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The cost equation · 2026-2032

As AI collapses digital IT costs, physical becomes the budget.

A research-grounded view of how onsite IT support — the one layer AI cannot reach — becomes both the most expensive and the slowest service in enterprise IT between now and 2032. Modelled for Fortune 500 enterprises. Cited from Gartner, MetricNet, Reworked, and IDC.

Today · 2026

Physical IT tickets cost 3× more than digital ones.

Per MetricNet's 2024 IT Service Desk Benchmarks, the average cost to resolve a Tier 1 digital ticket — password reset, software issue, generic service desk query — is around $22. The cost to resolve an onsite, desktop, or field-support ticket — the broken laptop, the new-starter kit-out, the peripheral exchange — is around $70. The physical ticket costs roughly three times the digital one.

That gap is the unsurprising one. Onsite resolution carries engineer time, dispatch overhead, travel, parts logistics, and coordination cost. None of that is news to anyone running an IT services budget. The 3× ratio is the floor most CIOs and CFOs have known about for a decade.

The surprising part is what the ratio does next.

Interactive · Drag to explore

As AI matures, the cost gap compounds.

Drag the slider to advance the year. The physical cost-per-ticket stays the same — AI cannot reach through a screen. The digital cost shrinks. The gap widens from 3× today to 14×+ by 2032.

Showing
Today · 2026
The cost gap
3.2×
physical vs digital ticket
Physical ticket
$70
Digital ticket
$22
2026 2027 2028 2029 2030 2031 2032
Today's cost gap, before AI compounds. The 3× ratio is the floor — it widens from here as Tier 1 automation matures across the service desk.
From unit cost to budget share

Unit costs are the symptom. Budget share is what your CFO sees.

The cost-per-ticket ratio is the operational view — useful for service-delivery managers, MSPs and engineering leadership. It explains why the gap matters. But the budget review happens one layer above. What the CFO sees on the spreadsheet is the line item: "Onsite IT support." And what makes that line item the standout problem is not its absolute size, but its share of operational IT cost — and the trajectory of that share over time.

The chart below models that trajectory for a representative Fortune 500 ICP.

The trajectory

Onsite IT support: the line item that keeps rising.

Modelled for a representative Velocity ICP — Fortune 500 enterprise, $10B revenue, 30,000 employees, 25+ sites, ServiceNow-standardised. The line below holds onsite cost flat in absolute terms. The share trajectory is dominated entirely by what happens around it.

Onsite IT support as a share of operational IT budget, 2026-2032

FORTUNE 500 ICP · $180M OPERATIONAL IT COST BASELINE · BLENDED 22% NON-ONSITE AI REDUCTION BY 2029

0% 4% 8% 12% 16% 2026 2027 2028 2029 2030 2031 2032 8.3% 9.9% 13.4% 2029 INFLECTION Gartner: 70% of enterprises deploy agentic AI in I&O by 2029 (up from <5%)
Today · 2026
8.3%
of operational IT budget consumed by onsite support — the unremarkable baseline.
By 2029
9.9%
as agentic AI cuts ~22% from the rest of the IT operational stack.
By 2032
13.4%
a 61% relative increase — onsite becomes a top-four IT operational line item.

Onsite isn't getting more expensive. Everything else is getting cheaper. Onsite just becomes a bigger slice of what's left.

For an MSP or in-house IT operation, the trajectory makes onsite the most visible cost-to-serve problem on the CFO's spreadsheet from 2027 onwards. The transition from "unremarkable" to "scrutinised" happens during the 2027-2029 window — exactly when agentic AI delivers its first cost reductions in adjacent categories. Boards will compare the two trajectories.

What's driving the squeeze

Three Gartner forecasts compound across the rest of the stack.

The trajectory above isn't a projection on its own. It's the arithmetic of three independent Gartner forecasts, each touching a different layer of IT operations, all bypassing onsite physical support.

80%
of common service issues will be agentic-AI-resolved by 2029
Cutting service operations cost by 30% on Gartner's central estimate. Tier 1 service desk, ITSM workflow automation, customer-service triage — all collapsing toward near-zero unit cost.
Gartner · March 2025
70%
of enterprises will deploy agentic AI in IT infrastructure operations by 2029
Up from less than 5% in 2025. Network operations, infrastructure management, AIOps, automated remediation — the back-of-house stack now run by agents, not engineers.
Gartner Predicts 2026 · December 2025
40%
of enterprise applications integrated with task-specific AI agents by end of 2026
Up from less than 5% in 2025. ServiceNow Now Assist, Microsoft Copilot for Service, Salesforce Agentforce — the AI layer arriving inside the apps your IT team already runs.
Gartner · August 2025
!

