The evolution of AI PCs

From AI Assistance to Agentic PCs

  An Agentic PC is your everyday AI PC, designed to help people work alongside AI agents. Depending on how it is deployed, it can also be configured as a dedicated Agent Computer that runs autonomous AI agents continuously.

2023–2024

AI Assistants

Answer Questions

  • Summarize a meeting
  • Improve an email
  • Search across your files

what it takes

  • Tens of TOPS1

2025–2026

Agentic AI

Understand Context

  • Plan a project from your apps 
  • Triage your inbox 
  • Draft a deck from your notes 

What it takes

  • Multi-threaded CPU
  • Large local memory

2026 and Beyond

Autonomous Execution

Complete the Work

  • Execute multi-step workflows 
  • Operate on private data 
  • Coordinate work across apps

what it takes

  • High-performance local AI

The future of enterprise AI isn't about asking better questions. It's about how Agentic PCs enable employees to delegate routine work to AI agents while staying in control of decisions and outcomes.

From AI Assistance to Agentic Computing

Why Agentic Computing Matters for Businesses

For decades, enterprise PCs have helped employees get work done. Agentic PCs help employees delegate routine work to AI agents, enabling people to focus on higher-value decisions while keeping enterprise AI protected, efficient, and cost-effective.

Business Professional Using Laptop in Modern Office with City View

Why Agentic PCs Change the Economics of AI

As organizations deploy more AI agents, cloud inference costs grow with every task they perform. Agentic PCs help reduce recurring cloud costs, optimize token usage, and provide a more predictable model for enterprise AI.

Real-World Impact

As AI agents become more capable and token efficient, the speed of local tool execution, orchestration, and application performance becomes increasingly important.

AMD "Zen 5" x86 CPUs Are Built for the Agentic Era

ASUS ProArt- AMD Ryzen AI Max+ PRO (16 Cores /32 TOPS )
6.0
ASUS Zenbook – AMD Ryzen AI 9 HX 470 (12 Cores / 24 TOPS)
3.2
4-year-old laptop
1.0
Up to
6X

Faster task completion vs. 4-year-old laptop2,3
Six Parallel Agents, Heavy Tool, Developer Workflow
ChatGPT 5.5 High / Codex

AMD AI Platforms

Built for Advanced Agentic AI Workloads

 The most demanding Agentic AI workloads benefit from high-performance AI PCs.

While many Agentic PCs accelerate everyday productivity, advanced enterprise AI workloads require greater compute performance, larger unified memory, and the ability to run multiple AI agents locally. AMD Ryzen™ AI Max PRO is purpose-built for these demanding scenarios.

AMD Ryzen AI Max Series processor package on a black background with the text "Ryzen AI Max Series" visible on the chip.
World's first x86 client processor to run a 300B+ LLMs
  • Run advanced local AI agents Run multiple AI agents locally
  • Execute concurrent AI workflows
  • Up to 192GB unified memory
  • Accelerate AI development
  • Optimize enterprise AI workloads

Proven Agentic AI Use Cases

How Agentic AI PCs Transform Enterprise Workflows

IT Operations

Monitors infrastructure, investigates incidents, executes remediation playbooks, and documents resolution steps.

Software Engineering

Reviews the codebase, implements features, runs tests, and opens a pull request.

 

Executive Support

Coordinates executive calendars, prepares briefings, builds travel itineraries, and drafts follow-up actions.

Cybersecurity

Detects threats, investigates activity, executes response playbooks, and documents security actions.

Customer Support

Resolves customer requests, retrieves account history, drafts responses, and updates CRM records.

Financial Analysis

Reviews filings, builds valuation models, identifies risks, and drafts investment memos.

Expert Insights

Insights

AI infrastructure demands are increasingly determined by the workflow around the model.

Shop Systems

Featured Agentic PCs

Explore commercial Agentic PCs powered by AMD Ryzen AI PRO and Ryzen AI Max PRO processors.

FAQ

Frequently Asked Questions

Agentic PCs help organizations run more advanced AI workloads locally, supporting low cloud inference costs, improving data control, and enabling AI agents to support more sophisticated enterprise workflows.

Agentic PCs enable more AI workloads to run locally, reducing reliance on cloud inference for everyday tasks. This helps organizations optimize token usage, lower AI operating costs, and reserve cloud resources for larger or more complex models.

Running AI agents locally improves responsiveness, keeps sensitive business data closer to where work happens, and reduces dependence on cloud infrastructure. Organizations can use local AI for everyday workloads while leveraging the cloud when additional scale is needed.

Agentic PCs support enterprise workflows that require planning, analysis, and multi-step execution. Common examples include software engineering, IT operations, cybersecurity, executive support, customer service, and financial analysis.

AMD Ryzen™ AI Max PRO processors are designed for demanding Agentic AI workloads, delivering high-performance compute, large unified memory, and the ability to support advanced local AI models and multiple concurrent AI agents.

As AI evolves from assisting employees to supporting end-to-end workflows, organizations need systems that can deliver greater performance, lower AI infrastructure costs, and stronger control over enterprise data. Agentic PCs help enable that next generation of business computing.

Ready to Explore Agentic AI Further?

Register for our upcoming webinar and hear directly from AMD experts about Agentic PCs, enterprise AI, and local AI workloads.

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Footnotes
  1. GD-243: Trillions of Operations per Second (TOPS) for an AMD Ryzen processor is the maximum number of operations per second that can be executed in an optimal scenario and may not be typical. TOPS may vary based on several factors, including the specific system configuration, AI model, and software version. GD-243.
  2. SHO-73: Testing as of July 2026 by AMD. Performance measured as average local tool shard execution time over multiple runs of a CODEX, python-based, multi-agent, heavy tool usage workflow. The workflow used six parallel Codex subagents with ChatGPT 5.5 High and a python harness to perform deterministic offline developer-tool work, including AST/static analysis, compile/import smoke tests, unit-style execution, JSON/CSV serialization, SQLite queries, compression/hashing, package/manifest work, and mixed local-tool workloads. System specifications: ASUS ROG Flow Z13 with AMD Ryzen™ AI Max+ 395 processor, 128GB memory, AMD Variable Graphics Memory set to 64GB, AMD Software: Adrenalin Edition 26.6.2, Performance mode, Windows 11 Pro 25H2, compared with an HP EliteBook with AMD Ryzen™ PRO 6850U processor, 32GB memory at 4800 MT/s, AMD Software: Adrenalin Edition 24.10.20.01, Performance mode, Windows 11 Pro 25H2. All values up to. Performance may vary. SHO-73.
  3. GPT-45: Testing as of July 2026 by AMD. Performance measured as average local tool shard execution time over multiple runs of a CODEX, python-based, multi-agent, heavy tool usage workflow. The workflow used six parallel Codex subagents with ChatGPT 5.5 High and a python harness to perform deterministic offline developer-tool work, including AST/static analysis, compile/import smoke tests, unit-style execution, JSON/CSV serialization, SQLite queries, compression/hashing, package/manifest work, and mixed local-tool workloads. System specifications: ASUS Zenbook S16 with AMD Ryzen™ AI HX 470 processor, 32GB memory at 8533 MT/s, AMD Software: Adrenalin Edition 26.6.2, Performance mode, Windows 11 Pro 25H2, compared with an HP EliteBook with AMD Ryzen™ PRO 6850U processor, 32GB memory at 4800 MT/s, AMD Software: Adrenalin Edition 24.10.20.01, Performance mode, Windows 11 Pro 25H2. All values up to. Performance may vary. GPT-45.