The New Innovator's Dilemma: Fostering Young Talent in the Age of AI
Sometimes the feedback you get earliest in your career sticks with you the most.
I still remember the first meeting I led as a newly minted college graduate working in venture philanthropy. I arrived with a tidy, ambitious agenda that I launched into headfirst without any smalltalk. On our drive back to the office, my colleague Jennifer urged me to take a different approach: “You need to warm up a meeting; make conversation with people,” she said. “Treat them like they’re humans.”
The feedback kept coming. During my performance review that year, my manager Jonathan told me, “You’re too cynical.” At 23, it’s easy to think that exhibiting cynicism will make you appear wise — but it doesn’t. ”Sometimes you need to balance your skepticism with hope,” he added.
While I doubt my current colleagues would consider me a warm optimist, those moments of candid feedback early in my career, while hard to swallow, were invaluable. Their advice has helped me navigate a host of workplace environments with more awareness and grace than my younger self had the know-how to muster.
AI’s impact on early careers
For graduates today, the rise of AI may spell the end of entry-level work as we know it, along with the related opportunities for candid feedback and mentorship, for at least three reasons:
First, the supply of entry-level roles stands to shrink dramatically in coming years. Whole industries (some more than others) will pursue efficiencies that swap tech for talent. As The New York Times recently reported, some of the largest investment banks have wagered they could “cut back on their hiring of junior investment banking analysts by as much as two-thirds, and slash the pay of those they do hire, on the grounds that the jobs won’t be as taxing as before.”
Second, and at the same time, the expectations on entry-level workers are getting higher, leaving young talent at a steep disadvantage. As education and workforce analyst and investor Ryan Craig has pointed out, entry-level jobs increasingly (and ironically) require multiple years of experience. Craig argues that even if recent graduates have the skills required for a job, employers today are looking for more. “As AI makes skills more accessible, employers will place a higher premium on knowing what to do with skills [emphasis added],” Craig explains. “Do candidates have enough experience to know what to do with their skills — how to apply them in a specific job function and industry? For most employers, the only way to assess this is demonstrated experience. Otherwise, it could be months or even years before candidates know what they’re doing.” The result? A growing share of “entry-level” jobs requires two to three years of industry-relevant experience that most career starters lack.
Third, with more of their day-to-day tasks mediated by AI, even young employees who overcome these hurdles may have fewer opportunities for real-time human coaching, mentoring, and feedback.
Thanks to these trends, opportunities for many early career mentoring conversations could evaporate before young workers — and employers — realize what they’re missing.
This perfect storm stands to diminish the sorts of exposure, coaching, and support that build future leaders and innovators. These missed opportunities won’t show up in near-term key performance indicators (KPIs) or balance sheets. But they could dramatically narrow the pool of next-generation leaders, amplify industries’ tendency to overlook large swaths of talent, and risk widespread underinvestment in the very social capital that is proven to fuel the innovation economy.
The dilemma of investing in early talent
The counterintuitive ways that chasing efficiencies today can hinder growth tomorrow are not new. As Clay Christensen described in “The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail,” managers often struggle to see the long-term upside of lower-margin pursuits, in turn underinvesting in could-be breakthroughs. They chase the greatest profit margins to satisfy their most demanding customers while ignoring upstart opportunities in low-end and new markets. That dilemma is at the heart of a company’s susceptibility to disruption.
Disruptive innovation theory is a theory of competition between firms. But when it comes to mentoring early talent within firms, the same dynamics shape managers’ tradeoffs. Mentoring is a high-cost endeavor with poor incentives. It’s hard to justify investing in early talent whose added value starts off low and yields unpredictable returns. “This problem is analogous to The Innovator’s Dilemma, in which [companies] fail in spite of seemingly doing everything right,” said Martin Permin, founder of the mentoring platform Pelion. “The return on mentorship typically follows an S-curve, which means gratification is delayed. This means mentoring is often deprioritized by well-meaning, busy people.”
As AI infiltrates the workplace, resolving that dilemma is going to get even harder. With generative AI tools that can outcompete new graduates on a wide array of tasks, there will be even less slack in the system for early talent to perform basic tasks while they learn and are mentored on the job. In turn, we’ll likely see companies invest less in early talent and focus their mentoring energy on fewer and fewer hand-picked individuals. Whole sectors will be diligently using AI to unlock breakthrough efficiencies, all while shrinking their long-term leadership pipeline.
That also poses second-order threats to seeding innovation. Raj Chetty, Alex Bell and the team at Opportunity Insights discovered a troubling rate of what they dub “Lost Einsteins”: individuals who demonstrate high aptitude but, due specifically to lack of exposure and mentorship, don’t end up as innovators. Their findings underscore what we lose when exposure and support aren’t sufficiently widespread, particularly to groups on the wrong side of opportunity gaps. They estimate that if women, people of color, and children from low-income families became inventors at the same rate as white men from high-income families, innovation in the U.S. could quadruple.
