Methodology

Data Sources & References

Where the numbers come from — the primary benchmark and the external studies cited alongside it.

Georgian + NewtonX AI, Applied Benchmarks, Wave 3 · March–April 2026

Every figure in this report is either primary — from the Georgian + NewtonX benchmark — or external, drawn from a named third-party study and shown as a source line beneath the relevant chart. This page collects both.

Primary data

The report’s own figures come from the Georgian + NewtonX Applied AI Benchmarks, Wave 3 (n=501; technical panel n=252; fielded March–April 2026), with wave-over-wave comparisons to Wave 2 (June 2025) and Wave 1. Some breakdowns are internal cross-tabulations of that dataset by maturity tier and segment. See Methodology for sample design, bases, and significance, and Definitions for how the tiers and segments are defined.

External references

These third-party studies are cited in the report for context and corroboration. They are independent of the Georgian + NewtonX benchmark and reflect their own samples and methods.

  • Microsoft AI Diffusion Report 2025 — pace of AI adoption versus prior technologies. (Microsoft, Feb 2026)
  • PwC 2026 AI Predictions — 2026 as the year agentic deployments scale. (PwC, 2026)
  • ZoomInfo State of AI in Sales & Marketing 2025 — AI users’ productivity gains and hours saved on low-value manual tasks. (ZoomInfo, May 2025)
  • PwC Global Workforce Hopes and Fears 2025 / Stanford — entry-level decline in AI-exposed fields; growth in AI-augmented occupations. (PwC / Stanford, 2025)
  • McKinsey — AI deployed broadly, but most companies not yet seeing significant value. (May 2026)
  • Deloitte 2026 State of AI — revenue expectations from AI versus realized gains. (n=3,235)
  • Writer 2026 — executives benefiting from AI versus those seeing significant organizational ROI. (n=2,400)
  • Bain CFO Survey 2026 — enterprise-wide AI investment increases this year and over two years. (Bain & Company, Apr 2026; n=102)
  • RGP survey of US CFOs — measurable AI impact to date versus expected within two years. (Oct–Nov 2025; n=200)
  • Gartner 2025 CFO Survey — organizations unable to state total AI spending due to fragmented budgets.
  • NBER Working Paper 34984 — macro-level AI impact on employment and productivity. (Mar 2026; n≈6,000 executives)
  • Shift Magazine / LinearB — share of production code that is AI-authored. (Feb 2026)

The report also references industry commentary — Marc Andreessen’s “software is eating the world” (2011) and Jensen Huang’s “AI is eating software” (2017) — as framing, not as data.

Citing this report

When referencing this report, please cite it as Georgian + NewtonX, Applied AI Benchmarks, Wave 3 (June 2026).