The workers secretly influencing their companies’ AI usage
When Estefania Angel started working as an executive assistant at a large tech company a few months ago, she noticed something counterintuitive: while her company’s job was to help other enterprises set up AI to streamline their in-house tasks, her company didn’t use those systems internally itself. Using AI apps in Slack, Outlook, and Google to track various assignments and ping colleagues, Angel got the attention of her superiors. One even asked Angel to teach her how to use AI at work. “We started tracking a whole project that she was doing,” says Angel, who works as an executive assistant (EA) with EA service company Viva Talent, streamlining the project’s workflow. That was just the first step. Ultimately, through Angel’s use of AI to make a variety of office tasks increasingly efficient, more and more of her colleagues began adopting those AI-driven processes until it became the company norm. It wasn’t company executives driving AI adoption—but rather lower-ranking, self-taught employees who helped AI use cases trickle upward. This bottom-up AI adoption tracks with wider trends: Last year, McKinsey found that “the biggest barrier to scaling [AI] is not employees—who are ready—but leaders, who are not steering fast enough.” McKinsey researchers surveyed 3,613 employees and 238 C-level executives and learned that the latter seriously underestimate how much the former use AI. C-suite executives, for example, believed 4% of employees used gen AI for at least 30% of their work, when employees’ self-reported percentage was three times higher. While EAs can be
When Estefania Angel began working as an executive assistant at a large tech company a few months ago, she observed a peculiar disparity: her company, which specialized in helping other enterprises implement AI to streamline their operations, was not utilizing such systems internally. Angel, who uses AI apps in Slack, Outlook, and Google to manage assignments and communicate with colleagues, caught the attention of her superiors. One even requested that she teach them how to use AI at work.
"We started tracking a whole project that she was doing," Angel recalls, referring to her role as an executive assistant (EA) with EA service company Viva Talent, where she streamlined the project's workflow. This marked the beginning of a subtle yet significant shift. As Angel leveraged AI to enhance various office tasks, her colleagues gradually adopted these AI-driven processes, eventually making them a standard practice within the company.
This story underscores a broader trend: AI adoption is often driven not by top executives but by lower-ranking, self-taught employees. Last year, McKinsey found that the biggest barrier to scaling AI is not employees—who are eager to adopt the technology—but leaders who are not steering fast enough. The research, which surveyed 3,613 employees and 238 C-level executives, revealed that executives severely underestimate the extent to which their staff uses AI. For instance, C-suite executives believed that only 4% of employees used AI for at least 30% of their work, while employees' self-reported percentage was three times higher.
While executive assistants like Angel can play a pivotal role in driving AI adoption upwards due to their close proximity to executives, other employees across various roles have also been instrumental in sparking widespread AI integration within their organizations. Recruiters, data workers, individual contributor (IC) coders, project coordinators, and even valets have all contributed to the permeation of AI across their workplaces.
The reality is that executives are rarely the primary drivers of AI adoption at the workplace. Instead, it is often the employees engaged in day-to-day tasks who are at the forefront of integrating AI into their routines. This grassroots approach has the potential to accelerate AI adoption more effectively than top-down mandates.
As companies recognize the value of AI, fostering a culture that encourages employees at all levels to experiment with and adopt new technologies can lead to significant improvements in productivity and efficiency. By empowering employees to leverage AI in their daily work, organizations can harness the full potential of this transformative technology and stay ahead in an increasingly competitive landscape.
In conclusion, the story of Estefania Angel and her colleagues highlights the power of bottom-up AI adoption. When employees are given the freedom and resources to explore and implement AI solutions, it can lead to a ripple effect that ultimately benefits the entire organization. As McKinsey's research shows, executives must recognize the readiness of their staff and support their efforts to drive AI adoption, rather than underestimating the impact that these self-taught innovators can have on the company's success.
