the future of work
Here’s how leaders can adapt and thrive.
Technology executive Thomas Anglero was trying to win a potential client’s business halfway around the world. He had 24 hours to lay out the terms and conditions of the deal, but the staffers who’d usually review the contract were all unreachable. So, he turned to a generative AI (GenAI) chatbot, Anthropic’s Claude 3.5 Sonnet.
Anglero and his colleague told Claude to assume a series of personas—architect, engineer, lawyer, marketer, and so on—and asked what someone in each role would want to include in the contract. They then asked the AI to draft an agreement that took all of those conversations into account. Finally, they had Claude compare that agreement to the one they had drafted, and tell them if they had missed anything.
“Working with Claude was like having endless resources of professional colleagues with specific business experience,” says Anglero, CEO of Too Easy AS, a SaaS platform for mobility solutions based in Oslo. “I now use Claude to review most of my decisions. I treat it like a trusted advisor open to disagreements and debate.”
As we’ve all learned over the last two years, GenAI bots can perform many tasks that were once considered the sole province of humans. Today, three out of every four enterprises have deployed large language models (LLMs) in some form, according to IDC. And while most organizations are still in the experimental phase, roughly 30% have put GenAI apps into operational use
AI will have a dramatic impact on the future of work, but it’s not clear what that future will look like. While machines may fully take over some existing roles, a much larger number of jobs will be augmented, with repetitive, rote, and supporting functions handled by algorithms. And new roles will emerge.
But when half of a job is performed by bots, what does the other half look like? And how will organizations recruit people for AI-heavy jobs that haven’t been invented yet? What new skills will your company need, and how will you hire for them?
“The impact AI will have on the landscape of people and skills is something we’re all still trying to figure out,” says Kevin Delaney, co-founder and CEO of Charter, a future-of-work media and research company. “AI is an adaptive challenge that will present questions without obvious answers. It will require a lot of experimentation and a different kind of leadership.”
AI in the workplace is not new. For many years, financial services firms have used AI-powered analytics to predict market trends and detect potential fraud. Manufacturers use computer vision to inspect materials flowing along assembly lines. Enterprise cybersecurity teams rely on machine learning to analyze system logs and flag potential attacks. Healthcare organizations have deployed AI to diagnose ailments and speed the development of new drugs. Retailers use it to manage their supply chains and offer personalized shopping recommendations. The list of potential use cases grows longer each day.
But nearly all of the traditional uses of AI remain the province of data scientists and technologists. GenAI is artificial intelligence for the masses. The ability to use natural language queries to extract previously inaccessible data—or generate entirely new content—puts AI within the reach of every employee, democratizing the technology in ways previous iterations have not.
GenAI will have profound initial impacts on employee productivity. Researchers at Harvard Business School and MIT Sloan found that highly skilled workers who use GenAI are nearly 40% more productive than those who don’t. ServiceNow’s 2024 Workforce Skills Forecast predicts AI will save U.S. technology workers between 4.5 and nearly 14 hours per week—the equivalent of more than 12 million full-time employees.
However, GenAI also introduces new conflicts that all organizations will have to navigate. For example:
But unlike previous eras, when emerging technology primarily disrupted lower-level workers, today’s AI will change the jobs of highly skilled employees with advanced degrees in architecture, engineering, finance, and law.
“AI will help us close that gap,” says Sarah Tilley, senior vice president of global talent for ServiceNow. “While some positions might be eliminated, AI will create new jobs for AI-savvy workers, and it will transform the nature of many other jobs.”
“About 30% of the time, it’s spot on,” says Geoffrey Bourne, co-founder of Ayrshare (pronounced “airshare”), which builds software that allows brands to automate their social media posts. “What might have taken me five or 10 minutes now takes about 20 seconds. Multiply that over a day of programming, and it saves me hours.”
GitHub’s research shows that AI assistants can cut the average time needed to complete coding tasks by 55%. But Bourne warns that such tools can’t replace developers entirely. Coding assistants can also hallucinate code, just as writing-assistant AIs can confidently present false information as fact. If you don’t know enough about programming to recognize when the assistant is churning out bad code, you could end up with buggy or insecure software, he adds.
But concerns over copyright infringement in the materials used to train these GenAI platforms, coupled with a lack of consistent quality in their output, have made many enterprises hesitant to use them. That’s why today’s AI creation tools are more likely to be deployed in early stages of ideation and brainstorming than when generating final product, says Audrey Schomer, media analyst and research editor for Variety Intelligence Platform (VIP+) and author of a report on the state of generative AI in Hollywood.
