AI’s Push for Consumer Scale and Enterprise Infrastructure

Anthropic and OpenAI are accelerating a two-front race in artificial intelligence, expanding from chatbots into enterprise workflows while competing for paid subscribers as consumer habits harden.

New data reported by The Information shows that daily signups to Anthropic’s Claude chatbot have tripled since November, while paid subscribers have more than doubled since October and free users have grown 60% in the past month.

The surge suggests that even as Anthropic emphasizes enterprise APIs, its consumer business is gaining momentum.

The company has previously estimated that roughly 86% of its $4.5 billion or so in 2025 revenue was expected to come from sales of its models through its application programming interface, with about $600 million coming from chatbot sales. That split underscores a broader shift underway across the AI sector: Consumer traction is increasingly feeding enterprise strategy, and vice versa.

At the same time, OpenAI continues to dominate consumer usage. As PYMNTS reported, ChatGPT leads in consumer AI adoption as OpenAI rolls out new paid tiers and monetization strategies, while internal projections suggest the company expects ChatGPT to reach 220 million paid subscribers by 2030. Separate PYMNTS Intelligence data shows that consumers are locking in AI usage habits early, making initial platform choice more consequential over time.

Against that backdrop, both companies are pushing beyond simple chat interfaces.

Turning Chatbots Into Workflow Engines

Anthropic has been repositioning Claude from a conversational assistant into a tool embedded in enterprise operations. As PYMNTS reported, the company is moving Claude beyond chat into structured enterprise workflows, integrating the model into coding, document analysis and business process automation.

The spike in consumer signups appears linked in part to the growing popularity of Claude Code, a coding agent available to paid subscribers, and Claude Cowork, its AI agent for automating other types of white-collar tasks. Those tools blur the line between consumer subscription and enterprise productivity software, allowing individual users to adopt agent-like capabilities before companies formalize deployments.

Anthropic has also made a targeted bet on legacy modernization. Its recent push into COBOL translation, covered by PYMNTS, aims to help financial institutions convert mainframe code into more modern programming languages. That move positions Claude not just as a productivity tool, but as an infrastructure bridge for banks and enterprises grappling with decades-old systems.

For large financial institutions, that capability could shift mainframe economics. Automating code migration reduces dependence on scarce COBOL developers and potentially lowers long-term maintenance costs, while accelerating digital transformation initiatives.

Consumer Habits, Enterprise Stakes

The convergence of consumer growth and enterprise functionality reflects a deeper structural shift. Early consumer adoption is not occurring in isolation. Professionals are bringing AI tools into their daily workflows, effectively piloting enterprise use cases from the bottom up.

That dynamic gives OpenAI a distribution advantage, with ChatGPT’s 910 million weekly active users far outpacing competitors. But Anthropic’s rapid growth in signups suggests that differentiation around coding agents, enterprise automation and ad-free positioning may resonate with certain segments.

The competitive field also extends to monetization philosophy. Anthropic recently emphasized that it would not introduce advertising into Claude, contrasting its approach with OpenAI’s experimentation around ads. For enterprises evaluating vendor risk, those choices may influence perceptions of long-term alignment.

Ultimately, the race is no longer simply about model performance. It is about distribution, embedded workflows and revenue mix. Companies that can convert consumer scale into enterprise adoption, while turning enterprise credibility into consumer trust, may be best positioned to define the next phase of AI economics.

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