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He joined The Verge in 2019 after nearly two years at Techmeme.OpenAI plans to focus on “practical adoption” of AI in 2026, according to a blog post from CFO Sarah Friar. As the company spends a huge amount of money on infrastructure, OpenAI is working on “closing the gap” on what AI can do and how people actually use it. “The opportunity is large and immediate, especially in health, science, and enterprise, where better intelligence translates directly into better outcomes.”Much of the blog post, titled “A business that scales with the value of intelligence,” is about how OpenAI has evolved since it launched ChatGPT and how it has scaled up its business. The company’s weekly active user and daily active user metrics “continue to produce all-time highs,” thanks to a “flywheel” across “compute, frontier research, products, and monetization,” according to Friar. However, the company is also investing a lot on infrastructure, having made about $1.4 trillion in infrastructure commitments as of November of last year.OpenAI announced last week that it will be bringing ads to the platform soon and launched the cheaper ChatGPT Go subscription worldwide. Where OpenAI’s business model goes next will “extend beyond what we already sell,” Friar says:As intelligence moves into scientific research, drug discovery, energy systems, and financial modeling, new economic models will emerge. Licensing, IP-based agreements, and outcome-based pricing will share in the value created. That is how the internet evolved. Intelligence will follow the same path.This system requires discipline. Securing world-class compute requires commitments made years in advance, and growth does not move in a perfectly smooth line. At times, capacity leads usage. At other times, usage leads capacity. We manage that by keeping the balance sheet light, partnering rather than owning, and structuring contracts with flexibility across providers and hardware types. Capital is committed in tranches against real demand signals. That lets us lean forward when growth is there without locking in more of the future than the market has earned.Perhaps some of the “practical adoption” for ChatGPT could come in the form of the hardware devices OpenAI is building in partnership with Jony Ive, with the first device potentially being shown off later this year.Follow topics and authors from this story to see more like this in your personalized homepage feed and to receive email updates.Jay PetersCloseJay PetersSenior ReporterPosts from this author will be added to your daily email digest and your homepage feed.FollowFollowSee All by Jay PetersAICloseAIPosts from this topic will be added to your daily email digest and your homepage feed.FollowFollowSee All AINewsCloseNewsPosts from this topic will be added to your daily email digest and your homepage feed.FollowFollowSee All NewsOpenAICloseOpenAIPosts from this topic will be added to your daily email digest and your homepage feed.FollowFollowSee All OpenAIMost PopularMost PopularDisney deleted a Thread because people kept putting anti-fascist quotes from its movies in the repliesUnder Musk, the Grok disaster was inevitableWhy Coinbase derailed the crypto industry’s political futureBungie’s Marathon shooter launches on March 5thThe LG C5 and Apple’s M4 Mac Mini are both steeply discounted this weekendThe Verge DailyA free daily digest of the news that matters most.Email (required)Sign UpBy submitting your email, you agree to our Terms and Privacy Notice. 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OpenAI’s 2026 strategy, as outlined in a blog post by CFO Sarah Friar, centers on “practical adoption” of artificial intelligence, emphasizing the alignment between AI capabilities and real-world applications. Friar highlights the company’s efforts to bridge the gap between what AI can achieve and how users interact with it, a challenge exacerbated by the rapid evolution of both technology and user demands. This focus is driven by the recognition that AI’s potential in sectors like health, science, and enterprise requires not just innovation but also systemic integration into existing workflows. Friar underscores that “the opportunity is large and immediate,” particularly in domains where enhanced intelligence directly translates to measurable outcomes, such as medical diagnostics, scientific research, and corporate efficiency. The strategy reflects a shift from purely technical advancements to addressing the practical barriers that hinder widespread AI implementation, including cost, accessibility, and user familiarity. By prioritizing “practical adoption,” OpenAI aims to ensure that its tools are not only cutting-edge but also adaptable to the diverse needs of industries and individuals, fostering a more seamless transition from experimental AI to everyday utility.

The blog post, titled “A business that scales with the value of intelligence,” traces OpenAI’s evolution since launching ChatGPT, emphasizing its growth as a scalable enterprise. Friar notes that the company’s weekly and daily active user metrics have reached record highs, attributed to a “flywheel” effect that integrates compute power, frontier research, product development, and monetization. This cycle creates a self-reinforcing loop: improvements in AI models drive user engagement, which in turn generates data and revenue to further refine the technology. However, this growth demands significant infrastructure investment, with OpenAI committing approximately $1.4 trillion in infrastructure projects as of November 2025. These investments are critical for maintaining computational capacity to support the increasing demands of AI training and deployment, particularly as models become more complex and data-intensive. Friar acknowledges that scaling such infrastructure requires long-term planning, as securing high-performance computing resources often involves multi-year commitments. This approach ensures that OpenAI remains competitive while avoiding the pitfalls of overextending resources in a rapidly shifting market.

