AI Valuation Multiples
Explore private market AI valuation multiples with benchmarks structured by stage and region. Updated quarterly.
AI
Artificial Intelligence companies software, infrastructure, and applications that enable prediction, automation, and decision support at scale. Private market AI valuations are often influenced by model differentiation, data advantages, compute intensity, and the ability to translate innovation into repeatable commercial traction.
The category spans foundational models, applied AI products, workflow copilots, and enabling infrastructure. DealMatrix tracks valuation dynamics across 7 funding stages and all major global regions, updated every quarter.
Sector
AI
Software & Data
Sector tracked since
2000
25+ years of data
EV/SALES & EV/EBITDA ACROSS
6 Regions · 7 Stages
Modelled independently via proprietary econometric approach
UPDATE FREQUENCY
Quarterly
Data updates & model improvement
AI Valuation Multiples
Sector benchmark as of 31 March 2025 · median across 6 regions · updated quarterly
How we derive these multiples
DealMatrix multiples are derived from institutional-grade public-market index data covering ~150 GICS sub-industries across 6 regions, with quarterly history back to 2000. Regional scaling follows Damodaran (NYU Stern), and the methodology follows the IPEV Guidelines 2025. Published benchmarks are illustrative and dated; because IPEV 2025 prohibits static multiples for reporting periods from 1 April 2026, current quarterly data for valuation work is available on the platform.
The Venionaire DealMatrix Multiples Model
DealMatrix multiples are proprietary private-market benchmarks, derived through a six-step model that translates public capital-market index comparables into private-market segments and funding stages, adjusted for macroeconomic conditions.
The model produces three components: The reported public multiple, the model-predicted multiple, and the lower bound predicted multiple averaged into the DealMatrix Composite, then adjusted for region and funding stage. The methodology follows the IPEV Guidelines 2025.
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AI Valuation Multiples — FAQ
What is the average valuation multiple for AI companies?
As of 31 March 2025, the AI sector benchmark was an EV/Sales multiple of about 3.5× and an EV/EBITDA multiple of about 16.3× (median across six regions). Multiples vary by funding stage and region; stage-level and current-quarter figures are available in DealMatrix.
What is the difference between EV/Sales and EV/EBITDA for AI?
EV/Sales (enterprise value ÷ revenue) is used for high-growth AI companies that are not yet profitable, while EV/EBITDA (enterprise value ÷ operating profit) applies to mature, profitable ones. Early-stage companies are usually benchmarked on EV/Sales.
How are AI valuation multiples calculated?
Each AI multiple is a weighted blend of public-market index comparables, cleaned for outliers and gaps, then adjusted for macroeconomic conditions, region, and funding stage through a six-step model that follows the IPEV Guidelines 2025.
Do AI valuation multiples vary by region?
Yes. North America serves as the reference market and typically carries the highest multiples, while emerging markets trade at a structural discount. Region-specific figures are available in the DealMatrix platform.
How current is this AI data and how often is it updated?
The benchmark shown is an illustrative annual figure as of 31 March 2025. The underlying model is updated every quarter. Because the IPEV Guidelines 2025 prohibit static multiples for reporting periods from 1 April 2026, current quarterly data for valuations is available in the DealMatrix platform.