The deal was supposed to be simple: keep the desk job, collect the paycheck, and ride it to 65. A new study suggests AI may be disrupting that deal for workers who thought their experience and seniority gave them a safer runway.
You are not too senior to be affected. In some exposed occupations, you may be exactly the worker facing a career plan that needs revisiting.
The Hard Truth About AI And Older Workers
Boston College’s Center for Retirement Research examined whether older workers in AI-exposed occupations are leaving employment more often. Its Issue Brief 26-13, by Geoffrey T. Sanzenbacher and published June 30, 2026, combines the Tufts Digital Planet AI Exposure Index with Current Population Survey data. It tracks workers first observed between January 2014 and April 2025.
One central finding challenges a common assumption: workers ages 55 and older hold jobs that are just as exposed to AI as mid-career workers. Exposure is especially high in work involving data and coding; lower-exposure jobs more often involve physical work with machinery or people.
Before ChatGPT launched in November 2022, high-exposure jobs had a longevity advantage. In the study’s sample, 11.7% of workers in high-exposure jobs left employment over a year, compared with 14.1% in low-exposure jobs. After the launch, highly exposed jobs saw relative increases in transitions out of work, including a significant share into unemployment, meaning people were out of work and still looking. The historical career-longevity advantage of those jobs was greatly reduced.
The brief’s modeled predictions put the contrast in focus: predicted transitions out of work for computer programmers rose from 8.7% to 11.1%, an increase of more than 25% relative to the earlier rate. For painters, among the lowest-exposure occupations in the comparison, the predicted increase was about 2%.
The potential stakes are particularly sharp for people in higher-paying jobs, unlike earlier automation waves that often hit lower-wage work first. Yet these numbers do not say that AI has already eliminated entire professions, or that every experienced worker in them will lose a job.
The brief also reports an adoption gap. Citing an AARP survey, it notes that among workers 55 and older, 18% see AI solely as an opportunity, while 28% see it solely as a threat. Generative AI use is lower among older workers: 18% of people ages 50–64 use it, and even the 42% usage rate among decision-makers 55 and older trails workers in their 30s and 40s.
That gap matters when technology changes job expectations. But the study found increased transitions to unemployment, not a significant increase in retirement itself. Involuntary separation can still push someone toward an earlier-than-planned retirement. As policymakers debate longer work lives amid Social Security pressures, a disrupted late-career job can work against that goal.
The Pipeline Is Already Cooling
The next generation is also responding to a different market signal. National Student Clearinghouse Research Center data for spring 2026 show undergraduate enrollment in computer and information sciences fell 8.4% at four-year institutions and 11.2% at two-year colleges, while overall undergraduate enrollment grew 1.3%.
That follows a decade-long surge: computer science bachelor’s degrees more than doubled, from 43,066 in 2010–11 to 108,503 in 2021–22-an increase of 151.9%. In its May 2026 analysis, Revelio Labs reported that the computer science share of students peaks with the class of 2026 and declines afterward, fastest at the top 25 programs. It also found the starting-salary premium over mechanical engineering narrowed from roughly $19,000 in 2016 to under $10,000 by 2024.
The hiring picture adds context. College Transitions’ analysis, using Census data for recent graduates ages 22–27, found unemployment between 2022 and 2024 rose from 2.3% to 7.9% in computer engineering, from 2.7% to 7.0% in information systems, and from 4.4% to 6.7% in computer science. Across all fields, it moved from 3.6% to 4.3%. At the same time, underemployment for computer science graduates barely moved: about 23.4%. The challenge appears to be getting hired, not necessarily finding degree-level work once hired.
Indeed Hiring Lab reported software development postings were 31.8% below the February 2020 baseline as of January 2026, while total U.S. postings were 4.4% above it. As Indeed’s Laura Ullrich put it: “AI didn’t cause the bust in hiring in the tech sector, but it might be preventing it from recovering at the same rate it would have.”