Lisa Simon, chief economist at workforce intelligence firm Revelio Labs, says determining how much an existing role will be affected by AI involves breaking each job function into discrete tasks, then determining which could be performed more efficiently by a bot. The process starts with creating a taxonomy of job activities. She says that understanding the nature of a company’s work and who does it will help organizations determine how to reconfigure existing roles and what new skills they will need.
“One person might have 15 out of 20 core work activities exposed to AI, while another might have five,” Simon says. “But just because AI can potentially do a job doesn’t mean it actually will. Has your company acquired any software that would allow this to become a reality? Does the regulatory environment you operate in allow this?”
Long-term workforce planning has always been a challenge, says ServiceNow's Tilley, but it’s especially challenging with emerging technologies like AI.
“It’s never been easy to predict the skills you’re going to need in the future,” she adds. “You have to start by quantifying all the skills you have in the organization today. And AI is also going to help us do that in a way we’ve never been able to do before.”
For example, machine learning platforms can scan external job postings to analyze which skills are in greatest demand and map them to an organization’s existing skills portfolio, Tilley says. ServiceNow has developed AI-based tools that can look at an employee’s existing skill set and predict new tasks at which they might excel.
She adds that simply replacing your current workforce with new, more AI-savvy employees is not going to work. Organizations will need to invest even more heavily in upskilling and retraining to get their people up to speed.
“If you’ve got 15,000 people in your organization who lack the requisite skills, you can’t simply eliminate that population,” she says. “You’ve got to equip them. In an era where technology advancements are so relentless, the idea that everyone has to be learning all the time becomes absolutely critical.”
Conversely, as machines take on more rote tasks, organizations will also need to focus more on recruiting people who can do things humans are better at, such as thinking strategically, uncovering the root causes of problems, and fostering strong relationships, Tilley adds.
With its ability to take on human roles, GenAI promises to alter the workplace—and work itself—irrevocably. Ethan Mollick, a professor of management at the University of Pennsylvania's Wharton School of Business, predicts that LLMs will drive “a fundamental shift in the way work is done, organized, and communicated,” with entire tasks being outsourced to algorithms.
That, in turn, will change how companies are organized. GenAI’s ability to perform key job functions will allow startups to stay smaller longer, says Jess Lantis, vice president of people operations for Guru, an AI-powered knowledge management platform. Larger enterprises may use it to flatten their management structure, relying on smaller teams assembled for specific projects.
“You won’t need layers of managers on managers or as many highly specialized experts,” says Lantis. “Employees can remain versatile, perform a variety of jobs, and learn the information they need by asking an LLM. That will impact headcount and org design.”
Many managers may find themselves overseeing AI employees. “In the future, we won’t just be managing people; we’re also going to be managing AI,” says Mark Campbell, founder and principal of 3dot Insights, a consultancy on emerging tech.
And many human employees could end up being managed by AI. No level of management is immune from AI change. Nearly half of all C-suite executives surveyed by online learning platform EdX believe AI chatbots could perform most or all of even a CEO’s duties. Forty-nine percent of CEOs agree.
Having AI in the management chain will require a new approach, Campbell says. Managers and leaders of AI agents won’t have to worry about things such as compensation, career advancement, or whether they’re overworking the bots. However, they may have to consider the potential impact of hallucinations, increased risk and uncertainty, and the sometimes unrealistic expectations of project stakeholders.
AI has arrived in the workplace, and it’s here to stay. Business leaders must ensure that their use of AI enhances human capabilities instead of replacing them. That means organizations will need to decide whether to prioritize augmentation over automation, says Charter’s Delaney.
“Businesses play a huge role in how this plays out,” he says. “You can train workers how to use AI, or you can find new things for them to do. It’s possible that AI will create more jobs than it destroys, and the history of technology suggests that this is a reasonable expectation.”
Organizations must also ensure that they deploy AI responsibly to keep businesses compliant with regulations and avoid causing harm.
Now is the time to focus on education and experimentation. Top executives need to embrace the technology and encourage everyone in their organizations to follow their lead, says Kirk Bresniker, chief architect of Hewlett Packard Labs.
“Our CEO, Antonio Neri, often says he wants everyone in our company to ‘have a minor in AI,’” he says. “People need to educate themselves on the possibilities of the technology and ask whether what they’re doing today can be done better using AI.”
The answer won’t always be yes, he adds. But every organization and individual must be willing to explore the question.
“AI won’t replace you or your profession,” says Bresniker. “But people in your profession who embrace AI will replace those who don’t.”
