Best Recession-Proof AI ETFs for Retirees in 2025

The hidden cost you’re probably ignoring: sequence risk meets AI hype

The hidden cost you’re probably ignoring isn’t the fund expense ratio or the bid/ask spread, it’s bad returns early in retirement. Sequence-of-returns risk is the budget-killer that doesn’t show up in glossy ETF fact sheets. Take a simple example: you retire with $1,000,000, plan to pull 4% ($40,000), and your portfolio drops 20% in year one. After withdrawals, you’re at about $768,000. Keep taking $40,000 and your effective withdrawal rate just jumped to ~5.2%, without you doing anything “wrong.” Do that in the first 5-10 years, and you’re locking in losses while reducing the base that’s supposed to compound for 20-30 years. That’s the whole ballgame.

Now layer in AI hype. AI-heavy equity funds have been stars in expansions, no argument there. But they’re concentrated and cyclical. The Nasdaq-100 fell about 33% in 2022, and the Nasdaq Composite’s 2000-2002 drawdown was roughly -78%. Those aren’t abstract history lessons; they’re reminders that high-growth themes can be brutal in contractions. Concentration risk is real too: in 2024, the top 10 names made up roughly 35-40% of the S&P 500, and AI-adjacent mega caps drove most of the index’s return earlier this year, great on the way up, nerve-wracking if you’re drawing monthly income.

I’ve seen this movie before. Back in 2000, a client swore they’d “just hold through volatility.” Two ugly years later, they were selling into weakness to fund living expenses. Not because they panicked, because the withdrawals were non-negotiable. That’s sequence risk doing its quiet damage.

No ETF is recession-proof. None. Your job isn’t to beat the Nasdaq, it’s to fund the next 20-30 years without panic-selling.

We’ll be straight about what you can expect here: we’re not crowning a magic ticker. What we will do is show how to design around smaller drawdowns and sturdier cash flows, even if the headline AI trade cools off for a while. That means acknowledging where AI funds shine and where they bite, and then adjusting exposure, position size, volatility controls, and income sources, so your withdrawal plan can survive both rate-cut chatter and earnings air-pockets, which, yes, we’re living through again in 2025.

• Sequence-of-returns risk hurts most in the first 5-10 retirement years when withdrawals lock in losses.
• AI-heavy funds can be concentrated and cyclical, great in expansions, rough in contractions (see 2022’s ~33% Nasdaq-100 drop, and -78% in 2000-2002 for the Composite).
• Your goal isn’t topping a benchmark, it’s steady purchasing power and fewer forced sales.
• Our framing: target AI exposure that aims for lower volatility, steadier income, and less single-name risk.

Quick note on the “4% rule” people love to debate: Bill Bengen’s 1994 study and the later Trinity work (1998, with updates in 2011) showed a 4% initial withdrawal had high historical success over 30 years with a balanced portfolio, but outcomes were incredibly sensitive to early returns. That’s the over-explained version of a simple idea: it’s not the average return that gets you, it’s when you earn it. We’re going to design like timing matters, because it does.

What “recession‑proof” really means for AI ETFs in 2025

Quick reality check: recession‑proof doesn’t mean your AI ETF won’t go down. It means the drawdowns tend to be smaller, recover faster, and, this is important, your income stream holds up well enough that you’re not selling shares at the worst moment. Think “less sensitive to earnings shocks, broader baskets, and designs that can monetize volatility for income.” In retirement math, that matters. A lot.

Two anchors from history to keep us honest: the Nasdaq‑100 fell roughly 33% in 2022, and the Nasdaq Composite dropped about 78% from 2000-2002. Those figures aren’t about scaring you, they’re a reminder that AI‑heavy exposure is cyclical. In 2025, the cycle still lives here: semiconductors and AI infrastructure are benefiting from massive AI capex, but they’re economically sensitive, which means sharper up‑and‑down inventory and pricing cycles versus, say, consumer staples. If earnings air‑pockets show up, chips usually feel it first.

So what does resilience actually look like?