Beyond infrastructure, OpenAI’s business model is evolving to accommodate the expanding role of AI in various industries. Friar outlines a future where traditional revenue streams, such as subscription services and direct sales, will be complemented by new economic models like licensing agreements, intellectual property (IP)-based partnerships, and outcome-based pricing. These mechanisms, she argues, mirror the trajectory of the internet’s growth, where value creation and monetization strategies adapted alongside technological advancements. For instance, OpenAI could generate revenue by licensing its AI tools to enterprises for specific applications, such as drug discovery or financial modeling, rather than relying solely on consumer subscriptions. Outcome-based pricing, where clients pay based on the results achieved by AI systems, could further align OpenAI’s interests with those of its users, incentivizing the development of more reliable and effective solutions. Friar stresses that this diversification is essential for sustaining growth as AI becomes embedded in critical industries, where the stakes of failure are higher and the need for tailored solutions more pronounced.

To manage these ambitions, OpenAI is adopting a pragmatic approach to resource allocation and operational flexibility. Friar explains that the company prioritizes maintaining a “light balance sheet” by partnering with external providers rather than owning all infrastructure outright. This strategy allows OpenAI to avoid the financial risks associated with overcommitment while leveraging the expertise of specialized firms. Contract structures are designed to be adaptable, enabling OpenAI to switch between hardware providers or adjust agreements as market conditions change. Capital expenditures are also tied to real-world demand signals, ensuring that investments in compute power and other resources align with user growth rather than speculative forecasts. This disciplined approach is intended to mitigate the inherent volatility of scaling AI operations, where demand can fluctuate unpredictably. By balancing long-term planning with short-term adaptability, OpenAI aims to navigate the complexities of global AI adoption without compromising its financial stability.

The article also hints at OpenAI’s exploration of hardware innovations as part of its practical adoption strategy. Friar mentions collaborations with Jony Ive, the former Apple design chief, to develop hardware devices that could enhance AI accessibility and performance. While specific details remain scarce, the partnership suggests a focus on creating user-friendly interfaces or specialized computing tools that bridge the gap between software capabilities and physical interactions. The first device from this collaboration could be unveiled later in 2026, potentially offering a new way for consumers and businesses to engage with AI. Such hardware initiatives reflect OpenAI’s broader goal of making AI more tangible and integrated into daily life, moving beyond software-centric solutions to address the physical and ergonomic challenges of adoption. This approach aligns with Friar’s emphasis on practicality, as hardware innovations could lower barriers to entry by simplifying access or improving the efficiency of AI applications.

In addition to internal strategies, OpenAI’s 2026 plans include expanding its monetization tactics. The company recently introduced ads on its platform and launched the cheaper ChatGPT Go subscription globally, signaling a shift toward more diversified revenue streams. These moves aim to make AI tools more accessible while generating additional income to fund further development. Friar acknowledges that the company’s business model will need to evolve beyond its current offerings, incorporating new revenue sources as AI becomes more deeply integrated into industries. For example, OpenAI could explore partnerships with healthcare providers to deploy AI in clinical settings or collaborate with educational institutions to develop AI-driven learning tools. Such expansions require careful consideration of regulatory, ethical, and market factors, as well as the ability to scale solutions without compromising quality. Friar’s comments suggest that OpenAI is prepared to experiment with different monetization approaches, recognizing that a one-size-fits-all model may not be viable in the long term.

The challenges of scaling AI while ensuring practical adoption are compounded by the need to balance innovation with user expectations. Friar notes that growth is not always linear, as there are periods when infrastructure capacity outpaces demand or vice versa. During such times, OpenAI must navigate the tension between investing in future capabilities and managing current resources effectively. This requires a nuanced understanding of market dynamics, including the pace at which industries adopt AI and the varying needs of different user groups. For instance, while tech-savvy startups may rapidly integrate AI tools, larger organizations with entrenched workflows might require more time and support to transition. OpenAI’s strategy must account for these disparities, ensuring that its solutions remain relevant and accessible across diverse contexts. Friar’s emphasis on flexibility and partnership underscores the company’s commitment to addressing these challenges without overextending its resources.

Ultimately, OpenAI’s 2026 focus on practical adoption reflects a broader industry trend toward making AI more accessible and impactful. As the technology matures, its success will depend not only on technical advancements but also on how effectively it can be integrated into existing systems and workflows. Friar’s vision for OpenAI positions the company as a leader in this transition, leveraging its resources and partnerships to create AI solutions that are both innovative and practical. By prioritizing user needs, diversifying revenue streams, and maintaining operational agility, OpenAI aims to solidify its role as a key player in the global AI landscape. The coming years will test whether this strategy can sustain growth while addressing the complex interplay of technological, economic, and social factors that shape AI adoption.