Cbinsights-企业人工智能路线图：人工智能开发平台格局如何转变，改变买家评估ROI、用例等的方式（英）

The Enterprise AI Roadmap: How the AI development platform landscape has transformed, changing how buyers assess ROI, use cases, and moreWe mined CB Insights data and spoke with 50+ buyers of AI development platforms — including Databricks, Hugging Face, and Scale AI — to understand how they’re deploying AI models, what they’re paying, and what the future holds for the landscape. No company wants to miss out on AI.As commercial applications of AI scale rapidly amid the generative AI boom, enterprises are racing to overhaul their infrastructure to support the deployment and management of these advanced models.Enterprise buyers are increasingly turning to AI development platforms for their AI needs. AI development platforms enable enterprises to manage the AI lifecycle — from data preparation, training, and validation to model deployment and continuous monitoring — through a single platform. The landscape features a mix of enterprise machine learning (ML) players (H2O.ai, DataRobot), big tech products (Google Cloud Vertex AI, Amazon SageMaker and Bedrock), as well as emerging AI developer tools (Predibase, Lightning AI). Source: CB Insights — AI development platforms marketPlatforms are now under intense pressure to adapt their offerings for the genAI era and capture more enterprise AI spend, enabling enterprises to leverage the power of foundation models.We mined CB Insights valuation, headcount, and financing data, as well as 50+ buyer interviews, to map the evolving landscape and analyze its future.Below we’ll cover: 1. The AI development platform market landscape2. How enterprise buyers are evaluating the ROI of their AI tool spend3. The future of enterprise AI development4. Sample buyer case studies by industry The Enterprise AI Roadmap | 2ContentsGenAI is changing the AI development landscape 4The AI development platform market4Legacy ML companies lose steam5Companies harness genAI momentum6Big tech muscles in alongside new startups9Evaluating return on investment (ROI)9Productivity gains9Cost savings10The future of enterprise AI development13Harnessing proprietary data will unlock differentiated use cases15Big tech companies have multiple advantages17Enterprises face pressure to explore open-source models18Task-specific models gain adoption22Consolidation is coming as the generative AI space matures27Select genAI acquisitions, June 2023 – June 202428Enterprises become more disciplined in their AI spend29Customer case studies30AI development platform use case summaries31 The Enterprise AI Roadmap | 3GenAI is changing the AI development landscapeAI development platforms are not new. The landscape features several platforms founded in the early 2010s, when enterprise applications for machine learning started to become popular.But genAI has marked a new era in AI development. Increasingly sophisticated models are opening up new applications that e