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Fast Company
14-07-2025
- Business
- Fast Company
Women are slower to adopt AI at work. Here's why
As a leader in technology for nearly 30 years, I have observed waves of innovation disrupt the global business landscape and trigger major shifts in the way we work. Now, as AI takes its place as the next big thing, the global workforce is facing an overwhelming demand for new skills and capabilities. In my new book, Artificial Intelligence For Business, I highlight the impact of AI on the future of work, specifically the skills gaps and job displacements, as well as future essential skills required in global organizations. Interestingly, there is a cautious instinct at play, specifically for women at work, as they weigh the promise of innovation with the risks of AI application. This hesitation may be deterring women from using AI at work, as worries about embracing AI could undermine their credibility or even invite harsher judgement, instead of highlighting their true potential. According to recent research conducted by Harvard Business School Associate Professor Rembrand Koning, women are adopting AI tools at a 25% lower rate than men, on average. Synthesizing data from 18 studies that cover over 140,000 individuals worldwide, combined with estimates of the gender share of the hundreds of millions of users of popular generative AI platforms, the research demonstrates the gender gap holds across all regions, sectors, and occupations. Although the study highlights that closing this gap is crucial for business and economic growth, and development of AI-based technologies that avoid bias, the reasons for the gap existing in the first place needs to be explored further. Let's unpack several ethical, reputational, and systemic hurdles that may lead women to be more reluctant to use AI at work and explore how companies can help bridge this gap. Ethical concerns First, ethical concerns of AI adoption tend to weigh heavily on women's minds. Studies indicate that women consistently rate hesitation about AI technology adoption higher than men do, placing greater weight on ethics, transparency, accountability, explainability, and fairness when evaluating AI tools. In one study that examines public perceptions of AI fairness across three societal U.S.-based contexts, personal life, work life, and public life, women consistently perceived AI as less beneficial and more harmful across all contexts. This caution may be evident as women hold themselves, and their teams, to strong ethical standards. These concerns are amplified by the rapid increase in 'black box' AI tools adoption across key business decision points, where the inner workings are opaque and hidden behind proprietary algorithms. As more female ethicists and policy experts enter the global field, they raise high-impact questions about bias, data privacy, and harmful consequences, feeling a special responsibility to get answers before signing off on innovative technology solutions. Women all over the world watched in dismay as leading AI ethicists were penalized for raising valid concerns over ethical development and use of AI. Famously, Timnit Gebru, co-lead of Google's Ethical AI team, was forced out after pushing back on orders to withdraw her paper on the social risks of large language models. Subsequently, Margaret Mitchell was also fired while standing in solidarity with Gebru and raising similar concerns. This move, among others, has sent a stark message that calling out potential harm in AI could make you a target. Extra scrutiny Alongside ethics, there is may be a fear of being judged at work for leaning on AI tools. In my experience, women often face extra scrutiny over their skills, capabilities, and technical prowess. There may be a deep-rooted concern that leveraging AI tools may be perceived as cutting corners or reflect poorly on the users' skill level. That reputational risk may be magnified when flaws or issues in the AI outputs are attributed to the user's lack of competence or expertise. Layer onto this a host of ongoing systemic challenges inherent in the business environment and AI tools that are implemented. For example, training data can under-represent the experiences of women in the workplace and reinforce the perception that AI products were not built for them. Nondiverse AI teams also pose as a deterrent, creating additional barriers to participate and engage. The consequence of the gender gap in AI is more than a discomfort. It can result in AI systems that reinforce gender stereotypes and ignore inequities, issues that are augmented when AI tools are applied for decision-making across essential areas such as hiring, performance reviews, and career development. For example, a recruitment tool trained on historical data may limit female candidates from leadership roles, not due to lack of capabilities, but because historically there have been more male leaders. Blind spots like these further deepen the very gap that organizations are trying to close. To counter this and encourage more women to use AI at work, organizations should start by creating an environment that balances guardrails with exploration. Additionally, they should build psychological safety by encouraging dialogue that gives space for concerns, challenges, and feedback, without fears of being penalized. Open and transparent communication addresses any expected fears and uncertainty that accompany AI use in the workplace. Build fail-safe sandbox environments for exploration, where the goal is to learn through trial and error and develop skills through experiential learning. Policy changes Changing policy and guidelines in the organization can prove effective in encouraging more women to use AI at work. Apart from clear guidelines around responsible AI use, policies specifically allowing the use of AI can help close the gap. In a study conducted by the Norwegian School of Economics (NHH), male students were less likely to view using AI as 'cheating.' Additionally, when policies forbid the use of AI, male students tended to use it anyway, while women adhered to the policy. When a policy explicitly allowing the use of AI was put in place, over 80% of both men and women used it, suggesting that policies encouraging the use of AI can help trigger more women to use it. Crucially, organizations should make a proactive effort to bring in more women into the AI conversation at every level. Diverse perspectives can prove effective in catching blind spots, and this approach sends a powerful message that representation matters. When women see their peers proactively shaping AI application in a safe, fair, and impactful way, they will feel more confident in participating as well.