A caveat worth naming: Gartner itself (June 2025) forecasts that more than 40% of agentic AI projects will be cancelled by the end of 2027 due to escalating costs, unclear business value, and inadequate risk controls. The technology is real — but procurement discipline matters. The trajectory above assumes realised savings, not vendor claims. Even at a 50% adoption haircut, the share trajectory still bends sharply upward.

The speed problem

And it's not just expensive. It's slow.

Every employee in your business experiences instant gratification in their personal life — same-day delivery, on-demand food, AI answers in seconds. Then they walk into work and wait 2.9 days for a replacement laptop. As AI accelerates every other service inside enterprise IT, slow physical IT becomes the standout bad experience inside the modern workplace — and the line item IT leaders increasingly get fired for delivering.

Average resolution time
2.9d
Average time to resolve a P4 hardware request — sitting right at the SLA floor because that's where the SLA is set.
Standard enterprise SLA
3-5d
Industry-standard P4 (low-priority) resolution window — covering new-starter kit-out, peripheral requests, and replacement devices.
Worst-case observed
20d
The slowest P4 resolution time encountered across Velocity's customer base before Smart Collect® automation.
The expectations gap

Your employees ordered groceries in 30 minutes this morning.

Everyone in the building lives in a world calibrated to instant. The Spotify queue advances in milliseconds. The Amazon Prime parcel arrives the next day. ChatGPT answers questions in two seconds. Microsoft's State of Global Customer Service research consistently finds that 55% of customers expect a higher level of customer service year-on-year — and "customer" here means anyone receiving a service, including the employee receiving the IT one.

Then employees raise an IT ticket for a broken laptop or a new peripheral, and wait. Two days. Five days. Sometimes twenty. They don't know what a P4 SLA is. They don't care that the engineer is overworked. They know that everything else in their life is instant, and IT is the slowest service they touch. This is precisely why the industry is now moving away from SLAs as the primary IT metric and toward Experience Level Agreements (XLAs) — which measure perceived employee experience, not just compliance against a clock the employee never agreed to.

In their personal life:
ChatGPT answer 2 sec
Uber arrival 5 min
DoorDash delivery 30 min
Streaming a film instant
Amazon Prime parcel 1 day
At work, from IT in 2026:
Service desk auto-acknowledge 5 sec
Password reset (digital) 2 min
Software install request ~2 hours
New peripheral request 2.9 days
Replacement laptop 2.9 days
The productivity cost

Every day of waiting costs the business measurable productivity.

The productivity cost is measurable and consistent across the research. StrongDM's 2025 employee onboarding survey found that 43% of new starters were still waiting for basic workstation tools after their first week, and 18% were still missing essential tools after two months — every wait day is a day of paid salary delivering reduced productivity. InsightGlobal's workforce research separately finds that 78% of employees say they are missing at least one of the tools they need to do their jobs effectively. And on the new-starter end specifically, industry-consensus benchmarks (SHRM, Aberdeen) place time-to-full-productivity at 6 to 8 months — a window that begins on Day 1, with the laptop handover.

The economic damage is direct. The reputational damage is bigger. Every wait shortens the half-life of "IT is a partner" and lengthens the half-life of "IT is what's slowing me down" — and once an IT function lives in the second category, it doesn't move back.

Your CFO sees the cost. Your employees feel the speed. The IT leader who can fix both wins the seat at the table. The one who can't, loses it.

What Smart Collect® changes

The line doesn't have to keep rising. The wait doesn't have to keep stretching.

Smart Collect® automates the physical handover itself — the device exchange, the peripheral swap, the new-starter kit-out, the broken-laptop return. The ticket closes inside ServiceNow without dispatching an engineer. The cost-per-ticket drops toward digital parity. The 2.9-day wait drops to minutes. Both lines bend.

BEFORE · Today's onsite ticket
$70
Resolution time2.9 days average
The engineer dispatch, the truck-roll, the wait. The line item that won't move — and the experience employees rate worst.
WITH SMART COLLECT®
~$20
Resolution timeMinutes · 24/7 self-service
Automated handover. ServiceNow-native workflow. No engineer dispatch. The employee collects from a locker. The ticket closes itself.
PRE-AI

Smart Collect® has already delivered 500%+ throughput uplift in pharma, 60% onsite ticket reduction in nuclear energy, and 35% engineer travel reduction in aerospace — all before AI was driving the workflow. As Now Assist matures and the digital ticket closes itself, the physical-handover platform delivering these results today multiplies its impact across every workflow that needs to reach the workplace.

