With their infrastructure, resources, and expertise to provide multi-cloud services, hyperscalers are crucially positioned to capitalize on the promise of generative AI, as they can provide the scalable cloud and storage resources necessary to run these new tools. Furthermore, with recent announcements like Google Gemini, they’re also making critical investments in the space. We wanted to better understand who is currently leading the charge, and where our network is looking to deploy their own gen AI solutions today: - Microsoft - AWS - Google Cloud - Oracle - Cohere, NexGen, or Other Similar Services Based on this survey, Microsoft is still far and away the leader in the space today, with AWS trailing a ways behind. And yet, the future holds many opportunities for competition. opportunities exist in:  – Hardware investment in specialized hardware (GPUs, chips, etc.) will accelerate training time and data processing, leading to larger models and more complex datasets  – AI-powered enhancements to existing platforms and developer offerings are enabling more efficient deployment of AI models (easier management of backend resources, responses to security incidents, etc.)  - GitHub co-pilot from Microsoft, CodeWhispererfrom AWS, and IBM Watson Code Assistant will enable the creation of test cases and test documents, and assist developers in writing clean, efficient code  - Hyperscalers are heavily investing in large language models, as cloud computing offers the perfect solution for processing LLMs