonomy of driverless cars, boats and planes. This year, there has been a huge amount of interest in Generative AI tools such as Chat GPT. Solutions in this category generate content such as text, imagery or computer code, usually as instructed by humans.
Use Cases
The potential use cases for Generative AI provide useful insights into the many ways that humans and machines might complement each other’s work in the not-too-distant future.
To take just one example, a leadership team within a business may commission a market report before making a decision on launching a new product. Such a report will require staff to compile data from a multitude of sources before creating the kind of narrative that turns information into actionable intelligence.
A Generative AI tool can produce the report in a fraction of the time while also drawing on data resources that researchers might not consider. What you get is a more comprehensive document.
That doesn’t, however, mean that people are out of the picture. The report still has to be checked for accuracy and more importantly, it is humans who will use the findings to make strategic decisions.
In a different context, Generative AI is already being used to create marketing collateral in the form of ad copy, press releases and imagery. This can be created rapidly and deployed not across a full range of channels while also being targeted in bespoke formats to small, carefully identified subsets of consumers. Again, it is the marketers who direct the campaign. The software simply makes them more productive.
Increasingly, AI designed to produce software code will exponentially increase the output of companies in the digital economy. Freed from coding, engineers can focus on designing products.
So what will this mean? Well, in a recent Forbes article, Joanne Chen, a general partner at Foundation Capital put it simply. AI will be a force multiplier for human intelligence and productivity.
There are, however, questions that remain to be answered. In the same Forbes piece, contributor Maren Thomas Bannon acknowledged that in many cases, humans will be there to assist the software rather than the other way round.
For example, in the case of decision-making software – the kind of tool that is already being used to optimise supply chains or enable dynamic pricing – most of the decisions might be made by the machine, with people on hand only to ensure the AI is making the right calls.
In other cases, however – and the AI might be a kind of personal assistant for a human operator.
Taking the Right Road
So how can businesses navigate the options?
In a blog for the World Economic Forum, Ravin Jesuthasan, a transformation services leader at Mercer, recommends that businesses focus not on the technology itself in the first instance, but on the work that needs to be done.
What’s certain is that human employees will continue to be crucial to the success of organisations even as many repetitive tasks are being taken away and performed more efficiently by bots. So the question then is simply this. How best can objectives b? What combination of elements will result in the best outcomes? Once clear goals – such as increased productivity – have been established, the working processes can be designed.
Work will change, but it’s important to build an environment where people and AI complement each other.