Entrepreneur
20-06-2025
- Business
- Entrepreneur
The Best Defense Against Uncertainty Isn't a Single Strategy — It's a Mindset
In a business environment where the only constant is change, the small business owners who see the most success are the ones leaning into it. Opinions expressed by Entrepreneur contributors are their own. The small business landscape has never been more complex. Shifting consumer expectations, ongoing macroeconomic headwinds and evolving workforce dynamics are forcing business owners to rethink traditional strategies and embrace more adaptive ways of operating. A decade ago, the playbook looked different. Today, businesses face a swirl of uncertainty — tariff fluctuations, inflationary pressure, late payments and unpredictable policy shifts. Small businesses sit at the epicenter of these changes, asking: What's truly different? What lessons still apply? And how can we continue to adapt and grow in this high-stakes environment? A new reality: Pressure and possibility coexist Challenges are nothing new for entrepreneurs. But today's pressures are more intense, more layered and more sustained. From interest rate uncertainty to global trade tensions, small businesses often lack the cushion larger enterprises rely on to absorb these shocks. Yet in that vulnerability lies strength. Small businesses are uniquely agile. They can pivot faster, stay closer to customers and innovate with purpose. The ability to adapt swiftly is what separates those who merely survive from those who grow stronger in adversity. Related: 7 Reasons to Trust Your Gut When Starting a Business How today's small businesses are future-proofing for growth 1. Start with financial clarity Cash flow is the lifeline of any small business. But clarity goes beyond just watching the bottom line — it means being proactive about payments, forecasting accurately and understanding how external economic trends affect your operations. Late payments and rising costs are disruptive, but preventable. Business owners should work closely with accountants, bookkeepers, and local business groups to interpret policy and economic shifts. Staying informed isn't optional — it's your edge. Leaders who build financial agility into their operations will be far better positioned to seize opportunities and weather shocks. 2. Build operational resilience The pandemic reminded us how fast things can change. Businesses that successfully moved online, adapted their customer experience or adopted new tools proved how vital resilience and nimbleness are. But resilience isn't just for crisis response — it should be baked into your day-to-day operations. Continuity plans, regular process reviews and a willingness to iterate based on feedback are key. Agility is no longer a competitive advantage — it's a survival trait. 3. Innovate with intention Innovation doesn't mean chasing every new tool or trend. As AI and automation reshape industries, small business owners must ask: Is this the right investment now? Will it help solve a real challenge or improve efficiency? True innovation is rooted in purpose. Whether it's embracing digital tools that streamline operations or aligning your brand with social values, growth comes from clarity, not complexity. Technology is a powerful enabler—but only when aligned with your mission and customer needs. Related: How User-Generated Content Helps You Build Trust and Credibility 4. Stay deeply connected to customers Consumer expectations are evolving fast, and agility depends on staying in sync with those shifts. Case in point: nearly 90% of U.S. consumers prefer to pay by card — yet many small businesses still don't accept them. Adapting to preferences like this strengthens loyalty and accelerates cash flow. But flexibility is just part of the picture. Transparent communication — especially when external factors like regulation or supply chain disruptions arise — helps manage expectations and builds trust. Strong customer relationships aren't just good for business — they're the foundation for longevity. Final takeaway: Lean into the unpredictable In today's unpredictable world, the most successful small business owners aren't avoiding change — they're leaning into it. They're arming themselves with insights, embracing flexibility and leading with purpose. That mindset — not any single tactic — is what future-proofs a business.
