Written by Jeffrey Bussgang, General Partner and Co-Founder, Flybridge Capital Partners; Senior Lecturer, Harvard Business School
January 15, 2026
My HBS students are in the process of returning to campus and, bluntly, kind of freaking out. In just a few short months, they will graduate into the toughest job market in history.
The traditional MBA employers have all cut back their hiring. Big Tech? They’re growing 20-30% year over year with flat headcount. Consulting firms? They’re shrinking their associate classes while driving greater profitability. Investment banks, Wall Street, PE firms? Same story.
Every generation inherits a story about work. The defining narrative for this generation is the rise of AI and its far-reaching impact on productivity, which is hollowing out many traditional entry-level roles. Society is becoming more productive than ever, yet traditional jobs are becoming increasingly scarce.
The result? Welcome to GenE: the most entrepreneurial generation in history. GenE is not a demographic; it is a psychographic forced by economic necessity.
In an economy where AI relentlessly automates tasks, particularly the simpler tasks traditionally performed by entry-level professionals, entrepreneurship may become the most viable path to broad-based economic participation. Not for everyone to build unicorns—but for millions to create their own economic agency.
Why Entrepreneurship Becomes the Default, Not the Exception
AI is changing the labor market asymmetrically. It does not eliminate entire industries overnight; it removes slices of work—analysis, coordination, content creation, and routine decision-making. Tasks that previously took days are taking seconds. AI agents are being created and employed by organizations to take complex actions. The net effect is fewer people needed to produce the same output. This creates a paradox: society becomes more productive, yet fewer traditional jobs are available. When productivity rises without proportional job creation, the old social contract frays. I wrote about this at the end of last year (The AI Wildfire, Unemployment, and Wealth). This year, I’m focused on the implications.
Historically, entrepreneurship was constrained by capital, expertise, and scale. Those constraints are eroding. AI compresses the distance between idea and execution. A single person can now research a market, prototype a product, acquire customers, and operate a business with leverage that previously required a team. This shift turns entrepreneurship from an elite activity into a practical option for far more people.
In that sense, GenE is not simply choosing entrepreneurship; it is being pushed toward it by economic necessity and pulled toward it by technological feasibility.
GenE and The Experimentation Mindset
At the core of GenE is not just ambition, but a fundamentally different operating model. In The Experimentation Machine, I argue that startups win not by having perfect plans, but by running more experiments, faster, and learning sooner than their competitors. AI supercharges this approach. It collapses the cost of experimentation across product development, go-to-market, and operations.
This generation intuitively understands that advantage no longer comes from static expertise, but from the velocity of learning. GenE founders do not wait for certainty; they prototype, test, discard, and iterate. In the 20th century, we competed on scale; in the AI era, we compete on the rate of experimentation. AI becomes a cognitive exoskeleton—handling the heavy lifting of data synthesis and routine decision-making so humans can act as the central nervous system using their judgment, creativity, and discernment.
The result is the rise of what I call the 10x Founder: individuals who use AI to operate with an order of magnitude more leverage than prior generations of entrepreneurs. But what is often missed is that this dynamic does not apply only to venture-backed tech startups. It applies equally to entrepreneurs in traditional, real-world industries.
GenE Is Not Only Founders: The Era of the 10x Joiner
It is important to clarify something at this point. When I talk about GenE as the most entrepreneurial generation in history, I do not mean that everyone must be a founder.
In Entering Startupland, I wrote extensively about startup joiners—people who choose to build their careers by joining early-stage companies rather than founding them. There is real honor, learning, and opportunity in that path. In many cases, it is the smarter path.
Entrepreneurship is not defined by the cap table. It is defined by risk, responsibility, and rate of learning. Great joiners take on ambiguity, operate without playbooks, and own outcomes that materially shape a company’s trajectory. They are builders, not passengers.
AI amplifies this distinction. In a world where leverage is increasingly individual, the gap between founders and joiners narrows. A single exceptional joiner—armed with modern AI tools—can now operate with impact that once required an entire function. Product managers, marketers, operators, engineers, and sales leaders can all be “10x joiners,” compounding their judgment with AI in much the same way founders do.
This matters deeply for GenE. Not everyone should start a company. But many more people should work as if they are building one: embracing experimentation, taking ownership of real problems, and learning at entrepreneurial velocity. Early-stage companies remain one of the best environments for this kind of growth, precisely because they reward initiative rather than tenure.
Seen this way, GenE is not a generation of founders versus employees. GenE is a generation of owners versus renters of their careers. Founders and joiners sit on the same spectrum—differentiated by role, not mindset.
TopLine Pro and the New Entrepreneurial Middle
Our portfolio company TopLine Pro is a powerful illustration of this shift. At first glance, it is a software company. In reality, it is an entrepreneurship multiplier.
TopLine Pro serves home service professionals—plumbers, electricians, landscapers, contractors—jobs that AI will not replace because they require physical presence, trust, and skilled labor. These are not disappearing professions; they are durable ones. Yet historically, these entrepreneurs have been underserved by technology, particularly in marketing and customer acquisition.
TopLine Pro uses AI to solve that problem at scale. It allows the local roofer to spend more time on the job and less time fighting SEO algorithms and administrative billing. By automating the end-to-end business operations – from website creation to personalized outreach to customer engagement – the company enables millions of small, local business owners to compete more effectively in their markets. What is striking is not just TopLine Pro’s growth with a lean team, but the downstream impact: thousands of independent entrepreneurs generating real revenue in the physical economy, supported by AI leverage rather than displaced by it.
This is a critical point for GenE. The most entrepreneurial generation will obviously not consist solely of software founders. It will include tradespeople, service providers, and local business owners who use AI to amplify their productivity and independence. Entrepreneurship is a rich spectrum, not a binary category.
AI as a Tool for Economic Agency, Not Just Efficiency
Much of the public conversation about AI fixates on efficiency gains inside large organizations. That framing misses the more consequential shift. AI is not just making firms leaner; it is making individuals more capable. When individuals gain access to tools that once belonged only to institutions, power decentralizes.
For GenE, this means entrepreneurship is no longer about escaping the system; it is about reconfiguring it. Small teams can serve fragmented markets that were previously unreachable. Niche businesses become viable. Local expertise scales digitally without losing its human core.
This dynamic also reframes the unemployment debate. If AI reduces the demand for traditional labor, the solution is not to slow innovation. It is to expand the set of people who can create value independently. Entrepreneurship becomes a societal adaptation mechanism.
What Institutions Must Do to Support GenE
None of this happens automatically. A more entrepreneurial generation requires supportive infrastructure. Education systems must teach experimentation, not just credentialing. Policy must reduce friction for small business formation and failure. Capital must flow not only to the top of the power law, but to the long tail of sustainable, cash-flow-positive ventures.
Most importantly, we must update our cultural definition of success. GenE success will not be measured only by IPOs or unicorns, capital raised or employment counts, but by resilience, adaptability, and servicing real customer needs.
At HBS, we are reconfiguring our curriculum in three ways – something that other institutions will want to consider as well:
- Re-imagine our mission as training leaders who can create opportunities, not just manage them.
- Shift our curriculum to include more learning by doing, pushing our students to get hands-on with the modern AI tools.
- Modernize our case studies for the age of AI, exposing our students to the best practices of 10x founders and joiners.
The Choice Ahead
GenE is already forming. The only question is whether we recognize and support it. AI will continue to reshape work whether we are ready or not. Entrepreneurship offers a path forward—not as a cure-all, but as a release valve for creativity, dignity, and economic participation.
This generation may not inherit stable careers. But it can inherit something more powerful: the tools and mindset to build its own future.
