2025年人工智能全景报告

Copyright © 2025 HatchWorks AI, All rights reserved. This e-book is protected by copyright laws. You may notreproduce, share, or distribute it without permission Creative Commons License (CC BY-NC-ND) This work is licensed under a Creative CommonsAttribution - Non Commercial - No Derivs 4.0 License. For more info, visit: creativecommons.org/licenses/by-nc-nd/4.0 A round-up of industry stats, research, and insights to understandwhere AI stands, how it got here, and where it’s going. Index A Look at What’s to Come AI in Action: Industry Applications Tech Trends of 2024 20 The Red Tape of Intelligence:Governing AI’s Power What to Watch Out For: Ethics, Data,and User Experience Looking Forward: AI Is Easy to Do. A Look at Foreword by Omar Shanti,CTO at HatchWorks AI If 2023 was the year of theexperiment, 2024 was the year The barrier to AI adoption has Over the past year, a myriadof companies have built ondevelopments in pre-trained Yet not all succeeded. Whether forreasons of commercial viability,security and privacy, governing AI is easy to do, it’s just hard to do well. This report aims to distill the signal from the noise and provideclarity on what ‘doing it well’ looks like and who the players are that So what to expect? You’ll find a balanced analysis of the most important trendsshaping 2025—from game theoretic analysis about the leadingAI companies down to the emergent pattern of the agent mesh, You’ll also read insights from our team at HatchWorksAI—the people working at the intersections of Whether you’re considering your first generative AIpilot or scaling an enterprise-grade solution, you’llfind actionable guidance and strategies here. Let’s And with that, let’s begin. AI in Action:Industry Applications And with use comes the need for leadership. Chief AI Officers(CAIO) are now in 46% of companies. While companies are figuring out their strategy and theproducts they’ll use Gen AI to produce, their employeesare using this technology in their day-to-day lives. Younger This section brings together AI research from across the web toshow how AI is being used in business today and what it means If it feels like every company around you is using AI, it’s becausealmost every company is.85% of organizations are currently Regardless of age, use is on the up—72% of decision-makersuse Gen AI at least weekly, up from 37% in 2023 (Wharton). But there’s a twist—only 37% of executives believe their GenAI initiatives are truly production-ready. That means 2024 wasfull of pilots that never saw production. That’s something the Given that, all eyes are on 2025 to be the year of the That’s only the case in the companies who are readily embracingGen AI rather than just experimenting with it. Wharton’sresearch shows frequent Gen AI use is most popular among: Among enterprises, investment in Gen AIhas risen from $4.5M to $10.3M. Consulting services help organizations navigate the complexlandscape of AI implementation, providing expertise on aligningtools with business goals and avoiding common pitfalls. Finally, By investing in these areas, enterprises are not just deployingAI—they’re building the internal expertise and systemsnecessary to make it work smarter, not harder. The focus on Most of that investment is going toward This allocation reflects a clear priority: ensuring that AI isnot just adopted, but adopted well. AI tools, no matter howadvanced, are only as effective as the people and processes Given that a majority of execs don’t feel their pilots areproduct-ready, this focus on training, bringing in experts, and Maximize YourAI InvestmentFrom Strategy IT Teams are adopting Gen AI fasterthan anyone else, with 62% using it in Our AI Strategy & Roadmap service isn’t just aboutplanning; it’s about empowering your organization to We combine strategic consulting with AI EmpowermentTraining to ensure your teams are prepared to put AI into It makes sense that IT teams lead the way with AI adoption.Whether in creating self-serve help-desks or leveling up their But they’re not the only ones. Use is widespread: These transformations typically fall into three patterns: Semantic Analysis:Understanding meaning frommultimodal inputs such as user events, intent, sentiment, Content Creation:Generating multimodal outputs likemarketing campaigns, chat conversations, blog posts, and Pattern Recognition:Identifying common occurrencesin data streams, whether it’s fraud detection in finance, By enabling companies to understand, create, and optimizeat scale, these patterns are revolutionizing workflows across Across businesses, AI is making waves, impacting Front ofHouse (user experiences), Back of House (operations), and the Here’s a glimpse at how it’s being applied across sectors like E-CommerceRetail & Finance Top Use Cases Top Use Cases Customer service chatbots, product recommendations, dynamic Fraud detection, automated underwriting, regulatory AI in Action AI in Action