OpenAI Expands Enterprise API with Batch Processing and Lower Latency Tiers

OpenAI has announced a significant expansion of its enterprise API offering, introducing asynchronous batch processing endpoints and tiered latency options that dramatically reduce the cost of running large-scale AI workloads in production.

The new batch API allows enterprise customers to submit large volumes of requests at up to 50% lower cost compared to synchronous calls, with results returned within 24 hours. This makes use cases such as bulk document classification, data enrichment pipelines, and overnight report generation substantially more economical.

The tiered latency system gives developers explicit control over response speed versus cost, with a "standard" tier optimised for throughput and a "realtime" tier retaining the low-latency behaviour existing API customers depend on.

For businesses already running AI-powered automation workflows, these changes represent a meaningful shift. Workloads that previously required careful cost management can now be scaled more aggressively, and new use cases that were previously cost-prohibitive — such as enriching entire CRM databases with AI-generated summaries — become commercially viable.

The announcement reinforces the broader trend of AI infrastructure becoming a commodity utility: powerful, accessible, and increasingly cheap at scale. Organisations that have already built automation foundations will be best placed to capitalise on these reduced costs.