The decision window

Every IT leader is making this decision now.

Every MSP CFO and every Fortune 500 CIO is currently writing a 24-month plan for how AI lowers cost-to-serve. By the end of that window, the digital layers of IT services will be substantially automated. The physical layer will not have moved on its own.

The decision being made today — and the decision their clients, their boards, and their competitors are watching them make — is whether to address the physical layer now, or watch a competitor do it first.

Smart Collect® is the only ServiceNow-native answer to that question. The MSPs and enterprise IT teams that close the physical layer in the next 18-24 months capture the services-margin advantage. The ones that wait become the ones being compared against in 2029.

Frequently asked

Common questions on cost, speed, and what changes.

Per MetricNet's 2024 IT Service Desk Benchmarks, onsite (desktop) IT support costs around $70 per ticket — roughly 3× the cost of a Tier 1 digital ticket at around $22. The gap is driven by engineer time, dispatch overhead, travel, parts logistics, and physical handover coordination. The 3× ratio is widely understood; what's new is how it widens as AI compounds savings on the digital side and not the physical side.
For a typical P4 (low-priority) hardware request — broken laptop, peripheral swap, new-starter kit-out — the industry-average resolution time is around 2.9 days, driven by the standard 3-day enterprise SLA. The fastest performers observed across Velocity's customer base resolve in around 10 hours; the slowest extend to as much as 20 days. As agentic AI compresses adjacent IT services to seconds and consumer-grade experiences set the bar at instant, a multi-day handover wait becomes an increasingly visible and increasingly indefensible service problem. The industry is moving away from SLAs as the primary metric toward Experience Level Agreements (XLAs), which measure what the employee actually feels rather than compliance against an internal clock.
No. AI agents — ServiceNow Now Assist, Microsoft Copilot for Service, Salesforce Agentforce, agentic ITSM — can close digital tickets end-to-end, but they cannot perform physical handovers. The moment a workflow requires a device to be exchanged, a peripheral to be swapped, or a laptop to be collected, a human or a physical-fulfilment endpoint is required. AI does not eliminate onsite support; it makes it the only remaining manual cost in IT operations — and therefore the most visible.
For a representative Fortune 500 enterprise (around $10B revenue, 30,000 employees, 25+ sites), onsite IT support consumes around 8% of operational IT cost today — roughly 5% of total IT budget. Per Gartner IT Key Metrics Data 2025, end-user services account for 8-15% of total IT budget, of which onsite/desktop support typically represents 30-50%. The ICP modelled on this page sits in the middle of that range.
Gartner's central forecast (March 2025) projects that 80% of common service issues will be agentic-AI-resolved by 2029, driving a 30% reduction in service operations cost. Enterprise adoption in I&O is forecast to scale from less than 5% in 2025 to 70% by 2029 (Gartner Predicts 2026, December 2025). Gartner also notes (June 2025) that 40%+ of agentic AI projects will be cancelled by 2027 due to procurement immaturity — the technology is real, but vendor selection discipline matters. Most enterprises will see their first material agentic-AI cost reductions between 2027 and 2029.
The AI–physical bridge is the architectural gap between digital AI agents (which can close tickets, navigate systems, and take actions inside software) and the physical world (where devices, peripherals, and physical handovers happen). Smart Collect® is the only ServiceNow-native platform that closes this gap — enabling AI agents to complete tickets that require a physical exchange without dispatching a human engineer. As enterprise AI maturity rises, the value of the physical-layer endpoint rises with it.
The trajectory is sharper for MSPs. MSPs compete on cost-to-serve. As digital cost-to-serve collapses, the physical share of an MSP's delivered cost grows faster than for an in-house IT operation, because MSPs have less control over the rest of the budget structure around it. An MSP that automates the physical layer can bid 15-25% more aggressively than rivals still wedded to engineer-based hand-delivery, while protecting margin. The first MSP in a category to solve the physical layer typically captures share from the others — see, for example, Teceze's expansion into S&P Global via a Smart Locker-led commercial proposition.
Map your trajectory

What does your IT budget look like in 2029?

A 60-minute discovery workshop with a Velocity ServiceNow architect maps your specific environment, calibrates this model to your numbers, and identifies the use cases where Smart Collect® bends the trajectory.

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