Fortune AIQ 75

From the start, the goal of this project was to design a data collection process that could assess how effectively different Fortune 500 companies have been implementing AI. We knew at the beginning that it would not be feasible to collect complete data on all 500 companies in the Fortune 500, so we began the project by identifying a smaller list of companies in the Fortune 500 targeted for data collection.
 

Next, working with the Fortune editorial team, ETR designed a survey questionnaire that could be sent to IT decision makers at Fortune 500 organizations to evaluate how much success an organization has had at implementing AI. The survey consisted of a short screener to confirm employment status with a Fortune 500 organization, followed by a section designed to assess investment levels in AI technology at a respondent’s own company and a section designed to assess impressions respondents have of AI implementation at other companies in their sector.

The final AIQ RANKING SCORE is a weighted average of four component scores. Where a company was ranked on the 2025 AIQ 50 list, its previous AIQ ranking score is also included as an additional input; for companies without 2025 data, the four component scores are reweighted to sum to the full score. Including the prior-year score stabilizes year-over-year movement for returning companies, so a company’s placement reflects sustained performance rather than a single year of survey results. Each of the four component-scores represents an aggregation of survey responses collected by ETR. These scores are weighted differently. Those components are named below:
 

1. Self-Report Score
 

2. Peer-Report Score
 

3. Peer-Selection Score
 

4. AI-Agents Score-Added new to the 2026 survey
 

The “Self-Report” score is calculated based on survey responses where respondents are asked to reflect on AI implementation at their own company; the “Peer-Report” score is based on responses where respondents are asked to reflect on AI implementation at other companies in their sector; the “Peer-Selection” score is based on how frequently respondents select a company as “most effective” in their sector at implementing AI; and finally the “AI Agents” score measures the maturity, realized value, and scale of an organization’s AI-agent deployment.
 

“Self-Report”: Survey questions focused on AI implementation, return on investment, spending, and value.
 

“Peer-Report”: Survey questions focused on AI implementation, business development, competitive advantage, governance, leadership within sector/industry, and future prospects.
 

“Peer-Selection”: Survey question asked respondents, "Besides your own company, which single competitor/company in your sector/industry segment do you think is using AI most effectively?"
 

“AI-Agents”: Respondents were asked whether they have AI agents deployed in production, and only those answering yes proceeded with the remaining questions in this section. The score measures the maturity, realized value, and scale of an organization’s AI-agent deployment among companies with agents in production.

ServiceNow, ETR, and Fortune team including Ashley Lutz, Alexei Oreskovic, Jeremy Kahn, Lydia Belanger, and Scott DeCarlo