Editorial
Early adopters of AI realize that artificial intelligence is no longer an experimental technology, rather it is a business strategy capable of unlocking increases in productivity, efficiency and innovation at scale. The next wave of corporate growth will be driven by workers who know how to use AI as a tool, as a team member, and as an accelerator for re-designing their work. This means all employees-both women and men- must be fluent in AI, so they can enhance their productivity, creativity and be better positioned to compete in an evolving workplace.
But research from University of Phoenix determined there is a substantial gender difference in the use of AI at work. The survey of 604 HR leaders and workers in North America found women trail men in AI usage and confidence, with 36% of men reporting daily usage of the technology, compared with only 25% of women. In addition, even within the same profession, women are nearly 20 percentage points less likely than men to use ChatGPT.
Most troubling, there is a marked gender gap in recognizing the need to improve skills required to partner with AI in the workplace, with 48% of men saying they need skills to help them learn “how to work in partnership with Gen AI," compared to only 39% of women. Understanding how to partner with AI will increasingly become a crucial workplace competency as PWC estimates nearly 80% of companies are now using AI agents as a way of driving greater productivity and efficiency in the workplace.
How is the AI gender gap inhibiting widespread adoption of AI in the workplace? Understanding this can provide us with a clearer view of how to close the AI gender gap.
3 Reasons for the AI Gender Gap
Looking behind the numbers, the reasons for the AI gender gap appear nuanced. Women are more hesitant to use AI at work than men, often delaying AI experimentation and sticking to their familiar practices of work. Three key reasons emerge, including the greater possibility of women experiencing imposter syndrome, women’s concern for ethics and the perceived reputational risk of AI usage.
The Imposter Syndrome
Data shows that at least 70% of us will experience imposter syndrome at some point in our lives — a feeling which leads us to doubt our skills, talents and abilities. Studies consistently find that women experience imposter syndrome more often than men. This is consistent across a variety of industries and job roles. For many women, the AI gender gap is less about access to AI tools or their ability in using them, and more about their confidence in using AI tools in the workplace.
The Ethics of Using AI at Work
Harvard Business School Professor Rembrand Koning's research found women had higher levels of concern about the ethics of using AI in the workplace than men. According to this research, women consistently report higher rates of hesitation in using AI than men, with women placing greater weight on ethics, transparency and professionalism when evaluating if they should use AI at work.
The Reputational Risk of Using AI
Women historically have faced extra scrutiny over their skills, capabilities and technical abilities. In her book, “Artificial Intelligence for Business,” digital transformation expert Kamales Lardi contends that some women fear they may be perceived as “cutting corners” or cheating if they use AI at work. Women discern a higher reputational risk associated with using AI compared to men, and this influences their willingness to use AI in executing their job responsibilities.
This hesitancy in experimenting with AI can lead to stalled careers for women, especially as more companies follow the lead of Shopify, where AI literacy is a baseline expectation for all employees and influences hiring, performance reviews and consideration for promotions.
What Can Companies Do to Close the AI Gender Gap?
Businesses can take several steps to address the problem, including:
Cultivate the Next Generation of Female Talent in STEM Roles
The World Economic Forum estimates that while women make up almost half of total employment, they represent just 29.2% of all STEM workers. As the penetration of AI increases across organizations, STEM occupations will likely dominate the jobs of the future. Attracting greater numbers of women into these professions is a first step to closing the AI gender gap.
Schneider Electric is one company leading the way in creating a comprehensive strategy to increase the hiring, training and promotion of women entering STEM professions. It is proactively developing partnerships with both middle schools and high schools to expose young girls as early as 12-years-old to careers in STEM. Once hired, all Schneider Electric associates have full access to the company’s Data & AI School and the Digital Academy, accessing blogs, webinars, podcasts and “promptathons,” training geared to using AI in the flow of work.
Offer Both AI Training and AI Hackathons
Accessibility to training for all employees is crucial in closing the AI gender gap. Research from the Association for Talent Development finds more than 70% of employees are very or extremely interested in learning how to use AI, but less than a third of organizations provide such training.
At the same time, companies must go beyond AI literacy training to create AI hackathons—events where employees work together to create new AI products. These initiatives provide all employees with “AI sandbox time,” to test AI tools and take risks without fear of making mistakes. This is especially important for female employees who report having less confidence in partnering with AI at work.
Cisco's Teaming with AI, a type of AI hackathon, has led to increasing confidence in working with AI. Approximately 800 Cisco employees were invited to experiment with AI tools. The mandate was to use AI as you would coach an intern, learn to work with AI as your thought partner, check its work and question its output. After three months, the cohort generated 182 use cases of AI, and employee confidence in AI use jumped from 62% to 91%. These action learning practices provide employees with a safe way to experiment with AI.
Encourage Leaders to Be Role Models of AI Use
Leaders must stop issuing AI mandates and be role models for AI usage. An interesting example comes from Cornerstone CEO Himanshu Palsule, who regularly engages with the company’s internal secure Digital AI Hub before interviewing a new job candidate. After uploading a link to the individual’s LinkedIn profile, Palsule collaborates on possible interview questions and probes where there might be an experience or skill gap between the candidate and the company.
Then, after doing his own independent evaluation of the AI-generated feedback, Palsule shares his full analysis with the rest of the Cornerstone interview team and, importantly, with the job candidate. The prospective employee is then encouraged to give feedback and respond in the next round of interviews. CEOs who act, in effect, as Experimenters In Chief use AI in their workflow and spread AI literacy across the organization, encouraging their teams to adopt AI in their jobs.
The Time Is Now to Close the AI Gender Gap
Demonstrating AI fluency is becoming a baseline expectation for all employees, regardless of their role or level. Companies ranging from Shopify and Zapier to BlackRock and Cisco are mandating AI literacy for both current employees and new hires. Overall job postings requiring AI literacy have risen more than 70% from one year ago, according to LinkedIn.
Women will be left behind in hiring and promotions if the AI gender gap continues. Closing the AI gender gap is not only critical to establishing workplace equity but is an urgent business imperative to compete in an AI-powered workplace.
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Editor's Note: For more thoughts on AI adoption, see:
- Don't Let Women Get Left Behind: Why the Future of AI Upskilling Must Be Inclusive — Women still lag in AI adoption at work. The risk is we'll leave talented women behind and hurt business performance. Tips to close the gap.
- EZCater's Mark Christianson on Building an AI Mindset to Drive Adoption — EZCater's senior manager, digital workplace and AI strategy discusses their efforts to encourage AI adoption, with the goal of making every team an R&D hub.
- Why It's Critical We Have More Women in AI — For AI models to improve, we need people of diverse backgrounds and genders in the loop of the training processes to address biases.
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