The State of GenAI in the Workforce

The distribution of GenAI adoption reveals a notable shift towards more advanced GenAI implementation compared to earlier industry research. This trend suggests a more rapid acceleration of AI integration that exceeds previous expectations and assumptions, marking a significant turning point in the adoption of technology.

We asked the 529 respondents who reported having GenAI deployments in production or are piloting out-of-the-box tools to rank their use of three GenAI solution types. On average, out-of-the-box tools were most likely to be ranked first, low-code platforms were most likely to be ranked second, and custom-built solutions last.

The survey reveals a general strategic priority for GenAI in the workplace, with 67% of organizations prioritizing internal productivity improvements first. Customer-facing applications are gaining rapid traction, with 58% of respondents selecting this option. This indicates that businesses are moving beyond experimental uses to accretive AI implementations.

The data reveals alarming gaps in workplace AI enablement. More than 42% of respondents have not received even basic communications about GenAI from their employers, less than half have not received GenAI guidelines or documentation, and fewer than 35% are receiving hands-on, role-specific training. This highlights a critical need for stronger approaches to GenAI governance that balance risk management with innovation.

The data reveals an interesting pattern in the middle categories. Many respondents identified tools as either not available but desired or available but not used. Notably, "tools that help me design something" was indicated as least useful by respondents.

While developers, marketers, and specialized professionals might find certain digital tools essential, not every tool or technology is universally applicable. This sentiment is particularly illustrated by 182 respondents explicitly stating in the next question that existing GenAI tools are not designed for their unique use case.

A significant portion of respondents reported no barriers to GenAI adoption, indicating that they have the tools they need and are using them. This finding is particularly noteworthy given the survey's structure, where selecting the "nothing" option precluded choosing additional barriers, suggesting a surprisingly straightforward path to AI integration for many professionals. Additional research is needed to understand what portion of those who selected “nothing” are using GenAI tools.

The responses reveal two distinct clusters in expectations for AI’s impact on job functions. One group believes AI will advance rapidly, with many expecting it to handle half of their work within just one to three years. The other distinct cluster, however, remains skeptical, believing this level of ability will never be achieved. This bimodal distribution suggests a fundamental difference in trust. While some see AI as an imminent game-changer, others doubt its ability to replace human work at scale.

A compelling 76% of respondents report that GenAI is increasing their work productivity through improved quality and/or output quantity. However, a substantial 24% responded “neither,” signaling an important undercurrent of skepticism.

Among the 624 respondents who say GenAI is improving their work quality, a striking 59% believe its output is comparable to a professional with 8-10 years of experience. This confident assessment suggests that for professionals actively using AI, the technology isn't just an incremental tool but a transformative force capable of matching seasoned expertise.

The majority of respondents (57%) express a high level of trust in their employer to implement GenAI responsibly. It’s encouraging to see how much trust workers have in their employers to deploy GenAI responsibly. This is, however, expected, given strong adoption numbers seen in question 5, with more than 60% of respondents selecting that they use GenAI to answer questions and help with writing.

Almost half (49%) of respondents feel hopeful about their future job prospects amid GenAI adoption. Meanwhile, 30% remain neutral, while 21% feel fearful.

As with trust in their employers, we are pleasantly surprised to see how hopeful people are about their future job prospects. While individual contributors’ responses were normally distributed around neutral, executives were heavily skewed towards hopeful. This indicates a disconnect between leaders and line workers that highlights further the gaps in change management seen in response to question 4.