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For venture capital, 2025 was all about artificial intelligencea trend that’s all but certain to carry into 2026. More than half of all VC dollarsand 36% of total dealsnow flow to AI companies, according to a recent Silicon Valley Bank report. Crunchbase recently reported that 14% of all global venture investment in 2025 went to AI giants OpenAI and Anthropic. The year also saw huge deals like a $2 billion seed round raise by Thinking Machines Lab, the AI startup founded by former OpenAI CTO Mira Murati. AI deals are also often closing quickly, with investment rounds that once would have taken weeks to close being handled in a manner of days, says Tim Tully, a partner at Menlo Ventures. You’re seeing people raise these large rounds with no decks, which is kind of shocking, or not even absolute clarity around precisely what the company is going to do, he says. Youre seeing funding of teams over what the team is doing. But even amid speculation that the industry could be in a bubbleand some signs of public fatigue with the technology thats snuck into everything from therapy sessions to childrens toysinvestors and industry observers say the AI push will continue in 2026. TAM explosion In some ways, AI mimics the investment wave around other recent transformative technologies, like the rise of the PC, internet, and mobile phone. New technologies come, and they’re transformative, and that drives a lot of investment, says Steven Neil Kaplan, a professor at the University of Chicago who studies venture capital. Some of them work out, some of them don’t, and hopefully the world becomes more productive. But Michael Carmen, co-head of private investments at Wellington Management and the coauthor of a venture capital outlook report the firm released in December, says AI companies have recently been growing revenue at a historically fast ratequicker than previous generations of software-as-a-service (SaaS) companies. Widespread internet use has given new AI products essentially instant access to a huge potential market, Carmen adds, noting, When you think about the [total addressable market] of AI over the longer term, it could be the largest TAM of anything that we’ve ever seen in technology. AI is increasingly competing with traditional SaaS businesses for both customers and investors, says Saagar Bhavsar, partner at Begin Capital. For one thing, artificial intelligence has businesses wondering if its more viable to build software tools in-house with the aid of new coding assistants and other AI agents. If your cost of building the software and time of building the software is going close to zero, the whole idea of SaaS disappears, says Sergey Gribov, general partner at Flint Capital. Even without AI, some companies have begun to reconsider the sprawling set of cloud services theyve signed up for over the years, including deals they signed during the chaos of the pandemic shutdowns, Bhavsar says. And investors are taking note. Few people are calling themselves B2B SaaS investors anymore, even if they did that historically, he says. Bhavsar says VC firms and their investors are showing an increasing appetite for new kinds of opportunities, including investments in computing hardware, data centers, physical computing, and robotics. Theres also a rising interest in so-called AI roll-ups, popularized by VCs like General Catalyst, where VC-backed businesses buy services businesses like IT companies, call centers, or accounting firms with the goal of making them more efficient through AI adoption. Its historically more like private equity investment, but the tech tie-in has made it appealing to the VC world. The most interesting part right now is that any type of deal can be a VC deal, Bhavsar says. Any pitch can be a VC pitch if they pitch it right. AI models, running on powerful graphics processing units like the ones that have helped chipmaker Nvidias market value skyrocket, could become the basis for a wide range of applications. (Its similar to the wave of software developed atop Microsoft Windows and Intel chips in the PC era, suggests Carmen.) VCs are looking to invest in companies building those AI-powered apps, though theyre also still enthusiastic about the frontier labs developing the models and core technology that help AI process text, images, video, and sound. That market, after all, still sees fierce competition among companies like OpenAI, Anthropic, and Google, and new startup labs emerging like Muratis Thinking Machines or Tokyo-based Sakana AI. I think there will be a lot more of these people coming out of the bigger names, or researchers coming out of academia wanting to start these research labs, says Christine Tsai, founding partner and CEO of 500 Global. Theres also roomand VC appetitefor new, innovative AI models for other areas besides language and image processing, like autonomous vehicles and robotics. We believe there’s going to be a company that’s going to build the robotic brain, if you will, that will power many different apps, many different use cases, says Janelle Teng, partner at Bessemer Venture Partners. Fintech, defense tech, and the rest Still, AI hasnt completely captured the VC sector. Other areas seeing investor interest include fintech, particularly after the 2025 IPOs of companies like Klarna, Circle, and Chime, as well as space and defense tech, Teng says. Space and defense startups also benefit from the Trump administrations push to overhaul military procurement and move business away from big defense contractors, while fintech startups may take advantage of the administrations deregulatory approach to finance. VCs that in the past wouldnt have invested in defense tech have also been encouraged by the success of Anduril, according to Carmen, who notes that another area of excitement for VCs is health tech, including wearable technology and other tools that help provide consumers with information to manage their health. One open question for VCs and other startup investors is whether the IPOs and acquisitions that characterized 2025 will continue into the new year. There was a lot more activity and liquidity in the markets, and we saw it in our own portfolio, in contrast to years prior, where it was extremely dry and felt like things were still frozen, Tsai says. A number of big startups are reporedly preparing for IPOs, including AI companies OpenAI and Anthropic and Elon Musks SpaceX. Their success could spur more initial offerings. Those transactions provide early-stage investors with funds for the next round of investment, though with big companies staying private for longer than in previous tech booms, there are often other ways to sell stock through company tender offers and other private deals. And, if recent activity is any indication, theres no shortage of investor cash pursuing stakes in startups, particularly around AI. Only time will tell, of course, which of those investments will prove wise, and whether the ever-escalating valuations of so many AI companies will last. The thing that’s hard to know is, are we in 1997, or are we in 1999, says Kaplan. VC investments in 97 did very well. VC investments in 99 did horribly.