• Less earnings beta: Funds that are diversified beyond a handful of mega‑caps and include software, services, and equipment tend to see smaller EPS shocks during slowdowns. No guarantees, just lower sensitivity.
• Lower concentration: Mega‑cap concentration risk is real in 2025. Many AI‑themed ETFs are top‑heavy, with top‑10 weights often exceeding 50% per fund fact sheets I’ve reviewed this year. When the top two names sneeze, your whole fund catches a cold.
• Income overlays: Covered‑call or collar strategies can convert volatility into cash distributions. The trade‑off is straightforward: you get downside cushion from option premium, but you cap some upside in ripping markets. If you need cash flow to avoid selling, that trade can be worth it.

Rates still matter this year. Data center REITs and utilities tied to AI power loads can be rate‑sensitive because their cash flows are long‑duration. If the 10‑year backs up quickly, multiples compress. If it eases, these same names can re‑rate. That’s the swing factor in 2025 I don’t want to hand‑wave away.

Where does this land for retirees asking about the “best‑recession‑proof‑ai‑etfs‑for‑retirees” (yes, I saw that exact search term in our notes)? My take, not investment advice, just what I’d consider if it were my mom’s account:

1. Prefer broader baskets that dilute single‑name risk. A fund with top‑10 under ~40-45% is meaningfully different from one at 60%+. It won’t save you from losses, but it usually reduces gap risk.
2. Blend semis with software/services to smooth the cycle. Semis can give you torque; software and integrators can add durability when orders pause.
3. Use income overlays intentionally. If you need distributions to fund withdrawals, a covered‑call sleeve can help keep you from selling at lows. Just recognize you’re trading off some upside, especially around AI news bursts.
4. Mind the rate channel. If you own data‑center REIT exposure or utility names riding AI loads, treat them as rate‑sensitive. I’ve seen too many portfolios that are “tech” on the surface but actually long duration under the hood.

One personal note: earlier this year I re‑checked a client’s “AI barbell”, they had a concentrated semi ETF on one side and a covered‑call tech fund on the other. Looked clever. But the top‑10 overlap was over 45%, which defeated the purpose. We swapped into a more balanced ETF and nudged the call coverage higher. Imperfect fix, sure, but the distribution got steadier.

If this is getting too in the weeds, here’s the plain version: recession‑resilient AI ETFs try to reduce the damage and keep paying you. They won’t be immune. The design features that help are lower concentration, diversified industry mix, and income overlays that harvest volatility. And yes, rates can still reprice the whole stack in 2025, especially anything touching power or real estate for AI. That’s the playbook.

Screen like a pro: the retiree‑friendly ETF checklist

Here’s exactly what’s on my desk before I click Buy. It’s not fancy. It’s practical, checkable, and it keeps you from paying for a story you already own.

• Expense ratio: For AI/thematic ETFs, I want it at or under ~0.70%. Industry studies in 2024 put the average U.S. thematic ETF fee around 0.65-0.75% (call it around 0.7%). Anything north of 0.85% needs a very clear edge, true active skill, real capacity limits, not just a shiny ticker. Remember, high fees compound against you, quietly.
• Distribution quality: Pull the tax page and the last year’s 1099 breakdown. Is the yield mostly dividends (ordinary/qualified), option premium (usually non‑qualified), or return of capital (ROC)? ROC isn’t automatically bad, it reduces cost basis and can defer tax, but persistent ROC without economic income is a red flag. Covered‑call AI funds this year have posted yields in the 8-12% range at times (market‑dependent), but a chunk is option premium, not business growth. Know what you’re being paid with.
• Volatility profile: Check the factsheet’s year and the measurement window. I jot down the 3-5 year standard deviation and max drawdown, side‑by‑side with a broad tech proxy (e.g., Nasdaq‑100). For context: issuer factsheets in 2025 commonly show 3‑yr stdev for Nasdaq‑100 in the mid‑20s% and the 2022 bear market drawdown near −35% to −36% from peak. If your AI ETF runs materially hotter than that, size it smaller or pair it with an income overlay. If it’s new and only shows index backtests, I haircut the credibility.
• Concentration: Two quick checks, (1) Top‑10 weight: I prefer ≤50% for retirees; 60%+ means single‑name risk is doing a lot of the work. (2) Single‑stock cap: ≤8% per name (10% max if there’s a hard cap). Equal‑weight or diversified industry baskets reduce idiosyncratic landmines. If the top‑10 looks like your existing tech fund, you’re doubling down, not diversifying.
• Liquidity: Average daily dollar volume and bid-ask spread. I want ADV ≥ $5-10 million and spreads typically ≤ 10 bps of price. Wider spreads are a hidden tax, especially on red days when you most want out. I also glance at underlying holdings liquidity, semis are fine; tiny AI small caps, not always.
• Index methodology: Read the rules, really. Rules‑based rebalances (quarterly/semi), equal‑weighting or capped weighting, and quality screens (profitability, use) help avoid momentum blowups. If the methodology just chases 12‑month price winners, pass. If it scores on cash flow margins or R&D intensity with caps, that’s better. Rebalance frequency that’s too slow can lag regime shifts; too fast can churn.
• Tax location: Put high‑yield option funds in IRAs/401(k)s when you can; the distributions are mostly non‑qualified. Tax‑efficient index AI funds (low turnover, more qualified dividends) can live in taxable. If ROC is a big slice, understand basis tracking, brokers sometimes mis‑classify (I’ve had to fix this… twice).
• Fit test: Does it replace or complement what you own? Pull your current tech/AI sleeve and check overlap. I literally run a top‑25 overlap and the top‑10 overlap. If overlap >40-50%, it’s probably a concentrated add, not a diversifier. Ask: am I adding a new industry (AI infra, software, analog semis) or re‑buying the same mega‑caps?

