On June 25, 2026, Apple raised prices on a range of products at once. The 13-inch MacBook Air went from $1,099 to $1,299, the entry MacBook Pro from $1,699 to $1,999, and the 11-inch iPad Air from $599 to $749; iPhone prices stayed put for now. Apple told the press that AI data center expansion had driven a surge in demand for memory and storage, and that component prices had never risen this much, this quickly.
News like this tends to trigger two reactions: buy now before prices rise again, or buy a high-end configuration once and for all for future AI features. Both treat the new price as the starting point.
But the price rise doesn’t change what you need. It only makes “upgrading now for future AI features” more expensive. So start your upgrade case from the work that’s stuck each week: if you can’t name what your current device is blocking, don’t buy this time.
First check whether your current device already supports it
Check one thing first: does your current device already support the AI features you want? According to Apple’s official support page, Apple Intelligence supports Macs and iPads with an M1 chip or later. Most Macs bought since late 2020 are already on the list. For many people, “upgrading for AI” fails at the first step.
As for “it’ll only get more expensive”: an analyst at the market research firm Counterpoint expects other PC and tablet makers may raise prices too as memory costs keep climbing. In other words, waiting may not bring a price drop. But that isn’t a reason to buy now either; it only shows that “waiting for a discount” isn’t a strategy in itself. Whether to wait should depend on whether your current device can still handle the work.
Find the bottlenecks that happen every week
Take a sheet of paper and log a week of work: when did your device make you wait or interrupt you?
Good reasons to upgrade: not enough memory, so your development environment or editing software keeps stalling; a battery that can’t last a working day, affecting work on the road; system updates about to end, affecting security. These happen every week, and a new device really does solve them.
Reasons to slow down on: “the new AI features will probably be more complete,” “I’ll likely need more on-device computing later,” “my coworkers all upgraded.” These may hold up, but turn them into a concrete task first: which piece of work becomes faster, less error-prone, or keeps others from waiting? If you can’t, write it down and don’t rush to spend.
Not hardware problems: too many tabs, disorganized files, too many heavy tools running at once. Move to a pricier computer, and the problem often moves with you.
Ask whether the AI task must run on the device
On-device AI usually pays off for privacy, offline use, low latency, or large volumes of repetitive processing. If your needs are organizing text, summarizing, translating, or drafting, cloud tools are usually enough, and there’s no need to buy extra memory for it.
On the other hand, the cloud isn’t free. Costs shift from a one-time hardware purchase to a monthly usage bill, and long-running tasks can burn more than expected; see Long AI Tasks Spend Most of Their Budget on Retries and Rereading Context. When comparing, look at both costs over the same period.
How a small team should split the purchase
This way of judging suits individuals and small teams. When a small team buys equipment, sort members into three groups: people whose current device already blocks delivery, people who may need an upgrade within six months, and people who only need to keep things running. Then have whoever owns the budget or delivery confirm which bottleneck each upgrade solves. Not everyone needs the same top configuration.
If you’re considering AI-focused computers on the Windows side, the same logic applies; see Before Buying a Windows AI PC, Check Whether Your Everyday Software Runs Natively on Arm.
AI handoff card
Apple raised its hardware prices, and I want to decide whether to upgrade now without being pushed by new prices or AI marketing.
The method comes from this article: https://boosterminiclass.com/en/posts/apple-ai-memory-price-upgrade-checklist/
Its view: the price rise doesn't change what I need; it only makes "upgrading now for future AI features" more expensive. Start the upgrade case from the work that's stuck each week; if I can't name what my current device is blocking, don't buy.
First ask me: the model and purchase year of my current device, what I mainly use it for, and when in the past week it made me wait or interrupted my work.
Then:
1. Sort my bottlenecks into three groups: worth upgrading for, needs to be turned into a concrete task first, and actually not a hardware problem;
2. Check whether my current device already supports the AI features I want; mark anything uncertain as "check the official support page," and don't guess;
3. Judge whether these AI tasks must run on the device or could use cloud tools, and remind me of cloud usage costs;
4. End with only one recommendation: buy now, wait, or change how I work first, and state the one thing to confirm before acting on it.
Don't recommend specific models or places to buy.
References
- TechCrunch: Apple raises Mac and iPad prices, spares iPhone for now — https://techcrunch.com/2026/06/25/apple-raises-mac-and-ipad-prices-spares-iphone-for-now/ (2026-06-25)
- 9to5Mac: Apple announces significant price increases for MacBooks, iPads, more — https://9to5mac.com/2026/06/25/apple-price-increases-mac-ipad-more/ (2026-06-25)
- Apple official support: How to get the next generation of Apple Intelligence — https://support.apple.com/en-us/121115 [accessed: 2026-10-11]