In other words, shrinking mentorship opportunities won’t just give fewer individuals the chance to prove their leadership potential. It will also further neglect latent innovation potential across the population.
Weaving training and mentorship into education and work
This dilemma all points in one direction: the need to radically redesign the interface between education and work to ensure that a much wider cross-section of young people can access early career experience and mentorship opportunities once traditional “entry-level” roles that provide learning on-the-job are no longer an option. Otherwise, exposure to early career coaching and support will become yet another luxury good in an education market that tends to reward prestige over potential. Mentorship will become even more pay-to-play: to maintain a competitive edge, affluent students will simply buy experiences that confer experience and support in the form of unpaid internships where employers bear few costs, expensive specialized coaching and summer experiences, and time-intensive extracurricular offerings, leaving students with less time, money, and flexibility at an even steeper disadvantage.
For someone who studies innovation in education, this is a daunting, disturbing set of conclusions to consider. When it comes to ensuring that students secure good jobs, today’s educational institutions face their own innovators’ dilemmas, entrenched in broken business models with warped incentives. Aligning to the needs and shortcomings of employers is tricky when professors have immense autonomy over what and how courses are taught and administrators are measured by how many students enroll and persist, rather than how students fare in the labor market post-graduation. And most schools lack structures and incentives that tackle exposure and mentorship gaps head on: less than half of college graduates say they had access to a mentor, and numbers are similarly underwhelming among recent high school graduates.
Luckily, the last decade has seen important strides in more deeply integrating the worlds of training and work. More students are reaching beyond the four walls of the classroom and accessing work experience, through real-worldprojects that both hone their skills and connect them to professionals in fields that interest them. Some tools match postsecondary students with online work opportunities, supervised by real employers. For example, a company called Parker Dewey operates an online micro-internship marketplace where college students are paired with professionals offering paid virtual project work. Another company, Riipen, connects students with industry projects that provide academic credit instead of monetary compensation.
Other models, like that of Extern, offer a full-stack externship to students, overseeing and assessing students on companies’ behalf. Still others offer “earn and learn” opportunities for students to learn on the job through apprenticeship programs sponsored by companies but also subsidized by the government.
And approaches like Big Picture Learning and the CAPS Network start even earlier, allowing high school students to learn through part-time internships and client projects under the guidance of industry professionals.
What do these various models have in common? These organizations are absorbing some of the costs that employers won’t tolerate when it comes to supporting young talent. Crucially, however, they aren’t merely training talent for employers, but with them. In turn, students gain not only opportunities to perform real workplace tasks, but also access to feedback and coaching from working professionals.
Patient capital for next-generation growth
Innovative efforts like these have been lauded by education reformers and forward-thinking employers. But with the impact AI will have on entry-level work, these approaches need to migrate from the margins to the mainstream. As Craig describes, “[c]areer ladders will be cruelly yanked up and away so few will be able to reach the first rung.” Employers and educators need to advocate for and champion tight partnerships between education and industry that build that first rung back, investing in these pathways as a future talent strategy for employers, as a necessary learning opportunity for students, and as an engine for innovation for our economy.
Employers also need to keep an eye on, and help influence, what gets emphasized through these tighter partnerships. In an AI-powered world, even upskilling models aimed at widening the talent pipeline could discount the enduring role of human support and mentorship gained through real-world experience, particularly around leadership and management skills that are often absorbed through experience and exposure rather than through rote learning. Employers therefore need to invest in connecting future graduates with opportunities to work with, and receive feedback from, professionalswho are already engaged in the workplace.
Seeding those relationships early can pay long-term dividends for young adults, employers and our national economy, fueling recruitment, retention, and growth.
It bears noting that, paradoxically, some companies may try to use AI itself to tackle the very talent and experience gaps that AI is likely to worsen. Some firms are already exploring AI-enabled coaches, mentors, and ‘co-pilots’ to support young talent.
AI tools could build better career on-ramps. But I’m not persuaded they can sustain careers the way human coaching and mentorship do. I’m still in contact with Jennifer and Jonathan, and both have connected me to a wide network of investors and entrepreneurs who have contributed to my research. Managers who invest in young talent have a vested interest in their long-term success. If we automate that away, we’ll punish the next generation for our short sightedness.
About the Author:
Julia Freeland Fisher is the director of education research at the Clayton Christensen Institute and author of the book Who You Know: Unlocking Innovations that Expand Students’ Networks. She researches students' access to and ability to mobilize peer, mentor, and industry connections. She holds a BA from Princeton University and a JD from Yale Law School.