介绍
自主企业是采用人工智能 (AI)、机器学习 (ML)、机器人流程自动化 (RPA) 和数据驱动决策等先进技术来减少人类在业务流程和运营中的作用的组织。
本质上，它是一种能够借助自动化系统自行响应、调整、优化甚至纠正的业务。这种转变的动力源于对运营效率、实时数据分析、各行各业（IT、制造、零售、金融服务和保险业）数字化转型战略日益增长的需求，以及云计算、物联网和人工智能技术的融合。
2025 年至 2031 年期间，自主企业市场预计以 17.1% 的复合年增长率增长。
增长战略
合作伙伴关系和联盟：例如，微软与咨询公司或系统集成商合作，协助企业部署自主代理/基于代理的解决方案。
产品创新与增长：各公司正在开发低代码或无代码平台，使企业能够开发自主代理（软件机器人/代理），而无需太多人工编码。例如，微软的 Copilot Studio 有助于创建多代理编排。
Mergers & acquisitions: Acquiring new capabilities (like security automation or AI lifecycle management). Example: Check Point's recent actions in AI-security build up the autonomous enterprise security stack.
Industry-specific verticalisation: Verticalising autonomous enterprise solutions for specific industries (manufacturing, supply chain, retail, BFSI) for greater domain value. As indicated, the solution segment accounts for ~65 % of the 2024 market.
Geographic growth & services expansion: Growth markets in Asia-Pacific, Middle East, emerging markets, as well as growing demand for professional services around autonomous enterprise deployments.
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Future Opportunities & Trends
Agentic AI and autonomous agents: Next generation is not just automating tasks, but having autonomous agents which are able to act, cooperate and make decisions (e.g. multi-agent orchestration). Microsoft puts a strong emphasis on this "web of agents" vision.
Security and autonomy convergence: As businesses implement autonomous systems, security becomes paramount autonomous security processes, threat detection and mitigation in real-time (e.g., Check Point's AI-driven Infinity Platform).
Edge, IoT & real-time decision making: Autonomous businesses will increasingly place intelligence at the edge (factory floor, supply-chain points, logistics), facilitating fast, local decision-making.
Industry-specific autonomous processes: Applications like predictive maintenance (manufacturing), autonomous supply-chain orchestration (logistics) and autonomous customer-engagement workflows (retail & BFSI) are gaining momentum. For instance, process automation accounted for 31 % of applications in 2024.
Skill-gap and governance solutions: With increasing complex automation, enterprises will require services related to skills, governance, compliance and integration. Integration of legacy systems and talent shortages are common challenges for several organisations.
New business models & "agent boss" jobs: Certain companies (e.g., Microsoft's story) see workers controlling AI agents instead of performing tasks manually the human becomes manager, the agent is the doer.
Key Segments
By Component
Solution
Services
By Business Functions
Accounting and Finance
IT
Human Resource
Sales and Marketing
Supply Chain and Operations
By Vertical
BFSI
IT & ITeS
Retail & Ecommerce
Healthcare
Manufacturing
Government & Defence
Key Players & Recent Developments
Microsoft
Microsoft has been proactively driving its vision for the autonomous enterprise through its Microsoft 365 Copilot, Copilot Studio, and Dynamics 365 solutions.
At Build 2025, Microsoft announced new features in Copilot Studio: "multi-agent orchestration", "bring your own model" using Azure AI Foundry, and enterprise agent identity using Microsoft Entra.
Microsoft made a strategic partnership with PwC (January 2025) to take AI agents to industry scenarios and empower businesses to scale autonomous workflows.
They're more and more focusing on the "autonomous enterprise" story: transitioning from apps to agents.
Microsoft will let organisations build autonomous AI agents through Copilot Studio and unveiled 10 pre-configured autonomous agents for Dynamics 365.
IBM
IBM is also one of the most significant players in the autonomous enterprise arena:
IBM CEO unveiled a plan to bring together and enable AI agents from various vendor platforms (Adobe, Workday, Salesforce) and make use of IBM's own Granite AI models.
In October 2025, IBM formed a strategic alliance with Anthropic to bring Claude large-language models into its enterprise software products, announcing further investment in AI/agentic workflows.
Check Point
In the area of cybersecurity, Check Point (an entrant in autonomous enterprise security) is acting:
February 2025: It released six new AI-enabled features for its Infinity Platform to drive zero-trust acceleration, simplify security operations and lower complexity.
September 2025: It revealed a definitive deal to buy Lakera, an AI-native security platform, to enable full enterprise AI lifecycle security as the basis for autonomous enterprise adoption by securing AI models and agents.
These trends reveal how vendors are adding autonomous solutions (agents, automation, AI) and securing them, which is essential for autonomous enterprise adoption.
Opportunities
SME adoption: Although large enterprises dominate today, there is a huge opportunity in small and midsize businesses embracing autonomous workflows to bypass competitors.
Emerging markets: Countries like Asia, Latin America, Africa have lower legacy overhead and can embrace autonomous enterprise solutions faster.
Industry-specific solutions: Autonomous enterprise solutions bespoke to an industry (e.g., autonomous orchestration of logistics, autonomous diagnostics for healthcare) can enable new top lines.
Security and governance services: Enterprises will require secure frameworks around AI agents, data governance and compliance and thus drive demand for services and consulting.
Edge/IoT integration with autonomous systems: Autonomous enterprise solutions that bring IoT, edge computing and AI for real-time decision-making (particularly in manufacturing and utilities) is a lucrative area.
Conclusion
在自动化、人工智能、实时决策和数字化转型需求的推动下，自主企业市场正在强劲增长。那些能够实施自主工作流程的企业，能够在其中整合代理、自动化和分析技术，最大限度地减少人工干预，从而获得巨大的竞争优势。该市场覆盖广泛，涵盖面向职能部门（IT、销售、财务、供应链）和行业（金融服务、保险、制造、零售、物流）的解决方案和服务。微软、IBM 和 Check Point 等巨头正在大力投资自主时代的代理平台、自主工作流程和安全保障。
常见问题 (FAQ)
自治企业到底是什么？
自主企业采用人工智能、机器学习、机器人流程自动化、分析和自动化，以最少的人工干预实现运营、决策和流程，从而企业可以实时响应、优化和调整。
什么推动了自主企业市场的增长？
关键驱动因素是：AI/ML 能力的变化、对运营效率的需求、实时分析和决策的要求、行业的数字化转型、不断发展的云/边缘基础设施以及安全/自动化融合。
主要的挑战或制约因素是什么？
一些关键的限制因素包括：部署的初始成本高、遗留系统集成、缺乏熟练的员工、数据治理和安全问题以及自主系统的扩展复杂性。
哪些行业受益最多？
商业、金融服务和保险业 (BFSI)、IT 和 ITES、制造业、物流和供应链、零售和电子商务以及医疗保健等行业是自主企业解决方案的主要采用者。例如，由于风险、欺诈和自动化需求，商业、金融服务和保险业占据了相当大的比例。
企业走向自主化需要注意什么？
企业应该考虑：业务战略与自主目标的同步；数据质量和治理；开发或合作获得必要的人工智能/自动化专业知识；安全和信任框架；从目标用例（例如流程自动化、代理）开始并逐步扩展；以及投资回报率、生产力效益和风险衡量。
