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The narrative that women entrepreneurs receive less than 2% of venture capital (VC) funding has been widely circulated. It stems from data provided by Pitchbook, a respected research firm that delivers insights on global capital markets. However, a closer examination of their data reveals a more nuanced perspective. Pitchbook only studies investments funded by VC firms, which is a big part of the market but does not include the very substantial investments made by angel investors. Significant progress has been made in these early stages of the venture market. Twenty years ago, a mere 3% of angel-funded startups were led by women. Fast-forward to today, and women now account for well over 30% of angel-funded companies. Researching and monitoring these shifts have been a critical part of our own investing journey as the co-CEOs of Golden Seeds, an organization that invests exclusively in early-stage women-led U.S. companies. Back in 2004, when Golden Seeds was founded, there was a data void. Insights on women entrepreneurs and womens leadership were rarely collected because they simply werent considered important. Thankfully there is now more research into these topics. Pitchbook has been a leader in this effort, particularly as it relates to later-stage venture capital funding. But in the process of deciphering the data around female founders, a misleading narrative has inadvertently been created. Understanding the methodology behind theseand any venturestatistics is crucial to appreciating the strides made by women in the startup ecosystem. Here are the two biggest misrepresentations worth clarifying about women entrepreneurs and their ability to secure capital. Misinterpretation #1: Women get less than 2% of capital Countless articles, books, and panels have cited that only 2% of VC funding goes to women entrepreneurs. However, this interpretation is incorrect because Pitchbook collects data only on company founders, which excludes women in executive leadership roles or those who might move into executive roles and hold substantial equity. These women are not included in these calculations but they play important roles in the success of their companies. Furthermore, when including funding received by gender-diverse founding teams, the numbers reveal a more encouraging trend. In 2024, companies founded by at least one woman secured 23% of total VC capital, a considerable increase from just 9% in 2008. Additionally, the percentage of deals VCs invest in that include at least one female founder has more than doubled in the same time frame, from 12.2% to 25.4%. That number may in fact be even higher when you consider that this data excludes companies that have non-founder women in key roles who hold substantial equity. The growing presence of gender-diverse teams signals a positive shift in the funding landscape, as startup investors increasingly recognize the benefits of diverse leadership in driving business success. It also more accurately reflects the full universe of startups seeking capital today. Of course, the reality remains that 7580% of VC funding goes to companies with all-male founding teams (although we do not have information on the gender diversity of the management teams of these companies at the time of funding). More work is needed to get the venture industry closer to realizing gender parity. And its critical that we analyze the current data beyond just the single point of the initial founders. Misinterpretation #2: Female founders need a male cofounder to successfully raise VC capital One notable trend in the VC space is the increased success of mixed-gender founding teams in securing investment. While some may interpret this as a disadvantage for all-female teams, this conclusion is misleading. Founding teams form in many different ways, and most investors prioritize skill, determination, and the strength of the business over gender composition. Research consistently highlights the advantages of diverse teams, including broader skill sets, varied perspectives, and enhanced problem-solving capabilities. These benefits may make mixed-gender teams attractive to investors seeking to maximize their returns. And in our experience, founding teams are increasingly more likely to include both women and men. Systemic biases, however, still persist within the VC industry. Historically, VCs have favored investing in industries such as software and AIsectors where women have been underrepresented. Additionally, many investors prefer to back serial entrepreneurs with prior successes, a criterion that disproportionately benefits male founders due to historical inequalities in startup funding. Addressing these biases is essential to ensuring that innovative ideas from women and underrepresented founders receive the recognition and investment they deserveand that the progress made at the earliest stages of the market continues into later stages. Women are doing well raising capital from angel investors. They are receiving funding at a comparable yield to other entrepreneurs. (The yield is the rate at which companies seeking funding receive funding.) This trend has been growing for a long time now, as more women are actively pitching their businesses to angel investors. Forty-six percent of all companies seeking funding in 2023 were women-owned, up from 5% in 2004. In addition the growth of women angels, now over 40% of angel investors in the country, would seem to have played a significant role in increasing the share of funding. Its worth noting that the pace of VCs funding women-led companies has also been steadily improving, as described above, albeit slower than the progress in the angel market. And remember, VCs arent the only path to later-stage capital. Many entrepreneurs, both women and men, successfully seek subsequent funding from family offices, corporate ventures, and other high-net-worth individuals. Embracing a more empowered narrative Transforming an industry is challenging and oftentimes frustratingly slow. For 20 years, weve tracked the trends, educated investors, and rallied the support, both financial and otherwise, that women entrepreneurs need to grow their businesses. The world is recognizing the contributions and value of women-led companies and that progress shows up in the numbers when you look closely. But progress is a continuum, and the work isnt finished. Encouraging greater diversity among investors, expanding funding opportunities in traditionally male-dominated industries, and addressing biases in investment decision-making will be crucial in leveling the playing field. Moreover, continued advocacy and accurate representation of data are essential in shaping mindsets and initiatives that support women-led businesses. Perpetuating a narrative that overlooks the resilience and ingenuity of women entrepreneurs over the past 20 years discredits the progress weve made and subtly signals defeat. Whats needed is a nuanced understanding of the ecosystem so that a clearer picture of the barriers, progress, and opportunities of women-led companies is continually embraced and acted upon.