Forbes
12-05-2025
- Business
- Forbes
Why Companies Looking For New Technologies Don't Manage To Innovate
Research shows tech outsourcing doesn't always push large firms to find novel solutions. In today's hyper-competitive business landscape, where technological change is constant and disruption looms large, company leaders often look outside their organizations for innovation. Big firms work with smaller start-ups to use their cutting-edge technologies in order to develop and introduce new products into the market. This phenomenon is referred to as 'technological sourcing,' and it's a win-win situation: The large company adds valuable new technologies that can improve its innovative and financial performance, while the small company gains access to funds and larger distribution networks. Managers often emphasize that tapping into external technologies is particularly valuable and, in some cases, acknowledge that new solutions are hard to come by within their large organizations. As former CEO Chris Viehbacher said regarding Sanofi's own internal R&D capabilities: 'There has to be some element of disruptive thinking to have innovation and I can tell you that big companies do everything to avoid any new thinking in their companies.' This leads to the question: Does external technology sourcing by large firms really add novel solutions to their technological repertoire? In our research published in the Strategic Management Journal, my co-authors and I found that, contrary to what some managers may believe, technology sourcing doesn't necessarily push large firms to pursue novel solutions. The reason? These decisions are guided by internal R&D teams, who are tasked with evaluating external technologies, and they tend to favor options that align with their existing knowledge, instead of branching outside of their comfort zone. Whether it's due to cognitive bias or established routines, the result is that, more often than not, large firms end up in-sourcing familiar solutions instead of adopting new, groundbreaking technologies. Ultimately, this leads to a disconnect between what managers claim they want to do (seek disruptive, novel solutions) and what they select in technology sourcing. And it can be a problem for companies wanting to enhance innovation through external collaborations. Why companies choose the familiar While this phenomenon can apply to many highly technological industries, my co-authors and I looked at biopharmaceutical companies between the years 1995 and 2015, a period of prominent collaboration between established firms and specialized firms working at the technology frontier. The narrative coming from the large firm CEOs at the time was to go beyond external boundaries and seek highly novel technologies. But after analyzing in-sourcing events like licensing, alliance agreements and acquisitions, we found that there was a clear preference for familiar solutions to problems. It's not that R&D teams weren't able to find the novel, core-shaking ideas top management pushed for; it's just that when it came time to decide where to allocate their money, they chose technologies similar to what they had already worked with. In a way, it's the human condition: better to deal with what you know. But, for companies, it can lead to inertia or failure to adapt to changing markets. (Think of VHS tapes' sudden irrelevance with the rise of DVD players, or typewriter companies' dwindling market when computers became more affordable.) Not every firm we looked at pursued the familiar all the time, however. Companies that had previously gone through unexpected failures – for example, unsuccessful drug trials – were more likely to get creative when searching for tech solutions outside their companies. That's because such an experience pushed the company to reassess the approach it was taking, as well as its judgement on where to allocate funds and resources. This, in turn, made them more open to novel tech solutions. The benefits of branching out We found that when top managers pay attention to specific problems (in our case, therapeutic disease areas like oncology or neurology), it can be an impetus for the R&D personnel to consider a broader range of technologies and select more novel solutions that the firm has not yet tried. It's crucial that mangers be aware their narrative and goals may not always be in sync with the firm's ultimate actions when it comes to seeking out novel technologies. However, we know that in a fast-changing world, the exploration of groundbreaking solutions (especially those with which a firm is not yet familiar) can have highly beneficial results. For biopharmaceutical companies, for example, monoclonal antibodies was a novel biotechnology that led to the creation of some of the most commercially successful drugs. Similarly, in the tech sector, companies like Apple and Google have famously embraced external ideas – from acquiring Siri to buying Android – and succeeded because they could integrate these technologies into a coherent, novel offering. Netflix is also an example, moving from DVD rentals to online streaming. So what can managers do to ensure their companies don't default to familiar technologies? First, managers can embrace opportunities that emerge from failures, as those may enable firms to become more receptive to novel solutions. It's also important for top managers to be more involved in the process in general. Simply establishing a unit to explore cutting-edge technologies or setting a mandate to seek novel solutions is not enough, as our research shows. Of course, attention and time are two things managers often lack, so that can be tricky to navigate. Ultimately, it's important for top management to keep in mind the influence they have on R&D teams, and the role they play in actively counteracting biases. It all starts with being aware of how their narrative and their 'quest for novelty' aligns with the actions the company takes when sourcing external technologies. By Thomas Klueter, professor of Entrepreneurship and Analysis of Business Problems at IESE Business School.
