Market Insight: Practical High-Value Industrial Use Cases For Generative AI In 2024
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Executive Summary
This report offers a comprehensive examination of the practical, high-value industrial use cases for generative AI (GenAI) for enterprise and industrial firms, as of September 2024. It outlines key advancements in foundational GenAI technologies – such as large language models (LLMs) and data retrieval systems – powering a new breed of natural language search engines, copilot-style chatbots, automated metadata enrichment and code generation. By focusing on real-world applications in operations, sustainability and safety, the report provides actionable insights for technology buyers, business executives and C-Level AI, operational technology (OT) and technology leadership. Highlighting the strategic benefits and implementation challenges, this analysis is essential for those looking to enhance operational efficiency, streamline regulatory compliance and drive lasting innovation with enterprise-grade GenAI tools.
Table of contents
Vendor investments in GenAI continue to support the large language model (LLM) architectureContinuing significant innovation in AI model orchestration for narrowly defined applications
Five practical high-value industrial use cases for GenAI in 2024
Table of figures
Figure 1. Implementation challenges stem from wide variations in GenAI technology maturityFigure 2. Practical high-value industrial use cases for GenAI in 2024
Organisations mentioned
ABB, Air Canada, Algolia, Alibaba Cloud, Amazon, Amazon Web Services (AWS), Andonix, Anthropic, Augmentir, Avarni, Benchmark Gensuite, C3 AI, Carnegie Mellon University, CO2 AI, Cognite, Cohere, Databricks, Datamaran, Diligent, Dozuki, EcoOnline, ehsAI, Elasticsearch, Evotix, FORBES, General Catalyst, GitHub, GLYNT.AI, Google, IBM, Makersite, Meta, Microsoft, Mistral AI, NASDAQ, Neo4j, OpenAI, Origami Risk, Otter.ai, Palantir Technologies, Persefoni, Princeton University, Quentic, Rapid Robotics, REPFLY, RepRisk, Salesforce, Seeq, ServiceNow, Sphera, Sweep, SymphonyAI Industrial, TigerGraph, Trendminer, TSC, Typesense, VelocityEHS, WorkivaAbout the authors
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