All the Companies With AI Agents in 2025: From Microsoft Copilot Agents to Anthropic Claude Agents

In 2025, AI agent frameworks transitioned from being independent to becoming actual products. For buyers checking out companies with AI agents and brands featuring AI agents, the focus changed from “Can it chat?” to “Can it plan, act, and make my experience with this company smoother?” The following is a curated selection of businesses that have the best AI agents, including how each company debuted it or rebranded with it in 2025, as well as what distinguishes them from other businesses. 

At a Glance: Branded AI agents in 2025

• Microsoft Copilot agents for enterprise, developer, productivity, and security.
• Salesforce Agentforce for CRM tasks that plan, act, and audit inside records.
• Anthropic Claude agents via the Claude Agent SDK and reliability playbooks.
• Security Copilot agents across the Microsoft ecosystem for SOC workflows.
• Vertical startups shipping focused research, web, and CX agents.

Microsoft Copilot Agents: enterprise, developer, and security workflows under one roof

Microsoft used Build 2025 to frame the “age of AI agents,” introducing Copilot agent modes that break work into steps, call tools across Microsoft 365, Azure, and GitHub, retain scoped memory, and present plans for approval. In security, Copilot agents previewed alert triage, incident narratives, policy checks, and vuln backlog grooming, signaling a full-stack posture that spans productivity, cloud, dev, and SOC operations (Microsoft Build 2025) (The Verge).

• Copilot agents automate workflows across Microsoft 365, Azure, and GitHub.
• Why it matters: Copilot agents live where identity, data, and permissions already are, which shortens the path from chat to closed loop.
  

Salesforce Agentforce: AI agents for CRM with plan, act, and audit in the record

Salesforce reintroduced its assistant stack as Agentforce, positioning “AI agents for CRM” that search first-party data, draft stepwise plans, get approvals, and execute directly in the object model with governance from the Einstein Trust Layer. Documentation and Trailhead shifted from generic copilot language to explicit agent orchestration, with heavy emphasis on transparency and auditable actions for regulated industries (Agentforce) (Trailhead).

• Agentforce acts directly within CRM records with transparent, auditable steps.
• Why it matters: revenue work needs agents that act inside CRM with logs legal and risk can defend.

Anthropic Claude Agents and the Claude Agent SDK: reliability patterns you can run in production

Anthropic focused on steerability and reliability with the Claude Agent SDK and engineering notes on context windows, memory stores, planning loops, tool arbitration, and stop conditions. The company published recipes, telemetry hooks, and guardrail patterns so teams could reduce flakiness and survive audits. For companies with AI agents under compliance, this “make it dependable” stance is a differentiator (Claude Agent SDK) (Effective context engineering).

• Claude SDK offers reliability and auditability for production-ready agents.
• Why it matters: reliability is a product feature, not a side effect of bigger models.

Google Agent Frameworks, AWS Agent Patterns, and OpenAI Orchestration: the hyperscaler convergence

Cloud and model providers converged on similar agent patterns in 2025, moving from chat assistants to frameworks that preview plans, call tools, retain memory, and enforce guardrails across calendars, docs, cloud resources, and code. Names differ, but capabilities rhyme. For multi cloud buyers mapping companies with AI agents, expect feature parity with selection driven by identity, cost control, governance, and ecosystem depth. 

• Hyperscalers now offer similar agent features—planning, memory, and guardrails.
• Why it matters: procurement will hinge on integration depth and policy controls more than raw model branding.

Microsoft Security Copilot Agents: SOC-ready triage and investigation

Beyond keynote narratives, Microsoft’s security org showcased domain agents that reduce level one noise and tee up higher-risk decisions for analysts, with previews of incident summaries, guided investigations, and policy aware actions. Security is a bellwether for the best branded AI agents in 2035 because success is measurable on precision, recall, and MTTR (The Verge).

• Security Copilot streamlines alert triage and investigations for SOC teams.
• Why it matters: SOC is structured, high volume, and audited, which exposes agent strengths fast.

Salesforce Agentforce for Service and Sales: agents in the flow, not in a sidebar

Salesforce’s ecosystem messaging emphasizes plan transparency, approvals, and actions written back to records. That triad, plan, act, audit, is the narrative that moves agents from “assistant toy” to “trusted coworker” for revenue teams. For brands with AI agents that touch customers, this is what privacy and risk teams will ask to see (Agentforce).

• Agents work inside workflows, logging plans and actions for revenue teams.
• Why it matters: revenue leadership funds agents that reliably move cases, quotes, and renewals.

Anthropic’s “Building Effective Agents” Research: the playbook for plans, tools, memory, and handoff

Alongside the SDK, Anthropic published a set of engineering posts that many teams adopted to standardize agent scaffolding and testing. The goal is simple, fewer bespoke patterns and more predictable behavior under policy. For brands with AI agents that must withstand audits or incident response, published, testable patterns are as valuable as model IQ (Building effective agents).

• Anthropic’s patterns standardize agent behavior and reduce custom code.
• Why it matters: shared designs reduce drift, on call surprises, and regulatory friction.

McKinsey State of AI 2025: adoption is real but operating model is the bottleneck

McKinsey’s survey flagged a widening gap between pilots and scaled deployments. Wins correlate with role design, data plumbing, and governance, not just model choice. Translation for brands with AI agents, the marketing story must include org change and permissions if you want durable ROI (McKinsey State of AI 2025).

• Scaling agents needs new roles and governance, not just better models.
• Why it matters: agents need default permissions and supervision to act at scale.

Vertical AI Agent Startups: focused autonomy where KPIs are clear

A wave of startups shipped narrow agents for research, browsing, operations, and CX. Funding news and vendor roundups point to traction where tasks are repetitive, toolable, and measured. Expect consolidation with winners packaging workflow depth, compliance layers, and browser native orchestration that buyers can deploy without custom glue code (Sendbird roundup).

• Startups deliver focused agents for measurable, repeatable tasks.           
• Why it matters: autonomy pays first where success is obvious and logs are clean.

FAQ

What made 2025 the breakout year for companies with AI agents?

Vendors shipped agents that plan and act inside real apps and permissions. Microsoft Copilot agents and Salesforce Agentforce led with execution in suite, while Anthropic’s Claude Agent SDK gave builders patterns that hold up in production.

Which brands with AI agents look most production ready for business users?

Agentforce inside CRM and Microsoft Copilot agents across 365, Azure, and GitHub, because both can act on first party data with approvals, logging, and governance.

Where should a team start to build a reliable agent?

Adopt a published pattern for plans, tools, memory, and stop conditions. Anthropic’s posts and Claude Agent SDK are a strong baseline, then layer identity, permissions, telemetry, and audits.

Is enterprise adoption real yet, or still hype?

Adoption is rising, but scale requires rewiring roles and permissions so agents can act by default. Surveys highlight operating model and governance as the gating factors.

The Competitive Landscape of AI Agents

The 2025 agentic AI product category had distinct competitors. Microsoft Copilot agents targeted productivity, dev, cloud, and security. Salesforce Agentforce focused on revenue-generating and customer-facing jobs. Teams can ship confidently using dependability recipes from Anthropic Claude agents. Vertical startups filled small autonomy-paying voids. If you are comparing firms or brands with AI agents for your roadmap, agents that can operate on your systems with audit trails and operating patterns your teams can run safely at scale will be the next benefit.