NEW YORK, April 15, 2024 — Fortune announced Fortune Analytics, an AI research product developed with Accenture to make more than 20 years of company rankings, financial data and business journalism accessible through conversational questions and visual analysis. A beta release was scheduled for June 4.

The product is designed to combine material from the Fortune 500 and Global 500 with related reporting in one research environment. According to Fortune's product announcement, a custom-trained large language model will help customers query the archive and turn retrieved evidence into charts.

Historical company data becomes queryable

Rankings data normally arrives as annual tables. Answering a question across several years can require downloading files, aligning company names and reconstructing changes in revenue, profit or position. Fortune Analytics is intended to move that work into a conversational interface supported by the publisher's own corpus.

The source base matters because a useful answer must connect a question to consistent definitions and identifiable evidence. Twenty years of records can reveal long-term patterns, but acquisitions, accounting changes, currency movements and revisions can still affect comparisons. An AI response is a starting point for analysis, not a substitute for checking the underlying period and metric.

Content and functions described at announcement

  • more than two decades of Fortune 500 and Global 500 financial information;
  • related Fortune journalism, research and analysis;
  • conversational answers generated from the selected corporate corpus;
  • graphic visualisations intended to expose comparisons and trends;
  • access to archive formats that Fortune said included articles, audio transcripts and other material.

Accenture contributes enterprise AI development

Fortune is working with Accenture on the custom model and product. Accenture chief AI officer Lan Guan said the combination could change how enterprise customers use the Fortune 500 by bringing financial research and archived journalism into a common tool.

The partnership joins two different responsibilities. Fortune supplies and governs the proprietary information, while Accenture contributes AI and enterprise implementation expertise. Product quality will depend on retrieval, model behaviour, permission controls and a clear path from a generated statement back to the original evidence.

Corporate data and business research
Corporate data and business research

Conversational access changes the first step of research

A user may begin with a plain-language question instead of a fixed spreadsheet filter. That can help executives and analysts explore which companies grew through a period, how sectors diverged or how a ranking changed. Follow-up questions can narrow the comparison before a formal analysis is exported.

Convenience also creates risk. A broad prompt can hide an ambiguous definition, and a fluent response may sound more certain than its evidence allows. Users should specify dates, currencies, measures and peer groups, then inspect citations and reconcile important findings with the original financial records.

Visualisation must retain context

Fortune chief technology officer Jonathan Rivers described a tool that could create graphic visualisations from the archive. Charts can make inflection points and outliers easier to see, especially across many companies. They can also mislead when scales, missing data or membership changes are not visible.

Responsible product design should preserve source dates, units, methodology and ranking eligibility next to each output. A visual comparison is not investment advice, and historical rank does not establish future performance. Enterprise users remain responsible for decisions and for any additional licensed data used alongside Fortune's corpus.

The announcement precedes the beta

Fortune announced the partnership at its Brainstorm AI conference and scheduled beta availability for June 4, 2024. The April statement therefore described the intended product before the beta began. It did not establish later pricing, adoption, accuracy results or general availability.

A beta period allows the teams to observe real questions, improve retrieval and identify where answers require better grounding. Useful evaluation should test factual consistency, citation quality, coverage, latency and whether the system declines questions that the source material cannot support.

A new use for a legacy publishing asset

Incoming chief executive Anastasia Nyrkovskaya presented Fortune Analytics as a way to combine the company's journalism, research and financial data. The product also represents an attempt to diversify a publisher's commercial model by making its archive useful as structured enterprise research rather than only individual articles and annual lists.

The value of that model depends on trust. A proprietary corpus can narrow the evidence boundary and improve attribution, but it does not eliminate model error. Clear provenance, corrections, access rules and separation between editorial judgment and commercial product decisions remain essential.

About Fortune Media

Fortune Media publishes business journalism, company rankings and conferences. Fortune Analytics is its planned AI research product developed with Accenture around Fortune's corporate data and archive.

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URL: https://fortune.com/about-us/press-center/
Announcement URL: https://fortune.com/media/502b56eb-c905-4a4f-9f03-fb994aed41b5/