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E-Commerce
2026 will be a crucial inflection point for businesses. The data are strikingthe proportion of employees using AI in their role in the U.S. doubled between 2023 and 2025. Across the Atlantic, 30% of EU workers are already using AI in their jobs. And according to Gartner, by 2026 more than 100 million workers will collaborate with robo-colleagues. The question for the coming year, then, is no longer whether AI will transform your organization, its whether your leadership team will guide that transformation thoughtfully or let it happen haphazardly, tool by tool and team by team. I have spent much of the past year working with my research team and industry partners to think through the most pressing challenges organizations face as they implement AI at scale. Drawing on this work, I have identified seven key priorities for leaders preparing for 2026. These arent isolated tactics but interconnected imperatives that, taken together, provide a road map for building resilient, adaptive, and human-centered organizations in the age of AI. {"blockType":"mv-promo-block","data":{"imageDesktopUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/creator-faisalhoque.png","imageMobileUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/faisal-hoque.png","eyebrow":"","headline":"Ready to thrive at the intersection of business, technology, and humanity? ","dek":"Faisal Hoques books, podcast, and his companies give leaders the frameworks and platforms to align purpose, people, process, and techturning disruption into meaningful, lasting progress.","subhed":"","description":"","ctaText":"Learn More","ctaUrl":"https:\/\/faisalhoque.com","theme":{"bg":"#02263c","text":"#ffffff","eyebrow":"#9aa2aa","subhed":"#ffffff","buttonBg":"#ffffff","buttonHoverBg":"#3b3f46","buttonText":"#000000"},"imageDesktopId":91420512,"imageMobileId":91420514,"shareable":false,"slug":""}} 1. Embrace Regenerative Leadership Principles Traditional leadership models that focus on efficiency and extraction are creating burned-out workforces and fragile organizations. As AI increases the temptation to pursue short-term gains, leaders must shift toward regenerative approaches that actively restore and enhance human, environmental, and technological resources. Regenerative leadership means moving beyond sustainability to create systems that actually improve over time. This involves: Adopting systems thinking to see your organization as an interconnected ecosystem Prioritizing employee well-being alongside productivity Measuring impact beyond profit to include ethical AI usage and community impact Companies like Patagonia, Interface, and Unilever have demonstrated that this approach doesnt sacrifice performance. Rather, it enhances it through improved brand loyalty, employee engagement, long-term resilience, and higher growth. The key is recognizing that AI should augment human potential, not exploit it. Leaders who build purpose-driven, people-centered strategies will create organizations that dont just survive disruption but evolve through it. Read more: The age of AI requires a new kind of leadership 2. Transform Your Organization, Not Just Your Training Most organizations treat AI reskilling as a training problem. But AI will cause systemic change that affects virtually every function and workflow, so preparing employees for the coming revolution requires more than just teaching them how to use AI tools. Fundamentally, it requires organizational redesignreimagining what work looks like in the AI age and transforming the organization to enable that work. Success requires workin in three interconnected dimensions: Rebuilding the infrastructure of work (providing the tools, data access, and workflow redesigns that make AI adoption possible) Redesigning interconnected roles across the organization simultaneously (because when one role changes, every connected role must shift) Cultivating a learning culture that prizes experimentation over perfection and treats failure as data rather than disgrace Read more: What AI reskilling really requires 3. Master the Art of Leading AI-Augmented Teams Throughout history, the core competence of leadership has always been guiding humans to achieve defined goals. But in the age of AI, leadership will take on a new meaning: leading hybrid teams in which humans and AI systems work side by side. Leaders must learn how to leverage the unique strengths of each while creating the context in which those unique strengths multiply by working in concert. In order to succeed, leaders must: Personally engage with AI tools themselves, so they can understand and eventually model effective collaboration Cultivate clarity of purpose to discern what is actually worth doing in a world in which AI makes everything possible Become moral agents capable of navigating urgent ethical questions surrounding the use of AI Develop the enhanced emotional intelligence needed to guide teams through an often unsettling transition Read more: The 7 secrets to successfully leading AI-augmented teams 4. Build a Balanced AI Portfolio: Moonshots and Mundane Wins Successful AI transformation requires a well-balanced innovation portfolioa deliberately diversified mix of initiatives spanning different risk levels and time horizons. Leaders must grapple with big-picture questions about industry transformation while simultaneously