hands of experts 16 Unblock your developers 18 Set bold automation goals 21 Conclusion 22 More resources 24 2 AI in the EnterpriseA new way 
 to work As an AI research and deployment company, OpenAI Enterprises seeing the most success from AI adoption are often the ones that invest time and resources in customizing and training their own AI models. OpenAI has invested heavily in our API to make own use cases. “Normally, in a business like ours, building even a prototype requires technical resources and time,” says Elena Alfaro, Head of Global AI Adoption at BBVA. “With custom GPTs, anyone can

knowledge base. Prompt agents to break 
 down tasks Providing smaller, clearer steps from dense resources 
 helps minimize ambiguity and helps the model better 
 follow instructions. Define clear actions guidance, and hands-on support to ensure 
 your success. 32 A practical guide to building agents More resources API Platform OpenAI for Business OpenAI Stories ChatGPT Enterprise OpenAI and Safety Developer

advancements that improve resource efficiency actually lead to increased overall usage of those resources. This is driving new focus on expanding energy production capacity – and new questions about the Open-Source Models – Compute Investment = Closed Models Higher, per Epoch AI Training Compute Resources for Open vs. Closed LLMs – 2/18-9/24, per Epoch AI Source: Epoch AI (11/24) AI Monetization Threats management holds the key. Effective rotational grazing enables more efficient use of natural resources and increased productivity, while also enhancing soil health and improving root structures to sequester

various tasks (Wei et al., 2022). However, the improvement comes at the cost of larger computing resources for training and a potential decrease in inference throughput. These constraints present significant