Navigating the Future of Work with AI
April 26, 2023
Artificial intelligence (AI) is changing the way businesses operate. As its use becomes more widespread, leaders need to understand how this technology works and what its future role may be.
- Generative AI — which creates original material such as text — has the potential to disrupt business operations across many industries.
- The emergence of generative AI tools has altered many expectations on what sort of tasks can be automated.
- While there are fears of jobs either being lost or changed radically, history shows that there’s no guarantee AI automation will cause widespread job displacement.
There’s a new hot topic among leaders in the business world. Generative AI, a type of artificial intelligence that can create original material such as images, music, or text, has only recently come to public attention but has already shown the potential to thoroughly disrupt business operations across fields and industries.
“There’s shock and amazement that these tools have progressed as quickly as they have,” says Muir Macpherson, partner, global human capital analytics at Aon. “Developments just over the past six or nine months have caught everyone by surprise, and those surprises haven’t slowed down.”
While the effect of AI technologies such as Open AI’s GPT-3 and -4 on the future of work remains uncertain, understanding the function of generative AI in business as it stands now and how it’s being used can help leaders strategize effectively.
Accessibility to AI has increased for businesses of all sizes, offering new opportunities to drive innovation and optimize operations.
“With these foundational models, artificial intelligence has become democratized,” says Christopher Blackburn, senior data scientist, Human Capital Solutions at Aon.
But in tandem with all the excitement, leaders and employees are anxious about the potential consequences AI can have for business, including producing false or faulty content and changing or removing jobs.
Understanding Generative AI
Generative AI has already altered many expectations on what sort of tasks can be automated.
“Before, many assumed artificial intelligence would mostly affect jobs where their responsibilities were manual, routine, and non-cognitive,” says Blackburn. “With GPT-3, we realize is that these foundational language models are zero-shot learners. Without having seen any examples of a given task, these models can generalize very well to new tasks and produce human-level output. That is quite remarkable, because this creates the opportunity for these generative AI models to be put in the domain of non-routine cognitive tasks, where complex human reasoning was required.”
The consequences of this sort of capability are difficult to fully assess. But the general trajectory is fairly clear.
“I think the best way to think about these technologies is that it dramatically lowers the costs of doing certain kinds of tasks,” says Macpherson. “When that happens, one possible outcome is that the demand for those kinds of tasks goes way up. I think we may see that actually in software development. As the cost of producing good code goes down, I think we may see the quality of software that people use go up and the areas in which software applied expand.”
As with any sort of upheaval in the business world, there will likely be a period where contemporary business processes and expectations will not have caught up with the functionalities of AI tools — particularly, as Macpherson observes, in fields where AI has an immediate application, such as industries where large sums of information must be formulated and digested quickly.
“The net impact of AI on a profession that generates and reads a lot of text, like a lawyer or a business consultant, is uncertain at this point,” says Macpherson. “I think it’s going to be really interesting to see how AI gets used on both sides of that equation to generate content, as well as to summarize content. I’m imagining a situation in which AI produces a 50-page document for someone who then sends it to another human, who then uses an AI to summarize that document.”
Fears of Job Displacement
One of the largest and most substantial fears of generative AI is job displacement. As AI becomes increasingly capable of doing more and more jobs that would otherwise require human intervention, some claim that it has the potential to replace countless numbers of people — people that will have nowhere else to go.
However, history shows that there’s no guarantee AI automation will cause widespread job displacement. “Looking at the history of how automation has impacted work, an example that a lot of people like to point to is the ATM,” says Macpherson. “You might think that rolling out automated teller machines would have resulted in the loss of bank teller jobs. But the ATM was introduced in 1978, and over the subsequent 30 years, the number of people working as tellers in the U.S. did not decline. It stopped growing, but it didn’t decline, and that was because the tellers became a lot more productive.”
In direct contrast to the fears of AI-related job loss, there’s also potential for new jobs to be created as a result of AI being used in the workplace.
“There is a displacement effect where some tasks do get automated away, but there’s also this generative effect where new tasks are created,” says Blackburn, noting that companies are still simply figuring out how to use AI technology in their existing processes. “One new type of position that’s been floating around recently is a job titled a prompt engineer, which their sole purpose is to design prompts to test language model capabilities.”
AI in Today’s Workforce
The conversation surrounding AI has been dominated by speculation about the future, but it is also important to consider the implications of how AI tools are being used today.
One thing that has become clear is that workers are using AI technology even if it doesn’t directly relate to their job. “I think one of the things that we’re hearing is that a lot of people are experimenting with these technologies on their own without even their company being aware of it and discovering ways that they can automate their jobs better,” says Macpherson.
What this means for businesses is that AI literacy will become a part of the range of competencies that employees bring to the workplace.
“I think there’s going to be a major shift toward AI literacy and skillsets that encompass this domain,” says Blackburn. “Not only would that be some foundational knowledge in probability and statistics, but also in areas like ethics and governance of AI and understanding the limitations of risks associated with adopting these technologies at scale.”
As businesses continue to explore the potential of AI in the workplace, it will be crucial to balance the benefits of automation with other practical needs and concerns of the company. Macpherson explains that being responsible with privacy and sensitive information still holds true for AI tools.
“One of the things that I know has been an immediate concern is employees are going to put sensitive information into an AI that’s hosted on OpenAI or another company’s website,” says Macpherson. “A company doesn’t want to be in the position of turning over sensitive tasks to AI at this point. It’s still a technology that we’re learning a lot about.”
To find out more about Aon’s insights on the future of work, click here.