A thinner entry-level ladder does not prove that mid-career and late-career workers are unsafe. But it is a reason not to assume that seniority alone guarantees a decade of stability.
What These Numbers Do Not Prove
The CRR authors urge caution. Federal research-and-development cuts could disproportionately affect AI-exposed jobs and exaggerate the apparent AI effect. Conversely, rapid hiring by AI startups in exposed fields such as data science could understate future disruption.
The occupation-level predictions are model estimates, not measurements of what will happen to any one worker. Even after the increase, high-exposure jobs still had lower exit rates than low-exposure jobs, partly reflecting higher education, higher pay, and less physical work. Exposure is not destiny.
None of this predicts your specific job, employer, or future. It is a reason to plan, not a verdict.
Why Franchise Ownership May Be Worth Exploring
If the career you expected to carry you to retirement may not last as long as planned, waiting to be rehired by another employer is one option, but not the only one. Franchise ownership offers a different question: instead of auditioning for a role as AI reshapes the workplace, could you own and operate an enterprise?
Experience can be an asset. A prospective owner in their 50s may bring financial discipline, a professional network, vendor-management experience, hiring judgment, and familiarity with budgets and profit-and-loss statements. Lenders and franchisors assess buyers using their own criteria, so neither age nor experience guarantees approval. Still, decades of operational maturity can be relevant.
Your background can also suggest useful research directions. Accountants and finance professionals might explore bookkeeping, tax preparation, payroll, or business-support services. IT and operations professionals might investigate home services, property services, or commercial cleaning. Senior care may interest people who want to serve an older population that includes their own generation. Corporate managers could look into business-support franchises.
These are starting points for research, not a ranking of the best franchises to own. A franchise for sale is not automatically a good fit, and franchise opportunities differ in cost, workload, territory, support, and risk. A franchise consultant can help organize your search and explain how to buy a franchise, but independent due diligence remains essential.
How To Buy A Franchise: Due Diligence
Start with the Franchise Disclosure Document (FDD), reviewed by an independent franchise attorney and a qualified financial professional. Under the FTC Franchise Rule, you must receive the FDD at least 14 calendar days before signing a binding agreement or paying the franchisor or an affiliate.
Pay close attention to:
- Items 5, 6, and 7: Initial and ongoing fees, plus estimated investment.
- Item 19: Financial performance representations, if provided. Compare the disclosed basis and assumptions with your own plans.
- Item 20: Outlet history and contact information for current and former franchisees.
- Item 11: Technology requirements. Find out who pays for maintenance, updates, and mandatory upgrades; what data the franchisor or vendors can access; how that data may be used or transferred; and what happens if a platform is discontinued.
Speak with both current and former franchisees. Ask about actual costs, support, daily responsibilities, and technology changes, not just the sales presentation.
THERE IS NO GUARANTEED INCOME. Past results, where disclosed, do not guarantee future performance.
Do not casually liquidate retirement savings to fund a business. Ask a qualified financial professional and tax advisor to review the funding vehicle and its risks. Options such as Rollovers as Business Startups have specific rules; get independent advice before acting.
For more guidance, review the FTC’s Consumer’s Guide to Buying a Franchise and Franchise Rule Compliance Guide. If you are considering SBA financing, check the SBA Franchise Directory. Inclusion is for SBA loan eligibility purposes; it is not an SBA endorsement or a guarantee of success.
Explore Your Options Without Quitting Your Job
You do not have to choose a business, or leave your job, to start learning. A FranLift consultant can talk through your goals, budget, and preferred lifestyle, then help you explore franchise opportunities that may fit. Contact FranLift to begin the conversation.
FranLift’s services are free to buyers. Franchise companies pay FranLift through their franchise development or marketing budgets.
A wider horizon starts with a better-informed next step.
This article is for general informational purposes only and is not legal, financial, employment, or investment advice. Franchise investments involve risk. Consult qualified independent professionals before making decisions.
© 2026 FranLift. Launch Beyond Boundaries.
