How AI can supercharge our work force
For years, artificial intelligence has been used to assist people in the workplace, to deliver better, faster, more cost-effective results.
Take the airline industry. When disruptions happen – whether it’s seasonal fog or more severe events like the Auckland floods and Cyclone Gabrielle – it’s important staff can re-plan and re-schedule quickly and effectively.
AI can ‘‘think’’ about swapping planes and routes faster and in more ways than humans can. AI can produce decisions much faster, too – down to a millisecond.
In our work in Aotearoa, we are starting to see more discussion around AI and productivity in everyday work, as it is starting to become more accessible for businesses, particularly from a cost point of view. One of the highest pressures on price is around needing to connect to clean data sources and codify its methodology.
At BCG, we established a dedicated team in Australia focused on AI 10 years ago, and it’s been expanding ever since, driven by unrelenting demand. The founder of our data science team in APAC, Adam Whybrew, has supported more than 300 projects. The main areas driving demand tend to be in operations and marketing. We are now seeing this demand here, too.
From an operations perspective, the productivity benefits of AI are immense. When we think about climate change and the role that infrastructure plays in mitigating and adapting to that, we also know that it is important to get the delivery of that infrastructure right. A wrongly laid road or housing development can have dire consequences down the line for both people and planet.
Through AI, we can supercharge productivity to do things like build ‘‘digital twins’’ and conduct experiments that would otherwise have cost tens of millions of dollars, and equivalent time for people working hard to find solutions.
Of course, AI is not a perfect tool. From a work force perspective, this means that – regardless of industry – there is now a demand for skilled data scientists because the cost of being wrong is enormous.
Our teams have to interview the people making the process decisions to understand what they are actually free to change and what parts of the data are simply correlations, before they can make recommendations for improved process settings. When they are correct, the benefits are enormous.
In the past, technological advances have made workers richer where they have increased their productivity, but have created significant unemployment and social problems.
With New Zealand’s ageing population, some degree of replacement will be necessary to maintain our standard of living, alongside a growing silver work force and increased immigration, so the social upheavals may not be felt as severely here as in places where there is an oversupply of labour.
However, it may still be that our workers have to look at different ways to approach the same jobs and industries, particularly with the progression of generative AI (of which ChatGPT is an example). The most established use case is in coding, in which the evidence is now fairly clear that AI assistance increases the productivity of coders.
The unlock beyond coding is that generative AI can be given plain English inputs. This is set to democratise its use and make some creative tasks quicker and cheaper. This is already happening in creating images, text and video for checking by humans.
Rather than rendering human capital obsolete, this means we will find ourselves learning the basics of an industry to gain the skills to ensure the AI gives accurate answers and doesn’t make things up. But the real-world solutions are nearer than one would think from just playing with ChatGPT.
The impact of AI on the work force ought not be feared. In working alongside people, AI is already helping workers create value. AI will fundamentally change the way companies operate, but people will remain an integral part of the company.
The real opportunity is finding ways to get the best working model between AI and humans, rather than trying to replace one with the other. This likely means AI will focus on lower cost, higher efficacy prediction while humans focus on judgment.
Most businesses combine ‘‘prediction’’ and ‘‘judgment’’ into a single role, meaning organisations will need to be fundamentally redesigned to make the most of this opportunity. And it is an opportunity. Because those who harness AI will arguably be at a permanent competitive advantage given the value AI delivers.