Article 8 Min ReadManaging Cyber Risk through Return on Security Investment
Navigating the Future of Work with AI
Artificial intelligence 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.
As AI’s use becomes more widespread, leaders need to understand how this technology works and what its future role may be.
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 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.”
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.
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.”
The information contained herein and the statements expressed are of a general nature and are not intended to address the circumstances of any particular individual or entity. Although we endeavor to provide accurate and timely information and use sources we consider reliable, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the future. No one should act on such information without appropriate professional advice after a thorough examination of the particular situation.
The contents herein may not be reproduced, reused, reprinted or redistributed without the expressed written consent of Aon, unless otherwise authorized by Aon. To use information contained herein, please write to our team.
Stay in the loop on today's most pressing cyber security matters.
Article 27 Min ReadTop 5 Cyber Threats To Mergers and Acquisitions
Article 12 Min ReadMitigating Insider Threats: Your Worst Cyber Threats Could be Coming from Inside
Article 17 Min ReadWhy HR Leaders Must Help Drive Cyber Security Agenda
Article 14 Min ReadResisting Cyber Attacks Through Layered Security Systems
Environmental, Social and Governance Insights
Explore Aon's latest environmental social and governance (ESG) insights.
Article 9 Min ReadESG Data: How Businesses Can Use Data to Gain an Edge
Article 12 Min ReadWhy ESG Is Even More Important In A Crisis Like COVID-19
Insights for HR
Explore our hand-picked insights for human resources professionals.
Article 9 Min ReadCOVID-19 has Permanently Changed the Way We Think About Wellbeing
Article 11 Min ReadDE&I in Benefits Plans: A Global Perspective
Article 13 Min ReadHow Data and Analytics Can Optimize HR Programs
Article 17 Min ReadWhy HR Leaders Must Help Drive Cyber Security Agenda
Article 10 Min ReadCase Study: The LPGA Unlocks Talent Potential with Data
Article 16 Min ReadNavigating the New EU Directive on Pay Transparency
Article 14 Min ReadHow to Design Better Talent Assessment to Promote DE&I
Article 8 Min ReadTraining and Transforming Managers for the Future of Work
Article 10 Min ReadRethinking Your Total Rewards Programs During Mergers and Acquisitions
Article 21 Min ReadBuilding a Resilient Workforce That Steers Organizational Success | An Outlook Across Industries
How do businesses navigate their way through new forms of volatility and make decisions that protect and grow their organizations?
More Like This
Article 17 Min Read
How Academic Research Can Help Drive Climate Risk Resilience
By leveraging the advances made by academic research, companies can develop more robust climate risk resilience.
Article 19 Min Read
Pricing Platform: Avoiding Pricing Pitfalls
Pricing pitfalls are more common than you think, whether it's working with incomplete data or key man risk – but with the right pricing process, many of these issues can be mitigated. Read our article to learn about the most common pricing errors, and what insurers can do about it.
Article 18 Min Read
Pricing Platform: The Importance of Getting Pricing Right
In today's increasingly complex insurance landscape, an inadequate pricing system can not only impact insurers' view of risk, but also prevent them from making the right decisions at the right time. Read our article on why it's essential to get pricing right.