The rapid integration of generative artificial intelligence into the global economy has created a significant divergence in how different demographics perceive and utilize these emerging tools. According to the fifth annual CNBC SurveyMonkey Women at Work survey, a pronounced gender gap has emerged regarding AI enthusiasm, with men significantly more likely to embrace the technology as a professional asset while women remain notably more skeptical. This divide, captured in data collected from over 6,300 participants, suggests that the "AI revolution" is not being experienced uniformly across the workforce, potentially setting the stage for new disparities in career advancement and economic parity.
The survey findings highlight a fundamental difference in perception: approximately 69% of men polled view artificial intelligence as a "valuable assistant and collaborator" in their daily professional lives. In contrast, only 61% of women share this optimistic outlook. This eight-percentage-point gap is further complicated by a widespread sense of ethical or professional unease among female workers. Half of the women surveyed indicated that they view AI with a degree of suspicion, asserting that "using AI at work feels like cheating." This sentiment is less prevalent among their male counterparts, only 43% of whom expressed similar reservations about the integrity of AI-assisted labor.
Chronology of the Generative AI Surge
To understand the current state of workplace AI adoption, it is necessary to look at the timeline of the technology’s recent explosion. The modern AI boom is widely traced back to November 30, 2022, when OpenAI released ChatGPT to the public. Within five days, the chatbot had reached one million users, signaling a paradigm shift in how the general public interacted with large language models (LLMs).
By early 2023, the landscape became increasingly competitive. Microsoft integrated OpenAI’s technology into its Bing search engine and launched Copilot, while Google responded with the introduction of Bard (later rebranded as Gemini). Throughout 2023 and into 2024, the ecosystem expanded beyond simple text generation to include sophisticated coding agents like Cursor, image generators like Midjourney, and specialized research tools such as Perplexity and Anthropic’s Claude.
The CNBC SurveyMonkey data, collected between February 10 and February 16, 2024, reflects a workforce that has had roughly 15 months to adjust to these tools. During this period, AI transitioned from a Silicon Valley novelty to a core component of corporate strategy, with major enterprises racing to implement internal AI guardrails and productivity suites. However, as the data suggests, the adoption of these tools has been unevenly distributed.
Disparities in Workplace Usage and Frequency
The survey provides a granular look at how AI is actually being used—or ignored—on a daily basis. A significant majority of women (64%) reported that they never use AI at work, compared to 55% of men. This suggests that while more than half of all workers are still holding out on AI adoption, the resistance or lack of opportunity is notably higher among women.
The gap becomes even more pronounced when examining "power users"—those who have integrated AI into their routine multiple times a day. Approximately 14% of men fall into this category, whereas only 9% of women report similar frequency. This disparity in "hands-on" time with the technology could have long-term consequences for technical literacy and efficiency. As AI tools become more embedded in standard office software, those who use them daily are likely to develop a competitive edge in speed and output quality.
Corporate Directives and the Economic Outlook
While individual workers debate the merits of AI, the upper echelons of corporate leadership have largely reached a consensus: AI is no longer optional. Jamie Dimon, CEO of JPMorgan Chase, has been a vocal proponent of this transition. In the bank’s 2024 investor day communications, Dimon characterized AI as "critical to our company’s future success." He revealed that nearly two-thirds of the firm’s workforce is already utilizing an internal large language model, illustrating a top-down push for adoption.
However, Dimon’s enthusiasm is tempered by the reality of labor displacement. He has acknowledged that AI will inevitably eliminate certain job functions, arguing that the responsibility lies with companies to retrain their staff for new roles. This corporate stance explains why Wall Street has been aggressively re-evaluating the tech sector. Software stocks have faced volatility over the past year as investors bet that AI will eventually displace traditional enterprise software stacks. Companies that fail to pivot to an AI-first model are increasingly viewed as vulnerable to obsolescence.
The Training Paradox and the "FOMO" Factor
One of the more complex findings of the survey is the relationship between AI usage and the desire for further education. Despite being more likely to use AI, men are also more likely to express a need for more instruction. Approximately 59% of men in the survey stated they need more training on how to use AI effectively at work.
This hunger for training is often driven by a "fear of missing out" (FOMO). The survey found that 39% of men fear they will be left behind if they do not embrace AI, compared to 35% of women. Perhaps more tellingly, 42% of women "strongly disagree" with the notion that failing to adopt AI will negatively impact their career trajectory. Among men, this figure stands lower at 36%.
This data suggests a potential disconnect between women’s current career confidence and the rapidly changing requirements of the labor market. If AI proficiency becomes a standard requirement for promotion and raises, those who currently view the technology as unnecessary or "cheating" may find themselves at a disadvantage in future hiring and review cycles.
Implications for the "Broken Rung" and Gender Parity
The emergence of a gender gap in AI adoption threatens to exacerbate existing inequalities in the corporate world. Sheryl Sandberg, founder of LeanIn.Org and former Meta Chief Operating Officer, has expressed concern that this technological divide could worsen the "broken rung" phenomenon—the well-documented trend where women are less likely to be promoted from entry-level positions to manager-level roles.
In an interview discussing the survey’s implications, Sandberg noted that AI is poised to be most challenging for those who do not know how to use the tools. "We know that AI is going to be challenging for jobs, and it’s going to be the most challenging for the people that don’t know how to use those tools," Sandberg said. She emphasized that if men are earlier and more frequent adopters of AI, they may gain a significant advantage in early-career milestones, which has a compounding effect throughout a professional life.
Sandberg warned that the disproportionate impact of AI could be a "real shame for our companies" and detrimental to the broader economy. If a large segment of the female workforce remains skeptical or under-trained in AI, the progress made toward gender parity in leadership over the last decade could be stalled or even reversed.
Analysis: Why the Skepticism Exists
The fact-based analysis of this gap suggests several potential drivers for the skepticism among women. First, there is the "perfectionism" and "imposter syndrome" factor often cited in workplace sociology. If women feel that using AI is "cheating," it may be because they are socialized to value the process of labor as much as the result, or because they fear that AI-generated work will be held to a higher standard of scrutiny.
Second, the types of roles predominantly held by women may currently offer fewer obvious use cases for generative AI, or conversely, may be the roles most threatened by automation. According to various labor studies, administrative and clerical roles—which are statistically more likely to be held by women—are among the first to be impacted by LLMs. This creates a defensive posture toward the technology rather than a collaborative one.
Finally, the "bro-culture" often associated with early tech adoption may be playing a role. Since the initial marketing and hype surrounding AI have been heavily concentrated in male-dominated tech circles, women may feel less invited to the table or may view the current AI discourse as another iteration of Silicon Valley hype that does not serve their practical needs.
Conclusion and Future Outlook
The CNBC SurveyMonkey data serves as a critical warning for both policymakers and corporate leaders. As AI moves from a specialized tool to a universal workplace utility, the gender gap in adoption and perception represents a significant risk to workforce equity.
To bridge this divide, experts suggest that training programs must be made more accessible and inclusive, moving away from the "power user" narrative toward practical, ethics-based integration. If companies can address the "cheating" stigma and demonstrate how AI can alleviate burnout rather than just increase quotas, they may see a shift in sentiment among female employees.
As the AI landscape continues to evolve through 2025 and 2026, the focus will likely shift from simple usage statistics to the quality of human-AI collaboration. Ensuring that this collaboration is balanced across gender lines will be essential for maintaining a diverse and resilient global economy. For now, the data remains clear: while the AI boom is well underway, its benefits and adoption are currently skewed, leaving a significant portion of the workforce at risk of falling behind in the next era of professional development.
