OpenAI Expands Enterprise Focus Ahead Of Potential IPO

by THEFUTURE.TEAM

March 18, 2026

Enterprise Focus Drives Next Phase

OpenAI is increasing its focus on enterprise clients as it prepares for a potential IPO later this year. During a recent internal meeting, Applications CEO Fidji Simo said the company is working to turn its generative AI tools into productivity-focused solutions for business use. ChatGPT has reached more than 900 million weekly active users since its launch in 2022. The company now aims to expand enterprise adoption and drive higher-value usage across its platform.

Market Dynamics And Strategic Investments

Competition in the sector is intensifying, with Google and Anthropic advancing their own AI products and exploring public market strategies. OpenAI is positioning ChatGPT as a core productivity tool for enterprise clients, alongside its existing consumer offering.

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Preparation For The Public Market

Preparations for a potential IPO are underway, with a timeline that could extend to the fourth quarter of the year. Chief Financial Officer Sarah Friar is leading changes within the finance function. Recent hires include Ajmere Dale, formerly at Block Inc., and Cynthia Gaylor, former CFO of DocuSign. Both are expected to strengthen investor relations and financial oversight.

Focused Execution Amid Competitive Pressure

In December, OpenAI introduced an internal “code red” initiative to prioritise the development of ChatGPT features. Simo said execution remains the main priority despite increased competition.

Looking Toward The Future

OpenAI has revised its long-term compute spending target to approximately $600 billion by 2030, adjusting earlier projections. Revenue is expected to exceed $280 billion over the same period, with contributions from both consumer and enterprise segments. The updated projections reflect a shift in capital allocation as the company prepares for a potential IPO and expands its enterprise offering.

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Meta’s $18 Billion Settlement Limits State Claims Over Children’s Data

by News Editor

August 28, 2026

Meta’s $18 billion settlement with attorneys general from 29 U.S. states includes a provision limiting future state claims over the company’s use of children’s data for age-assurance systems.

Under the agreement, Meta must develop, train and begin testing a system to identify users under 13 within a year of the settlement taking effect. The company already uses AI-based age-detection tools, although the agreement does not require the new system to use AI.

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States Agree To Limits On Future Claims

The Children’s Online Privacy Protection Act (COPPA) generally restricts the collection and retention of personal data from children under 13. Under the settlement, the 29 state attorneys general agreed not to bring past, present or future claims under COPPA or similar state laws over the specified use of children’s data.

Meta will not be permitted to use information from users under 13 for advertising, marketing or algorithmic optimisation.

Federal Enforcement Remains Unclear

COPPA is primarily enforced by the Federal Trade Commission, which is not a party to the agreement. That leaves open the possibility of separate federal action over how Meta collects or uses children’s data.

Another issue is whether Meta can keep age-assurance data isolated from its other systems. An independent auditor will monitor compliance, but the settlement does not fully specify what data Meta can retain for training, how long it can be stored or whether derived insights can be used elsewhere.

Legal Risks Remain

Joshua Wurtzel, a partner at Schlam Stone & Dolan, said states could still pursue claims if Meta uses the data outside the settlement’s limits. Such cases could depend on how those limits are interpreted.

Peter Jackson, a data and intellectual property attorney at Greenberg Glusker, said the provision could “disincentivize future enforcement actions.”

The agreement gives Meta greater legal certainty around using children’s data for age assurance, but questions remain over federal enforcement, data retention and secondary use.

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