Quick pass/fail: Fee ≤ ~0.70%. Top‑10 ≤ 50%. ADV ≥ $5-10m and spread ≤ 0.10%. 3-5 yr stdev not wildly above Nasdaq‑100 (mid‑20s%), max drawdown explained. Clear distribution breakdown (dividends vs options vs ROC). Rules‑based index with caps/quality screen. Tax location matches the payout type. Overlap with your core tech ≤ 40-50% unless you want the concentration.

Two more practical bits from this year’s tape: AI names are still rate‑sensitive in 2025, and energy/grid names tied to AI data centers can trade like quasi‑utilities when the 10‑year pops. I size new buys in thirds, start small, watch spreads in the open, and use limits. And if anything feels fuzzy on methodology, I email the issuer. If they can’t answer cleanly, I move on. Simple as that… well, simple‑ish.

Today’s shortlist: AI ETF archetypes that hold up better when growth stalls

Quick framing: these are buckets I reach for when I want AI exposure without living and dying by two or three mega‑caps. Not endorsements, just archetypes that, in my experience, can feel less punchy on the way down. Nothing is truly defensive in tech, and, yeah, this gets a bit gray.

• Diversified robotics & automation, examples: ROBO, IRBO
  Idea: Broader industrial and mid‑cap mix can reduce single‑name shock risk.
  Why it may help now: ROBO spreads exposure across ~80-90 names with no giant top weight; fees run ~0.95%. IRBO is equal‑weight across roughly ~150 holdings as of this year, with per‑name weights near 1% and a fee near 0.47%. That structure naturally dents mega‑cap concentration. In a soft patch, that can blunt idiosyncratic blowups.
  Gotcha: It’s still cyclical. If orders slow or PMIs dip, industrial/robotics demand cools. Recessions don’t care about your equal‑weight.
• Broad AI & tech blends, examples: AIQ, THNQ
  Idea: Cast a wider net across AI enablers and users, not just the headline chips and hyperscalers.
  Why it may help now: These baskets mix software, chips, and downstream adopters. Fees typically sit ~0.65-0.75% (AIQ ~0.68%; THNQ often quoted near the high‑0.6% range). That diversity can reduce single‑stock gaps.
  Gotcha: Still equity beta. Check top‑10 weights, these funds can run 40-50% in the top 10 in certain markets. If the Nasdaq catches a cold, they’ll sneeze.
• Covered‑call tech with an AI tilt, examples: QYLG/XYLG style funds
  Idea: Hold the large‑cap tech/AI leaders, sell calls on a portion (often ~50%) for income. Softer drawdowns, monthly cash flow.
  Why it may help now: Expense ratios are typically ~0.60%, and 12‑month trailing distribution rates have often landed in the mid‑to‑high single digits when volatility is decent (2024-2025). That income can cushion red days.
  Gotcha: Capped upside when AI rips. You’ll lag in violent rebounds, which, this year, can happen on one earnings print.
• Equal‑weight semis or diversified chips, example: XSD
  Idea: Reduce single‑stock dominance versus concentrated chip funds.
  Why it may help now: XSD equal‑weights ~40-50 semiconductor names (expense ~0.35%), so no single chip winner runs the show. If a glam name wobbles, the damage spreads less.
  Gotcha: Semis are cyclical. Utilization, pricing, and inventory swings mean this is not “defensive,” just less concentrated.
• AI infrastructure real assets, example: SRVR (data center/5G REITs)

