MSP Pricing and Packaging Trends Shaping 2026 Margins

MSPs are moving away from flat per-device and a la carte billing toward tiered bundles that scale with a client's budget, folding new tools, especially AI ones, into existing contracts instead of billing them separately. That shift changes how you should price anything you resell under your own brand, particularly tools the market has not agreed how to charge for.

Why Are MSPs Moving Away From A La Carte Pricing?

Kaseya's guide to managed IT services pricing, built from its annual benchmark survey, found that a combination of per-user and per-device billing is now the single most common pricing model, used by 26 percent of MSPs, ahead of straight per-user billing at 21 percent, per-device billing alone at 13 percent, and formal tiered service bundles at only 10 percent. The breakdown looks like this:

The same survey found that among MSPs who bill per device, 28 percent charge between 50 and 100 dollars per device per month, the most common range in that model, and among MSPs who bill per user, 22 percent land in that identical 50-to-100-dollar band. Those numbers sit low next to what a well-packaged tier can command, which is part of why so many MSPs are moving away from a single-variable rate card toward bundles that can carry a higher blended price without asking a client to swallow a jump in the one number they already recognize.

The pattern is easy to read. Straight per-device billing keeps shrinking because it punishes you every time a client consolidates hardware or moves to thin clients and remote work. Blended and tiered models let you capture value from users, endpoints, and add-on services at the same time, which matters more as the services you sell get more complex. If you are still pricing everything you resell by device count alone, you are leaving margin on the table with every client that changes how its people work.

What Does This Mean for How You Handle Renewals?

Every pricing shift lands hardest at renewal, not at signing. A client who has been on a flat per-device rate for a long stretch will notice a jump to a bundled tier even if the new tier costs less once you add up everything it now includes. The safer path is not a blanket increase applied across the base. It is a side-by-side comparison, shown at renewal, of what the client was paying piecemeal against what the new tier now covers for a similar or only slightly higher total. That comparison does the selling for you, and it protects the relationship in a way a flat percentage increase on an invoice never does.

This matters even more once an AI tool enters the mix, because most clients have no established price anchor for it yet. You get to set that anchor. Set it too low as a standalone add-on and you train the client to expect AI features bundled in for free going forward. Set it inside a tier they already trust and already pay for, and the feature earns its price through association instead of a hard negotiation every time you want to raise it.

What Does Bundling Look Like for AI and Governance Tools?

Research from AvePoint and Omdia, based on a survey of 333 MSP executives across North America, Europe, and Asia-Pacific, found that 49 percent of MSPs want a complete platform integrated with their other core tools rather than a collection of point solutions. The same research found that 91 percent of respondents say integrating backup and disaster recovery delivers stronger data governance than offering those functions separately. That same logic applies to how you package any white-labeled AI tool of your own. Selling a single AI feature as a bolt-on invites a client to price-shop it against every other bolt-on on the market. Folding it into a tier the client already trusts and already pays for does not invite that comparison at all.

The same survey found that 51 percent of MSPs cite governance and compliance challenges, not technical limits, as the main obstacle to rolling AI out to their own customers. That is a packaging problem as much as a technology problem. A client does not need to understand the model behind an AI tool to buy it. They need to trust that it is already governed, monitored, and included in a plan they recognize.

How Should You Price the AI Tools You Resell?

Trade coverage backs this up in less quantified but still telling terms. ChannelE2E's August 2026 channel brief on MSP AI pricing describes an industry still working out whether an AI service is a one-time project or something a customer pays for every month, with vendors and MSPs equally unsettled on the answer. That uncertainty is an opening for a white-labeled reseller, not a problem: whoever settles on a clean per-seat or tiered price for an AI-driven service first captures the client relationship before the wider market standardizes around one answer.

The same AvePoint and Omdia research found that 94 percent of MSPs say they are committed to automating AI data readiness and compliance services, but only 43 percent have reached high maturity delivering those environments to customers. That gap between intent and delivery is exactly where a packaged, already-built tool beats a from-scratch build. Reselling a proven tool under your own brand, the model behind Actiforge's AI University for MSPs, lets you close that maturity gap without carrying the engineering cost yourself, while keeping the recurring revenue and the client relationship in your name.

Recurring Revenue Keeps Pulling Ahead

ScalePad's 2026 MSP Trends Report, based on a survey of more than 1,100 MSP professionals across North America, found that MSPs in the 41 to 60 percent recurring-revenue range make up the largest single segment at 34 percent, while their most common average revenue per user falls between 151 and 200 dollars per client per month. The same report found that 78 percent of MSPs reported an increase in recurring revenue over the past year, which tracks with the shift toward bundled and tiered pricing already covered here.

Higher average revenue per user and a larger recurring share are not separate wins you chase independently. They move together, and the products you choose to fold into a tier, rather than sell as an afterthought, are one of the few levers you control directly to push both numbers at once. That is the practical reason packaging deserves as much attention from you as the tools themselves.

A Hypothetical Look at Bundling Math

Consider a hypothetical MSP with 40 clients on a mid-tier managed services plan priced at 175 dollars per user per month. If that MSP adds a white-labeled AI tool as a 25-dollar-per-user line inside the existing tier instead of selling it as a standalone 40-dollar product, and only 60 percent of clients adopt it in year one, the bundled version still produces more new monthly recurring revenue than the standalone version, once you factor in the much lower close rate a brand-new, stand-alone line item typically gets from a busy client contact. The math holds up even in a rougher scenario: drop adoption to 40 percent of that same hypothetical base, and the bundled path still comes out ahead once you price in the higher cancellation rate a stand-alone line item tends to see at its first renewal. The favorable math shows up before you even count the retention benefit of one combined invoice instead of two separate ones to negotiate every year.

Where This Leaves Your Packaging Decisions

None of this means copying another MSP's tier names or price points wholesale. It means testing whether every tool you resell, including any new one you add, earns its keep folded into an existing tier rather than sold alone. A tool like Actiforge's Stack Builder exists for exactly that modeling work, letting you see the margin impact of a bundling decision before you roll it out to clients. When you are ready to see which white-labeled products are actually built to slot into a tier instead of compete against it, the Actiforge product catalog lays out what is available today.

Pricing is a lever you pull every renewal cycle, not only at onboarding, so it is worth revisiting these decisions on a fixed schedule rather than only when a client complains. See the full stack.