- When an organization requires a mature marketplace with robust trust signals
- If deep written reviews, rigorous certification, or transparent version histories are necessary, GPT Store may feel immature.
- When tight suite integration is required
- When core workflows live primarily inside Microsoft 365, Copilot-style embedded experiences may be more valuable than browsing GPTs in a separate interface.
- When spam and clone risk is intolerable
- Early reporting and user feedback indicate notable noise and spam risk; if a workforce is likely to use unvetted GPTs, this raises operational risk.
- When clear monetization and analytics are required for builders
- Builder monetization has been limited to select programs and lacks public formula transparency; analytics limitations are a frequent complaint.
- When on-premises or dedicated environment controls are required
- Organizations requiring strict hosting or isolated environments may be better served by internal deployments or tightly controlled enterprise offerings (depending on current OpenAI enterprise capabilities).
- Limitations implied by product design
- GPT Store behaves more like a directory than a commerce platform (limited purchase and licensing primitives per GPT).
- Trust signals are limited: ratings may exist, but written reviews and robust verification mechanisms are often criticized as insufficient.
- Spam, policy violations, and clone GPTs
- Press coverage reported that the store included spam and GPTs that appeared to violate policies or involve questionable behavior.
- Builder monetization and analytics gaps
- OpenAI’s monetization FAQ describes a limited test with select US-based builders; details of payout methodology are not public.
- Builders frequently report limited analytics and uncertainty about earnings.
- Security and misuse risks
- Security outlets and academic research have highlighted risks such as prompt leakage, malicious instructions, and other vulnerabilities in custom GPT ecosystems.