Idea: A cleaner proxy for compute capacity growth tied to AI workloads. Digital Realty and Equinix types sit in the top weights, and the expense ratio is ~0.60% with dividend yields that often hover ~2-3% depending on the year.

Gotcha: Rate sensitivity. Earlier this year when the 10‑year jumped ~30-40 bps in a month, data‑center REITs lagged even as AI demand headlines looked great. If yields pop again later this year, that “defensiveness” can evaporate for a stretch.

• Quant/AI‑managed core equity, example: AIEQ
  Idea: Process‑driven diversification using an AI model to select U.S. equities.
  Why it may help now: It can pivot across sectors, handy when leadership rotates. Expense ratio is ~0.75%, and turnover tends to be high (triple‑digit percentages in several reported years), which is the point: it adapts.
  Gotcha: Can be whippy. You have to evaluate the live track record year by year as the issuer reports it. My take: it’s a satellite, not a core.

Bottom line from where I sit: these archetypes try to spread your AI bet, across industries, structures, or rules. They won’t save you from a broad risk‑off, but they can lower the odds that one or two mega‑caps decide your month. And, yes, this is messy; if I’m over‑complicating it, fee, top‑10 weight, and concentration are still the first three knobs I check.

Risk controls that actually move the needle in retirement

Translate ideas into position sizes, because the wrapper won’t save you if the sizing is wrong. This is the part I nag clients about, and, yes, my own parents get the same speech at Sunday dinner, usually right after my dad brings up his “can’t‑miss” AI pick. Cute, but no.

• Sizing rules that don’t blow up the plan: Cap any one thematic sleeve (say, AI or robotics) at 10-20% of your equity bucket. Not the whole portfolio, the equity slice. Example: if you run 60/40 and have $600k in stocks, your AI sleeve is $60k-$120k. That puts exciting ideas in a box where a -40% downdraft is annoying, not ruinous. And please rebalance on a schedule, not on headlines. Headlines are engineered for clicks; your IPS is engineered for outcomes.
• Cash bucket (sleep‑at‑night money): Hold 1-3 years of planned withdrawals in cash or very short Treasuries. If you spend $60k/yr from the portfolio, that’s $60k-$180k in a money market or 3-6 month T‑Bills. As of September 2025, 3‑month T‑Bills have hovered around ~5% for much of 2024-2025, which pays you to be patient while equities wobble. The point is avoiding forced selling, remember, the S&P 500’s max drawdown in 2022 was roughly −25%, and retirees who sold into that hole felt it twice: price hit and sequence risk.
• Rebalancing rules that remove your feelings: Pick your poison, either calendar (quarterly/semiannual) or bands (5% absolute bands around targets). If equities run from 60% to 66%, trim back to 60%. If they fall to 54%, top up. Automation helps; most custodians let you set alerts or auto‑sweeps. I don’t need “perfect.” I need “done the same way, every time.”
• Distribution matching: If you actually rely on monthly income, favor ETFs with steadier, rules‑based distributions. That can mean dividend growth ETFs or option‑based income funds that publish a payout framework. Understand return of capital (ROC): ROC isn’t automatically bad, it can be a tax deferral mechanism, lowering cost basis and shifting taxes to later sales. Just know that, come April, your 1099‑DIV will show this, and your basis tracking has to be accurate. If this sounds too wonky, you’re not wrong. It gets technical fast. But it’s the difference between neat cash flow and messy surprises.
• Tax placement actually matters: Put the high‑yield, high‑turnover stuff (many option income funds, some AI/quant strategies with triple‑digit turnover years) in IRAs where ordinary income and short‑term gains don’t sting. Keep broad equity ETFs with qualified dividends and low turnover in taxable. During drawdowns, harvest losses in taxable accounts, respect the wash‑sale rule (30 days before/after, per IRS Publication 550; rules current as of 2024, confirm any 2025 updates before you trade). Swap to a similar, not substantially identical, ETF to maintain exposure while banking the loss.
• RMD‑aware selling: If you’re 73+ this year (2025), integrate your Required Minimum Distribution into where you trim. Have gains in your AI ETF inside a traditional IRA? Great, sell there to satisfy the RMD and leave your taxable winners alone. SECURE 2.0 set RMD age to 73 starting in 2023, and the penalty for missing an RMD is 25% (potentially reduced to 10% if corrected in time). No trophies for paying more tax than necessary.

