AI will create more jobs, not less, says tech company survey
As generative AI becomes more prevalent in society, more and more people are using it to make their work more efficient. However, a study by the Harvard Business Review found that while AI has indeed made traditional work more efficient, it has actually increased the amount of work itself.
AI Doesn't Reduce Work—It Intensifies It
Aruna Ranganathan and colleagues at Harvard Business Review conducted an eight-month study at a US technology company with approximately 200 employees to examine the impact of generative AI on work habits. The results showed that many employees used AI spontaneously without being told to do so, and welcomed it because it 'enabled us to accomplish more, made our work feel more familiar, and made our work more rewarding.'
However, it has also become clear that while AI has made work more efficient, it has also increased the workload. Ranganathan and his colleagues point out that 'the introduction of AI is significantly changing the nature of work,' and explain these changes in three major areas.
◆1: Task expansion
As AI fills knowledge gaps, employees are proactively taking on tasks that were previously handled by others: product managers and designers writing code, researchers taking on engineering tasks, and individuals taking on tasks that have been outsourced, postponed, or avoided across the organization.
However, this expansion of work scope had knock-on effects. For example, engineers began spending more time reviewing, correcting, and mentoring their colleagues' AI-generated code. They were also overwhelmed with new tasks, such as mentoring colleagues who 'code by feel' and completing incomplete pull requests. This oversight occurred informally, through Slack threads and verbal consultations, and increased the workload for engineers.
◆2: The boundary between work and non-work is becoming blurred
Employees are now slipping small amounts of work into times that would traditionally be their breaks. Many are typing prompts into AI just before leaving their desks, during lunch, or during meetings, and some are even letting AI do the work while they're away. Ranganathan and others say these actions don't feel like they're increasing the number of hours worked, but they do reduce breaks over time, creating a sense of constant engagement.
Furthermore, conversations with AI, which are more like casual conversations than formal tasks, further blurred the boundaries between work and non-work, making it easier for work to unintentionally encroach on evenings and early mornings. Many employees reported that they 'realized later that as they became accustomed to typing prompts during their breaks, their breaks no longer brought the same sense of recovery they once did.'
3. Increased multitasking
Employees are using AI to multitask: letting AI generate alternative versions while they manually write code, running multiple AI agents in parallel, or letting AI do the easy work so they can resume tasks they've been putting off for years. The motivation for these actions is that they feel they have a 'partner' to share the workload.
The presence of this 'partner' leads to constant switching of attention, frequent checking of the AI's output, and an increase in unfinished tasks, creating cognitive load and making people feel like they are constantly juggling multiple tasks at once, even while still feeling productive.
These three changes might seem like good things for an organization. If employees are willing to take on the challenge of expanding their business, nothing seems bad. However, Ranganathan points out that there are risks associated with expanding and accelerating business.
Employees often find it fun because AI can easily complete tasks they initiated themselves, but this can lead managers to overlook the burden employees are shouldering, which can lead to overwork in the long run.
While AI works like magic at first, once the initial excitement wears off, employees notice a quiet increase in workload and begin to feel overwhelmed trying to keep up with the sudden influx of work. This increased workload can lead to cognitive fatigue, burnout, and impaired decision-making skills, which can lead to other problems, such as increased productivity and increased employee turnover.
Ranganathan and his colleagues explained that instead of simply accepting that AI will expand business operations, companies can maintain sustainable productivity by carefully determining how to use AI, when to stop using it, and whether or not to expand business operations as new capabilities are acquired, and by accurately defining the extent to which AI should be incorporated.
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