AI agents will handle more complex business tasks and workflows with less human intervention.
Multiagent systems and physical AI will expand automation across software, factories, warehouses, and supply chains.
Governance, security, oversight, and business value will become essential for reliable automation at scale.
Automation has reached a point where simple software rules no longer define the market. AI agents can now handle tasks, make choices, work with other agents, and act across business systems. Gartner reports that 37% of surveyed organizations have already deployed AI agents, while another 34% plan a deployment within the next 12 months. Gartner also expects agentic AI funding to rise by an average of 31.8%, which makes it the fastest-growing technology investment area.
This shift gives 2027 a clear direction. Businesses will move from fixed workflows toward systems that can assess a goal, choose a path, take action, and adjust when conditions change. The change will affect office work, IT, supply chains, factories, and customer service.
AI agents will stand at the center of enterprise automation in 2027. Traditional automation follows set rules, while an agent can assess new information and choose the next step. IBM reports that 86% of surveyed executives expect AI agents to make process automation and workflow redesign more effective by 2027. IBM also reports that 76% of executives have organizations that develop, run, or scale proof-of-concept projects for autonomous workflows.
This change will affect tasks that once needed constant human action. An agent may review a customer request, check account data, select a response, update a system, and send the case to a human when a risk level crosses a set limit. Such systems can handle more than one task without a separate rule for every possible case.
IDC adds another strong signal. The research firm forecasts that agentic automation will enhance capabilities in more than 40% of enterprise applications by 2027. Applications will therefore move from simple tools toward active systems that can take part in business processes.
A single AI agent cannot handle every business process well. Multiagent systems offer a different model. Several specialized agents can divide a complex process into smaller jobs, with each agent focused on a specific role.
Gartner lists multiagent systems among its major strategic technology trends for 2026. The company describes these systems as groups of AI agents that work together on complex goals. This model can support better reuse, stronger control, and easier expansion across business workflows.
A sales process offers a simple example. One agent can review a lead, another can check pricing, a third can prepare contract terms, and another can handle account setup. A control layer can manage the full process and set limits for each agent. Such a structure may become common across finance, sales, IT, and customer operations.
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The next major step will take AI into the physical world. Gartner defines physical AI as systems that sense the real world, make decisions, and act through robots, drones, and smart equipment. Gartner now treats physical AI as a near-term business priority rather than a distant concept.
Factories, warehouses, transport hubs, and supply chains stand out as key areas. Robots can use AI to react to changes rather than follow only fixed instructions. Smart equipment can detect a problem, assess its impact, and trigger a response through connected systems.
IDC also expects software-defined factory systems to gain ground. By 2029, IDC forecasts that 30% of factories will use open, virtualized, software-defined automation platforms to configure and manage control systems from a central point.
Greater autonomy will also create greater risk. Companies will need clear limits for AI agents, strong access controls, audit records, and human approval for high-risk decisions.
IBM reports that 67% of executives expect AI agents to take independent action in their organizations by 2027, compared with 24% today. The same research shows that 57% expect autonomous decisions in processes and workflows, compared with 28% today.
That data points to a major change in enterprise control. Automation will no longer focus only on speed or lower costs. Trust, oversight, security, and measurable business value will shape adoption.
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The strongest automation trend for 2027 will not come from one tool. Agentic AI, multiagent systems, physical AI, process intelligence, and governance will connect into a broader automation layer.
IDC forecasts that 40% of operational data will integrate across applications and platforms autonomously by 2027. That signals a move toward systems that can connect data, make decisions, and act across several parts of an enterprise.
The result will be a new form of automation. Fixed rules will still have value, yet the biggest gains will come from systems that can handle change without a new workflow for every case. The companies that combine autonomy with strong controls will have the clearest path to reliable automation at scale.
1. What is the biggest automation trend for 2027?
Agentic AI stands out as the major trend, with AI agents taking a larger role in business processes and decision-making.
2. How will AI agents change business automation?
AI agents can assess information, make decisions, take actions, and handle different steps within a workflow.
3. What are multiagent systems?
Multiagent systems use several specialized AI agents that work together on complex business goals.
4. What is physical AI?
Physical AI connects artificial intelligence with robots, drones, smart equipment, and other systems that can sense and act in the real world.
5. Why will governance matter more in 2027?
As AI agents gain more independence, companies will need stronger controls, access rules, audit records, security measures, and human oversight.