identifying tactical opportunities for near-term deployment. The immediately practical projects create the foundationand fundingfor more ambitious undertakings. Evaluating which initiatives deserve resources requires systematic assessment across multiple dimensions: technical feasibility, true investment costs (including organizational attention), risk-reward balance, alignment with core purpose, and realistic timeframes. In our book Transcend and a companion piece in Harvard Business Review, we provide comprehensive toolsthe OPEN and CARE frameworksfor this strategic evaluation and portfolio management. Critical to all of this is engaged leadership at the C-suite level. CEOs cannot simply delegate AI projects to technical leaders. Instead, they must orchestrate the entire innovation portfolio to maintain strategic coherence. Read more: Why your organization needs both AI moonshots and mundane wins 5. Protect Your Organizational Uniqueness When everyone uses the same AI tools that have been trained on the same public data, outputs converge toward generic mediocrity. The quirks, the specific language, the unique ways of thinking that define your organization get smoothed into statistical averages. Competitive advantage in 2026 will come from authentic differenceleaning into what makes you, you. You can do this by: Auditing your uniqueness: Identify what is different and distinctive about your organization. Creating proprietary datasets: Whenever possible, use internal data rather than generic datasets that everyone has access to. Establish AI-free zones: Maintain places where only humans get to operate. Adversarial prompting: Use AI to critically evaluate your conclusions rather than to confirm them. The goal isnt to reject AI but to use it strategically while preserving the distinctive elements that make your organization valuable. Read more: How AI is creating a crisis of business sameness 6. Reinvent Middle Management for the AI Era AI is eliminating traditional middle-management functions at an unprecedented rate. Gartner predicts that through 2026, 20% of organizations will use AI to flatten their structures, eliminating more than half of current middle-management positions. And by 2028 and 2029, AI-driven jobs chaos will force organizations to reconfigure, redesign, split, or fuse more than 32 million jobs every year. There are significant efficiency gains to be made here. But organizations must be careful not to throw the baby out with the bathwater. Rather than simply trying to eliminate as much of middle management as possible, the task is to streamline it intelligentlymiddle management is still important, but its role must be fundamentally reimagined. Orchestrating AI-human collaboration: Understanding how to integrate AI with humans Serving as agents of change: Guiding organizations through continuous AI-driven disruption Coaching for a new era: Mentoring employees through constant reskilling and role evolution To successfully navigate this transformation, organizations must reskill middle management to enable them to succeed in their reimagined roles. Read more: How AI is killing (and reinventing) middle management 7. Know When to Changeand When to Hold Steady In a profoundly uncertain world, and a business environment in which the only constant is disruption, the most critical leadership skill of all might well be discernment: the wisdom of knowing what to preserve and what to transform. Effective leaders distinguish between their organizations core identity (the what that they must not compromise) an their methods (the how that can be endlessly reimagined). In times of change, it is essential for leaders to be steadfast about the former while being completely flexible about the latter. Read more: How to know when (and when not) to make a change An Integrated Path Not every organization will need to emphasize all seven priorities equally. A company with a strong and adaptable middle-management culture may focus elsewhere; one already grounded in regenerative principles can move quickly to portfolio building. The point is not to tackle everything at once but to recognize that these are the dimensions along which the AI transformation will play out, and to make deliberate choices about where to invest attention. What leaders cannot afford is drift. Organizations that treat AI adoption as something that happens to themtool by tool, team by team, without strategic intentwill find themselves shaped by the technology rather than shaping it. The difference between leading and following in 2026 will come down to whether these choices are made consciously or by default. The leaders who prepare their organizations for 2026 by tackling these priorities wont just survive the AI revolution. Theyll shape itbuilding organizations that are more resilient, more human, and more capable of creating lasting value in an age of unprecedented technological change. {"blockType":"mv-promo-block","data":{"imageDesktopUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/creator-faisalhoque.png","imageMobileUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/faisal-hoque.png","eyebrow":"","headline":"Ready to thrive at the intersection of business, technology, and humanity? 