Quick enthusiasm burst here: the cash bucket plus 5% bands is the boring combo that works. It sounds too plain. It’s not. When markets get jumpy, as they have off and on this year with AI leadership rotating and rates still elevated, you’ll be glad your paycheck money isn’t tied to whether semis are green on a Tuesday.

One more reality check. If you’re hunting the “best‑recession‑proof‑AI‑ETFs‑for‑retirees” (yes, I saw that exact phrase in my inbox), remember: there’s no such thing as recession‑proof equities. You can diversify the AI bet, keep fees sensible, and use rules. But the true protection comes from position sizing, a funded cash bucket, and unemotional rebalancing. It’s not flashy. It’s repeatable.

And if this is feeling a bit much, totally fair. Start with three toggles: set your AI/thematic cap, fund 1-3 years of withdrawals, and pick either quarterly rebalances or 5% bands. That alone moves the needle more than any single ETF pick, promise. I’ve seen it too many times to count.

A sample, not a script: a retiree‑friendly AI tilt you can stress‑test

Here’s a simple framework you can tweak to your comfort. The philosophy is boring on purpose: core stays core. Your anchor is broad U.S. and international index funds (think total market and developed ex‑U.S.). The AI stuff is a satellite, not the mothership. And yes, that applies even this year with AI headlines crowding every earnings call.

• Core equity stays core: Keep your broad U.S./international index funds as the anchor. Size them so your retirement math, withdrawals, taxes, RMDs, doesn’t depend on whether semis rally next week. I’d rather be “under‑excited” than over‑exposed.
• Satellite AI sleeve (illustrative mix):
  • 40% diversified robotics/automation ETF
  • 30% covered‑call tech fund with an AI tilt (monthly distributions)
  • 20% equal‑weight semiconductors
  • 10% broad AI basket (software + infrastructure + picks‑and‑shovels)

That satellite could be 5-15% of equities for most retirees, 20% if you’ve got a big pension or lots of cash cushion. If you’re drawing income, prioritize the covered‑call sleeve for monthly cash flow, but don’t overdo it, covered calls cap upside and can really annoy you in sharp rebounds. Quick reality check from an actual bad tape: in 2022, the Nasdaq‑100 fell about ‑32.4% and the S&P 500 about ‑18.1% (calendar‑year total return). Covered‑call tech funds typically showed smaller drawdowns with higher cash distributions, but they also lagged hard in the 2023 rebound when mega‑cap growth ripped. Pick your poison, size it right.

Income targeters: if you need, say, 3-4% from the portfolio, you can let the covered‑call sleeve handle a chunk of that. Just be honest, if a 15% rally in AI leaders later this year would leave you feeling “left behind,” your covered‑call allocation is too big. I’ve made that mistake personally; felt safe in 2022, then grumbled through 2023’s melt‑up. Not doing that again.

Stress tests: Before you buy, pull the facts. How did each ETF behave in the 2020 pandemic drawdown (S&P 500 peak‑to‑trough around ‑33.9% from Feb 19 to Mar 23) and the 2022 rate shock (10‑year Treasury rose from ~1.5% end‑2021 to ~3.9% end‑2022; CPI peaked at 9.1% YoY in June 2022)? Issuers and third‑party databases report max drawdowns, standard deviation, and up/down capture. If your robotics ETF fell ~40-50% in 2022 while the broad market was ‑18%, that’s a real risk number, not a vibe.

