Gartner forecasts worldwide AI spending of $2.52 trillion in 2026, a 44% year-over-year increase.
That number matters less as a headline and more as a map of where budgets move once experimentation meets procurement.
Gartner also anchors 2026 inside the Trough of Disillusionment and makes a specific point that changes planning: AI will most often be sold to enterprises by incumbent software providers, and scale follows once ROI becomes predictable.
That is a renewal reality, not a vendor discovery reality.
If your team is building the 2026 plan, assume this dynamic: the next twelve months will be shaped by contract cycles, platform consolidation, and measurable operating deltas tied to renewal leverage.
What the $2.52 trillion figure actually signals
Enterprise spend at this level reflects three forces moving at the same time:
- Procurement becomes the operating system
- AI initiatives that survive move from innovation language into sourcing language: SKU scope, platform commitments, multi-year discounts, and governance controls.
- Incumbents gain a distribution advantage
- When Gartner says incumbents sell most AI in 2026, it points to bundling and attach motions across cloud, data, security, and enterprise apps.
- Predictability becomes the gate to scale
- In 2026, funding expands fastest where outcomes can be framed as a measurable delta inside the same cycle as the spend. Gartner explicitly ties scale to improved ROI predictability.
The center of gravity is infrastructure
Gartner projects AI infrastructure spend of $1.366 trillion in 2026, which is more than half of total AI spending.
This is the clearest signal in the forecast: enterprises and providers are building capacity and foundations, then optimizing usage on top of them.
Gartner adds a more pointed detail: spending on AI-optimized servers is projected to grow by 49% and to account for 17% of total AI spending in 2026.
That tells you where the procurement gravity sits: compute first, then software and services aligned to that compute.
What changes in planning when incumbents dominate
When most AI spend routes through incumbents, the plan becomes an operating discipline.
1. Your biggest AI decision becomes a vendor concentration decision
The practical question is simple: which incumbent captures the majority of your AI budget across cloud, data, security, and application layers?
This decision then determines:
• Negotiation leverage
• Architecture constraints
• Talent requirements
• Governance design
• Speed from pilot to rollout
2. ROI has to be defined in renewal language
ROI that earns scale is measurable inside the same cycle as the spend. That typically means operational metrics tied to a function owner and a cadence.
Examples that procurement and operators can both audit:
• Call resolution time, containment rate, cost per contact
• Sales cycle time, pipeline conversion, forecast variance
• Engineer throughput, incident volume, change failure rate
• Fraud loss rate, false positive rate, investigation time
• Procurement cycle time, contract turnaround time, compliance coverage
3. Vendor selection shifts from features to enforceable outcomes
In a Trough of Disillusionment year, the winning business case is enforceable: baseline, target delta, measurement method, and accountability path.
The question that prevents an AI plan from staying a story
Here is the question to use in every budget review:
Which incumbent vendor will capture the majority of your AI budget, and what measurable business delta will you demand within the same renewal cycle?
When a team can answer both parts with precision, two things happen quickly:
• Procurement gains leverage because the scope is explicit
• Operators gain Monday morning clarity because the change is defined
Gartner’s forecast supports this operating stance: incumbent-led selling in 2026 and scaling gated by predictable ROI.
A practical framework for the next twelve months
Step 1: Map your renewal calendar to the AI scope
List every major renewal across: cloud, data platform, security platform, ERP or CRM, collaboration, and ITSM. Assign an AI scope hypothesis to each renewal.
Step 2: Pick one primary incumbent and one secondary lever
The primary incumbent is where the platform focuses its attention. The secondary lever is the competitor you keep credible to preserve pricing and roadmap concessions.
Step 3: Define one business delta per function with a single owner
One delta per function beats a long list. Tie it to a single exec owner, a baseline, and a measurement cadence.
Step 4: Build the measurement layer before the rollout
Predictable ROI requires instrumentation, governance, and adoption design. Treat analytics and change management as first-class budget lines.
Step 5: Negotiate outcomes, not feature access
Push for terms that align with adoption and measurable impact: usage commitments, support SLAs, implementation credits, price protection, and roadmap alignment.
What did Gartner forecast for AI spending in 2026
Gartner forecasts worldwide AI spending of $2.52 trillion in 2026, up 44% year over year.
Why does Gartner describe 2026 as a Trough of Disillusionment year for AI
Gartner states AI sits in the Trough of Disillusionment throughout 2026 and ties enterprise scaling to improved predictability of ROI.
What part of AI spending is the largest in Gartner’s 2026 forecast
AI infrastructure is projected to reach $1.366 trillion in 2026, accounting for more than half of total AI spending.
What is Gartner’s projection for AI-optimized servers in 2026
Gartner projects a 49% increase in spending on AI-optimized servers in 2026, accounting for 17% of total AI spending.
What is the main planning implication for enterprises in 2026
The forecast indicates that budgets will concentrate on incumbent providers and renewal cycles, with scaling tied to measurable ROI within the same cycle.