What factors could cause California's economy to overtake or fall behind other large economies in the next five years?

1. AI cash vs. concentrated exposure — a two-speed engine

Massive corporate capital spending on AI infrastructure is reshaping growth prospects: UCLA notes AI-related investment topped $405 billion in 2025 and is expected to rise in 2026, giving California outsized benefits because the state houses a disproportionate share of venture capital and high‑productivity tech firms ^{[1] [2]}. That concentration means California can leapfrog other large economies if AI demand translates to broad hiring, new business formation, and exportable services; conversely, the narrow sectoral gains could produce headline GDP growth without wide job creation, leaving the economy vulnerable if tech cycles reverse ^{[1] [5]}.

2. Labor-market weakness is the most immediate brake on upside

Multiple forecasts point to sluggish or negative employment trends in 2025: UCLA documents payroll job losses through much of 2025 and an unemployment rate that stayed above 5.0% for more than 19 months, and some models expect unemployment to inch higher before recovering in 2026–27 ^{[2] [3] [6]}. Weak job growth limits consumer spending diffusion and raises the political risk of policies (e.g., immigration enforcement or tariffs) that can further depress employment and consumption ^{[2] [3]}.

3. Housing, cost of living and population dynamics will decide talent and productivity

Housing costs—median home values more than double the U.S. median and rents roughly 50% higher—remain a structural headwind that deters worker inflows and raises business labor costs ^{[4] [7]}. Forecasts and policy notes show constrained building and slow permit issuance, so shortages can cap long‑run growth even if tech investment surges; slower population growth or politically driven migration trends would magnify downside risk ^{[4] [7]}.

4. Tariffs, trade friction and fiscal shocks create outsized risk

State and federal policy moves including tariffs and the record 43‑day federal shutdown in late 2025 are cited by forecasters as near‑term dampeners on GDP and inflation dynamics ^{[1] [8] [3]}. Tariff hikes also push inflation higher and complicate the Fed’s path, increasing the probability that higher interest rates will restrain housing and investment — problems that could leave California lagging other large economies should those economies avoid similar shocks ^{[8] [3]}.

5. Regional diversity: pockets of boom and bust

California is not a single economy. Coastal tech and aerospace clusters are expanding, while construction, leisure and some tradable‑goods sectors face headwinds; UCLA describes a “bifurcated” picture in which AI, aerospace and advanced manufacturing expand even as hospitality and government‑funded services struggle ^{[2] [9]}. That geographic and sectoral split raises the chance California’s aggregate GDP outperforms while large swaths of the workforce see flat wages or job losses — a political and social liability that can feed policy responses that alter the trajectory ^{[2] [9]}.

6. Scenario paths: what would make California overtake peers — or fall behind

Overtake scenario: sustained AI/CAPEX growth converts to durable non‑tech spillovers, immigration or retention of skilled workers, easing housing supply constraints, and no prolonged tariff or federal funding shocks — forecasts see California growing above trend in 2026 if those conditions hold ^{[1] [5] [10]}. Fall‑behind scenario: persistent employment recession into early 2026, higher inflation from tariffs, tighter credit and continuing housing shortages, all documented risks in UCLA and state forecasts ^{[5] [2] [8]}.

7. What forecasters disagree on — and why it matters

Economists agree on the big levers (AI investment, housing, jobs) but disagree on timing and strength of recovery. UCLA and some state forecasts expect a muddled early‑2026 with rebound later in 2026–27, while others (Comerica, regional updates) emphasize stronger 2026 growth led by AI and tourism rebounds ^{[2] [10] [11]}. These differences stem from alternative assumptions about tariffs, immigration, Fed policy and how quickly AI investment translates into broader demand ^{[1] [8] [5]}.

8. Bottom line for readers and policymakers

The next five years will be decided not by a single headline number but by how California converts concentrated AI investment into broad employment, eases structural housing constraints, and weathers policy shocks that raise costs. Forecasting models from UCLA, state budget offices and private analysts all note both the upside from innovation and concrete downsides from labor and housing frictions — the balance of those forces will determine whether California overtakes peers or falls behind ^{[2] [8] [4]}.