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For a while, the comforting narrative went like this: AI wont take your job. But someone using AI will. So, all you had to do was to use AI, and even if you lost your job you could take someone elses? The idea that you only needed to worry about AI secondhandvia another humanis in fact somewhat naive. AI is coming for your job directly. Not with fanfare or grand announcements, but through silent, pervasive creep: software agents booking meetings, writing reports, sending personalized emails, making decisions. There are even tools to send your digital clone to videoconference meetings, without people even noticing its not the real youyes, an AI deepfake of your professional self capable of intervening exactly as you would, if not more cleverly. Soon, fully autonomous agents will do entire workflows without human hand-holding. So, if you are an ambitious knowledge worker the question is no longer whether AI will automate aspects of your job. Its whether youll have the initiative and creativity to out-evolve the automation. The more you use AI, the more vulnerable you become Heres the paradox you need to internalize: the more you leverage AI to become hyperproductive, the more you expose yourself to being replaced by it. Its no different from making your memory or spatial awareness redundant by relying too much on Google Maps or Waze, or abandoning any hopes of memorizing anything because you can always reach for your smartphone. In an age where AI can handle the bulk of our cognitive labor, we risk intellectual atrophy. When Scott Galloway called AI corporate Ozempic he was onto something: a tool that suppresses the need to think, even as it sharpens our output. Our ancestors didnt need gyms or Pilates classes to stay fit; survival took care of that. But we might soon require the cognitive equivalentstructured, even artificial, forms of mental exertionjust to keep our brains from becoming intellectually obese. Efficiency is a trap. If your value to an organization is framed entirely in how quickly and predictably you can produce outputs, congratulationsyouve just turned yourself into a template. And templates are easy to automate. Does this mean you shouldnt use AI? Absolutely not. It means you have to reinvest your newfound time intelligently. Most organizations havent yet figured out what to do with the massive time savings AI is generatinglargely because managers, bless their quarterly obsessed hearts, lack the imagination to redesign jobs beyond output metrics. A recent survey by Deloitte found that while 94% of executives believe AI will dramatically shift work models, only 17% have a clear plan for what that shift actually looks like. Which brings us to the golden opportunity: you dont need to wait for your manager to reimagine your job. You can start now. Indeed, here are 10 strategies to de-risk being automated by AI: 10 Ways to Avoid Being Automated by AI Reinvest time saved by AI into higher-value, human-centric tasks. Use automation to eliminate drudgery, but spend that freed-up time deepening client relationships, mentoring colleagues, or solving problems that require empathy or judgment. Bridge communication gaps. Act as the translator between technical and nontechnical teams. AI still struggles with nuance, humor, and reading the emotional temperature of a room. Combine skills in unique and strategic ways. Be a generalist with spikessomeone who blends multiple competencies across fields, forming a professional fingerprint that’s hard to replicate. Make yourself unpredictable. Routine and predictability are blueprints for automation. Engineer variability into your tasks. Experiment. Cross disciplines. Add complexity that AI can’t model easily. Strengthen emotional intelligence. Cultivate empathy, persuasion, adaptability, and the ability to resolve conflictscore human capabilities that are still well outside AI’s reach. Own niche domain knowledge. Carve out expertise in verticals where context and nuance matterareas where even the best AI stumbles due to lack of real-world grounding. Invest in your personal brand. Write, speak, and share your thinking. Visibility creates optionality. People hire (and retain) people they know, not templates they can replace. Master AI tools in your domain. Dont compete with AIpromote it. Be the go-to person for AI literacy in your field. People who understand the tools are less likely to be replaced by them. Be the human-in-the-loop. AI often needs human oversightediting, refining, validating. These judgment calls are increasingly valuable. Stay curious and adaptable. Treat this era not as a tech shift but a cognitive revolution. Your ability to unlearn and relearn will be more important than any static skill set. Evolve faster than your environment You cant sit this out. You cant wait and see. The dodo bird strategystay passive, hope predators ignore youdidnt work out great for the dodo. Nor will it for the knowledge worker who thinks “AI-proofing” means hiding behind corporate inertia. You need to evolve faster than your environment. That means embracing AI as a tool, even as you actively cultivate the parts of yourself AI cant touch. Learn to become a less predictable, more creative version of yourself or be ready to face automation. The choice, for now, is still yours. So, where does that leave you? Somewhere between irreplaceable and obsolete, depending on what you choose to do next.
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Since ChatGPT sparked the generative AI revolution in November 2022, interacting with AI has felt like using a digital confession boothprivate, intimate, and shielded from public view (unless you choose to share). Thats about to change dramatically with Metas rollout of social features in its stand-alone AI app, released last week. Those quiet queriesWhats this embarrassing rash? or How can I tell my wife I dont love her anymore?could soon be visible to anyone scrolling through the apps Discover tab. If society is still grappling with how to navigate artificial intelligence, Metas changes risk throwing even more confusion into the mix. For tech-savvy users, the shift from private to public might be manageabletheyll at least be aware its happening. But most people arent monitoring every policy tweak from Big Tech, and may have no idea that what once felt like a private conversation with AI could now become public fodder, ripe for ridicule. (Meta did not respond to Fast Companys request for comment.) AI has quickly become a hybrid of search engine and digital confidant. Remember the embarrassment of accidentally posting a private message publicly? Now imagine that happening on a massive scale, as millions unknowingly expose deeply personal questions and experiences. This isnt a hypothetical concern. Posts from Meta AI users are already surfacing in the apps social feed, including verbal queries asked via voice mode, like one users question about folic acid, which also revealed her age and postmenopausal status. The Discover feed is shaping up to be a slow-motion privacy disaster, as users unintentionally share raw, unfiltered pieces of their livesfar from the curated, polished image weve grown used to displaying on social media. Meta said in a press release that its AI app aims to connect you with the people and things you care about, and calls the Discover feed a place to share and explore how others are using AI. While the company insists that nothing is shared unless you choose to post it, the app nonetheless nudges people to shareand oversharewhether they fully realize it or not.
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