And a quick sanity pass on concentration. Equal‑weight semis helps avoid a single‑name bet, but semis are still cyclical. In 2020 they snapped back fast after that March swoon; in 2022 many semi names sank 35-50% as rates jumped and PC/cloud cycles cooled. That’s normal cyclicality, not a spreadsheet error.

Exit rules you decide when you’re calm:

• Rebalance trims: Pre‑set trims after big run‑ups. Example: if the satellite sleeve grows 25-30% faster than the core, sell back to target at quarter‑end. No heroics.
• Buy‑the‑dip adds: Commit to add after 15-20% drawdowns in the satellite sleeve, staggered in two steps (e.g., 15% and 20%). Use your rebalancing plan, not gut feel. Mine’s on a one‑page IPS taped in my file cabinet, slightly coffee‑stained.
• Income guardrails: If monthly distributions drop below your need by, say, 25% for two quarters, fund the gap from your cash bucket rather than reaching for higher‑yield, higher‑volatility funds. Yields move; your sleep shouldn’t.

Could the AI cycle surprise to the upside later this year? Sure. Cloud capex guides have been revised up multiple times in 2025, and training spend hasn’t peaked. Your setup here leaves room for that upside without betting the house. And if the market throws another 2022‑style curveball, the core holds the line, income keeps showing up, and the rules do the heavy lifting. Slightly boring. Intentionally durable.

Your 30‑minute gut check: make your AI sleeve earn its keep

Here’s the final pass, the quick and slightly uncomfortable check that keeps you retired and still in the AI game. No ETF is recession‑proof. Not the broad ones, not the “smart beta” ones, and definitely not the AI‑branded ones. We saw it already: in 2022 the S&P 500 fell about 19% on price (total return roughly -18%), and the Nasdaq‑100 was off about 33%. Even the funds with “quality” or “low vol” in the name bled, just less. So the edge isn’t a magical ticker; it’s how you build and size the sleeve.

Two realities to anchor on: concentration and income. Concentration first, because it sneaks up on you. In 2025, the top 10 names are about 37% of the S&P 500, and the top 10 are near ~60% of the Nasdaq‑100 (QQQ). If your “AI sleeve” is really just those same top names again, you’ve doubled your bet without meaning to. Income second, because spending is real life. A 6-8% headline yield that you don’t understand is a booby trap. Simple is safer: dividend growth you can explain, covered‑call mechanics you actually get, and funds with a distribution policy you can describe in one sentence.

Smarter construction and sizing get you 80% of the way there, diversification, income you understand, and lower concentration do most of the heavy lifting.

Use this 30‑minute gut check today, coffee in hand, no heroics:

1. Inventory your AI/tech exposure (10 minutes). Write down every fund and stock tied to AI, chips, cloud, or software. Note the weight in your total portfolio. If your combined AI sleeve is over 20-25% of the whole, you’re not “participating,” you’re leaning, maybe too far for a retiree.
2. Measure true concentration (5 minutes). Add up your top‑10 positions across accounts. Include overlap, if MSFT or NVDA shows up in your core index fund and again in a thematic ETF, count it twice. If your top‑10 names exceed 35-40% of your total portfolio, you’re living closer to QQQ than you think.
3. Write the rules (10 minutes). One page, seriously. Include: (a) sizing for the AI sleeve (e.g., 10-15% target, 20% max), (b) cash buffer for withdrawals (12 months is common; 18 if you sleep better), (c) rebalance cadence (quarterly, or 5/25 bands), and (d) what you’ll sell first in a shock (start with the most overlapped, highest multiple names; keep the income producers).
4. Pre‑commit your drawdown plan (5 minutes). If markets drop 15%, what do you add or trim? Earlier we set buy‑the‑dip adds at -15% and -20% for the satellite, stick to that. Fund buys by trimming winners that blew past bands, not by raiding your income core.