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With President Trump back in the White House, this year has brought a barrage of executive orders and edicts that target workers. Trump reduced the minimum wage for federal contractors, made major cuts to the Occupational Safety and Health Administrationwhose express mission is to keep people safe in the workplaceand attempted to undermine collective bargaining rights for federal workers. He has also, of course, set his sights on dismantling diversity, equity, and inclusion (DEI) programs across both the federal workforce and corporate America. Still, theres a glimmer of hope for workers: Many states have taken it upon themselves to enshrine policies like paid leave and pay transparency, with some of them now turning their attention to how the misuse of artificial intelligence in hiring could harm workers. Here are some of the laws and policies that will take effect in 2026many of which continue to push forward on important issues for workers despite what the federal government has in store. Anti-DEI measures Trump has made anti-DEI policies a focal point of his time in office, kicking off this year with a number of executive orders that forced federal agencies to terminate all DEI-related policies and programs and stripped away a requirement for federal contractors that had been a crucial element of diversifying the workforce. That means, going into 2026, all federal DEI programs have been eliminatedbut there are a number of state-level bills that seek to curtail how DEI is utilized in hiring and across public education. In Ohio, for example, legislation that passed this year prohibits any consideration of DEI in hiring decisions at public colleges and universities. Similar laws in Kansas, Idaho, and Wyoming will curtail DEI programs for hiring across higher education. Meanwhile, the Equal Employment Opportunity Commissionthe agency tasked with enforcing antidiscrimination laws in employmenthas made clear that corporate DEI programs will be under greater scrutiny going into 2026. The use of AI in hiring As companies have embedded AI into their hiring process, many HR teams have started relying on automated résumé screeners and other AI tools. In 2026, three laws will take effect at the state level to create some guardrails around how AI is being used for employment decisions, following in the footsteps of New York City and California, which have already adopted AI in hiring laws. Colorado and Texas are introducing broader AI governance laws that also explicitly call for more oversight of how the technology is used in the hiring process to ensure it is not discriminatory. In Illinois, the law is an amendment of the states Human Rights Act and regulates how workers are impacted by the use of AI in all employment decisions. At the federal level, a bipartisan bill introduced in Congress last month wouldif passedforce employers to disclose when layoffs are caused by AI. Minimum wage The minimum wage continues to rise, year after year, as states have raised the wage floor in response to worker advocacy. As 2026 rolls around, 20 states will have enacted and started phasing in a $15 minimum wage, with hourly wages actually crossing $15 in a total of 11 states by the end of next year. Since 2012, a total of 15 states have adopted a $15 minimum wage, according to the National Employment Law Project, in no small part because of the Fight for $15 movement that originated among fast-food workers. By the end of 2026, many workers will see even greater pay increases as the minimum wage is boosted to $17 across 53 cities and localities. A handful of states have also approved changes to the subminimum wage, which typically pays tipped workers a lower hourly rate. (There have been several proposals at the federal level to eliminate the subminimum wage altogether, but nothing has successfully passed.) Paid leave While the efforts to pass federal paid family leave have more or less come to a standstill, a handful of states have kept pushing to secure those benefits for their workers. In Delaware, Maine, and Minnesota, a paid leave program will take effect in 2026, joining 10 other states that have already introduced the benefit. Meanwhile, states like Connecticut are making significant expansions to their paid sick leave program, now requiring companies with as few as 11 employees to provide leave. (By 2027, even employers with one worker will have to do the same.) In total, about 20 states now offer paid sick leave in some capacity, as these laws have picked up steam in recent years. A number of cities and localities also provide paid leave, even in states like Pennsylvania that dont have broader coverage. Pay transparency Pay transparency laws have grown in popularity over the last four years, in an effort to arm workers with more information as they go into salary negotiationsor before they apply for a job at all. These laws often require employers to disclose a salary range in all job postings, though some states have only mandated that employers verbally share salary information. This year, Massachusetts and New Jersey adopted laws that require pay ranges in job listings, bringing the total number of states with these laws on the books to 14. At the local level, some cities in Ohio have started requiring salary disclosures, as is also the case in Washington, D.C. Salary transparency laws also often prohibit employers from asking about a candidates salary history during the interview process and using that to determine their compensation.
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