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- Gartner, a management consulting company known for its research into workforce trends, estimates that by 2028 50% of employees will have a “robo-assistant.”
- While scaling the number of robo assistants that an organization has doesn’t necessarily cost anything, experts believe that it does raise issues that organizations must address — such as ethics and guardrails.
- Two-thirds of the over 1,200 professionals interviewed in Thomas Reuters’ recent “Future of Professionals Survey” said that they believe AI will be high-impact or transformational in their profession over the next five years.
The rising popularity of generative AI tools, like ChatGPT, is set to disrupt the entire global workforce in the coming years. Many would say that this disruption has already begun.
Each new deep-dive into possible societal impacts feeds a collective fear of a massive wave of job automation — one that could cause an estimated 12 million U.S. employees to be displaced and shift careers by 2030, according to projections from McKinsey & Co. However, more and more experts are saying that this almost apocalyptic scene from the Terminator will likely not be the case.
How might we use AI at work?
Analysts at Gartner, a management consulting company known for its research into workforce trends, share this positive outlook. In fact, researchers at the company estimate that by 2028, 50% of employees will have a “robo-assistant.”
In a webinar called “The Future of AI and Its Impact on Your Organization,” Gartner’s VP Analyst Whit Andrews, and Sr. Director Analyst Pieter J. Den Hamer, discussed the use of robo-assistant, automation and other AI workforce developments in more detail.
“Executives might think that they want something that replaces you, but they don’t really,” said Andrews during the webinar. “What they want is to take advantage of what workers are best at.”
While many employees around the world believe that automation may take their jobs, the researchers at Gartner believe that full-on replacement is unlikely. In support of this theory, Gartner’s analysts are pitching the idea of “Symbiotic Intelligence,” which refers to a synergy between human and machine intelligence. In this projection, AI will more than likely be used as a tool to boost productivity and job output through automation processes — rather than completely eliminating people from their jobs.
Companies are catching on to this symbiotic workflow, and they’re showing this in their quarterly reports. The Washington Post recently published an analysis of corporate reports and found that over 1,000 public companies have mentioned the use of AI. The report found that hundreds of U.S. businesses across a wide spectrum of industries are using AI in some shape or form.
From Ulta Beauty using AI to power “virtual try-on and skin analysis tools,” to Fidelity using AI to detect fraud, the diverse range of applications showcases the technology’s versatility and potential to change how people work regardless of the field in which their company operates. That being said, the adoption rate for AI at major firms has been slow, but has shown growth.
“When we asked in 2019, 81% of CIOs told us that they would have [AI] by now. In our most recent survey, that was last June, was actually just 32%,” Andrews said. “I suspect we’re getting up towards 40% now, but it’s less than half. So less than half of CIOs actually achieved what they said they were gonna achieve.”
What’s at risk with widespread AI adoption?
One chief concern found among employers that plan on using AI tools is making sure that employees do their job — instead of simply allowing their new robo assistants to do the job for them. While scaling the number of robo assistants that an organization has doesn’t necessarily cost anything, experts believe that it does raise issues that organizations must address — such as ethics and guardrails.
According to an analysis published by Goldman Sachs, “Using data on occupational tasks in both the U.S. and Europe, we find that roughly two-thirds of current jobs are exposed to some degree of AI automation, and that generative AI could substitute up to one-fourth of current work.”
The firm estimates that 300 million full-time jobs around the world are exposed to automation.
These kinds of concerns have led top technology firms that are heavily invested into AI technologies — including Google, Meta, Microsoft, and Amazon — to commit to AI safeguards proposed by President Joe Biden’s administration. Leaders at these companies also committed to meeting with the government to help guide public policy. While it’s still too soon to determine any impact, on Oct. 30, President Joe Biden signed a lengthy 111-page long Executive Order laying out plans for governing the development and use of AI safely and responsibly.
On top of policy, privacy, and ethical concerns, many companies are finding it challenging to get the necessary data they need to power their own AI use cases — especially if the firm is trying to establish its own company-specific applications. An example of one such application currently in use would be Mckinsey and Company’s AI tool called Lili. The recently announced in-house tool allows the firm’s employees to search thousands of company documents and interview transcripts to help gather relevant information and key insights faster and more efficiently. At the time it was unveiled, Mckinsey and Company stated that the tool was already being used by 7,000 employees.
As the technological innovation of AI mounts, it’s likely that the capabilities of what machine learning and AI can do will outpace what any organization and employees can actually achieve on their own, and this might be frustrating to employees, thus decreasing employee satisfaction.
“We need to be careful, and not underestimate how augmented AI or generative AI will impact us human employees in our employee satisfaction,” Hamer said during the Gartner webinar.
How can employees prepare–and how soon must they do it?
That point of technological advancement is when automation will come to the forefront and have a high impact on the workforce. In fact, two-thirds of the over 1,200 professionals interviewed in Thomas Reuters’ recent “Future of Professionals Survey” said that they believe AI will be high-impact or transformational in their profession over the next five years. The survey included professionals working in the legal, tax & accounting, global trade, risk management, and compliance fields employed at government agencies and corporate in-house departments.
Steve Hasker, CEO and President of Thomas Reuters, stated in the report, “An evolution of this magnitude will require us all to step out of our comfort zones and reassess spending allocation in key areas such as real estate, training, and hiring to better ensure we are keeping pace with emerging technology investment.”
Top priorities in the coming months for firms and departments varied, but many priorities cited fell under the “operational improvements” category as the most important. “Productivity” was cited as the top priority by 75% of legal and 59% of tax and accounting professionals working at firms. Similarly, 50% of employees at law firms and 55% of tax and accounting firm professionals cited internal efficiency as one of their top priorities.
With the massive improvements to productivity projected to have such a broad impact in the workforce, it will be important for leaders to invest in upskilling in order to build on employee strengths and talents.
Gartner recommends that organizations identify use cases where human strengths complement AI strengths. For example, in the creation of:
- Text, code, and other content
- Complex decision augmentation in tasks such as medical diagnosis, recruitment, financial trading or investments
- Improved control of equipment, machines or vehicles, or
- Incident and crisis management
The future of work hinges on whether or not the workforce can achieve a harmonious blend of human and machine intelligence. Guardrails and upskilling are pretty much essential to this outcome. While the initial apprehensions about AI replacing jobs are valid, the impact will likely not be as negative as many employees fear, so long as policy makers and industry leaders invest resources into continuous learning, ethical considerations, and focus on leveraging the unique strengths of both human and machine intelligence.