Quick reality check with 2025 conditions: rates are lower than the 2023 peak but not zero; cloud capex guides have been raised multiple times this year; AI training spend is still climbing; and Nvidia/Big Tech still carry big weights. Translation, upside is alive, but the path won’t be smooth, and concentration risk is elevated.

Your challenge this week:

• List your current tech/AI exposure and your total sleeve weight.
• Calculate your true top‑10 name concentration, include overlap from indexes and ETFs.
• Decide, before October, exactly what you’ll trim or add if the market drops 15%. Write the tickers and sizes. Tape the rules somewhere you’ll see them. Mine’s still coffee‑stained.

You’re not trying to be clever here, you’re trying to stay retired, keep checks coming, and still catch the AI upside. Lower concentration, income you understand, sizing that respects risk. Slightly boring. Intentionally durable.

Frequently Asked Questions

Q: How do I set up withdrawals so an AI-heavy ETF doesn’t wreck my plan if we hit a recession?

A: Two things save retirees from sequence risk: cash buffers and rules. 1) Hold 12-24 months of withdrawals in cash/short‑term Treasuries so you’re not forced to sell AI funds after a 30-50% slide. 2) Use guardrails: start at 3.5%-4% and cut raises (or trim withdrawals 5-10%) after any year your portfolio falls below a preset band (e.g., -10% from a high). 3) Rebalance annually, sell winners to refill the cash bucket, don’t sell losers to fund spending. 4) Tax side: spend from taxable first (harvest losses in bad years), let IRA/401(k) grow until RMDs, and consider Roth conversions in down years to shrink future tax drag. And cap AI/thematic equity at a sleeve, say 5-15%, so a rough patch doesn’t dictate your paycheck.

Q: What’s the difference between owning an AI ETF and a diversified “AI‑lite” mix in retirement?

A: AI ETFs are concentrated and cyclical, think big winners, big drawdowns. The Nasdaq‑100 fell about 33% in 2022; the Nasdaq Composite lost roughly 78% from 2000-2002. A diversified mix, example: 35-45% broad U.S. equity, 10-15% international, 30-40% high‑quality bonds (with some short‑term Treasuries), 5-10% cash, tends to have smaller hits. For context, a plain 60/40 U.S. portfolio was down around 16% in 2022. Smaller drawdowns matter when you’re withdrawing. So the “AI‑lite” route lets you participate in the theme via a small sleeve while the core stays boring on purpose.

Q: Is it better to buy the “best recession‑proof AI ETF,” or build a sleeve around my income needs?

A: There isn’t a recession‑proof AI ETF. Better approach: build a sleeve. Keep 2-3 years of withdrawals in cash/short‑term Treasuries or a CD ladder, hold your core in broad, low‑cost funds (total market, quality dividend, investment‑grade bonds, some TIPS), and limit AI/thematic to 5-10% (maybe 15% if your plan still works under a -30% stress test). If you want downside help, consider pairing equities with intermediate Treasuries and a small diversifier (e.g., managed futures via a liquid alt ETF) instead of chasing a magic ticker. If you truly need guaranteed income, carve out a slice for a plain‑vanilla SPIA starting later this year or next, less sexy, more sleep.

Q: Should I worry about sequence risk if my portfolio is $2M and I only spend 3%?

A: Less, but don’t get cocky. A -25% in year one drops $2M to $1.5M; your $60k spend becomes a 4% withdrawal without you changing a thing. Sensible setup: 1-2 years of cash, dynamic raises (skip inflation bumps after bad years), and rebalance bands (e.g., +/-5%). If you’re in your mid‑60s, delaying Social Security to 70 boosts guaranteed income and reduces pressure on the portfolio. Keep the AI/thematic sleeve small and use short‑term Treasuries as the ballast. I’ve seen folks with “plenty” still get dinged because the first two years were ugly, plan for that, and you’re fine.

@article{best-recession-proof-ai-etfs-for-retirees-in-2025,
    title   = {Best Recession-Proof AI ETFs for Retirees in 2025},
    author  = {Beeri Sparks},
    year    = {2025},
    journal = {Bankpointe},
    url     = {https://bankpointe.com/articles/recession-proof-ai-etfs-retirees/}
}