The Big 4 AI Agents of 2025: Complete Overview, Features, and Market Impact

Artificial intelligence (AI) has evolved from a buzzword to a boardroom mandate. By 2025, the world’s largest professional services firms—PwC, Deloitte, EY, and KPMG—launched multi-agent AI platforms.

These platforms, collectively known as the Big 4 AI agents, are more than just tools. They represent a fundamental rethinking of work itself, embedding intelligent digital teammates into the heart of global business operations.

In this article, we’ll unpack the origins, functionality, and strategic impact of each AI agent and why they matter for every business leader navigating the age of AI.

1. PwC Agent OS: Enterprise AI operating system

PwC began experimenting with AI assistants in 2019 but found early chatbots too limited. By 2022, the firm announced a multibillion-dollar commitment to AI. Out of this investment came Agent OS, rolled out in 2025. 

The goal is to build an internal operating system for AI teammates that could scale across hundreds of employees and thousands of clients.

How it works

Agent OS is structured like an enterprise app store for AI agents. Each department can “deploy” digital teammates specialized for their workflows.

• Architecture
  
  • Input layer: Pulls from enterprise resource planning (ERP), customer relationship management (CRM), and compliance databases
    
  • Knowledge layer: Connected to PwC’s proprietary data lake and industry benchmarks
    
  • Governance hub: Ensures all outputs are explainable, compliant, and auditable
    
  • Output: Generates dashboards, predictive forecasts, or regulatory-ready filings
• Core capabilities
  
  • Automates cross-border compliance monitoring
    
  • Runs financial forecasting scenarios with live economic data
    
  • Prepares HR compliance and employee risk reports
    
  • Provides instant insights for environmental, social, and governance (ESG) reporting

Market position

PwC markets Agent OS as a trusted AI partner. Unlike startups building flashy tools, PwC emphasizes compliance, governance, and transparency, making Agent OS particularly appealing to heavily regulated industries such as banking and healthcare.

Among the big AI agents, PwC’s is the most modular and governance-driven, offering a framework that feels less like a chatbot and more like an AI operating system for enterprises.

2. Deloitte Zora AI: Finance and procurement specialist

Known for its strong consulting footprint in finance, Deloitte launched Zora AI in March 2025. The platform grew from Deloitte’s recognition that finance and procurement processes were massive bottlenecks. Zora AI was created as an “AI-powered procurement specialist” to solve these pain points.

How it works

Zora AI is narrower than Agent OS but deeper in finance workflows.

• Core capabilities
  
  • Invoice automation: Scans, extracts, validates, and posts invoices in minutes
    
  • Contract review: Uses natural language processing (NLP) to identify risk clauses, nonstandard language, and missing compliance terms
    
  • Spend analysis: Consolidates procurement data to highlight inefficiencies and cost-saving opportunities
    
  • Predictive modeling: Forecasts supplier delays and recommends contingency actions
• Integration
  
  • Ties directly into ERP systems such as SAP and Oracle
    
  • Generates dashboards for chief finance officers (CFOs) with spend visibility
    
  • Links with procurement platforms to execute purchase decisions

Market position

Zora AI is Deloitte’s bet that transactional AI can deliver immediate returns. By focusing on finance and procurement, Deloitte carved out a niche within the Big 4 AI agents that directly appeals to CFOs and procurement leaders.

For companies exploring AI agent examples to replicate internally, Zora AI demonstrates how a specialized agent can deliver measurable results at scale.

3. EY.ai Agentic Platform: Global tax at scale

EY, one of the world’s largest tax advisory firms, faced an existential challenge: tax laws changing daily across more than 150 countries. On March 18, 2025, EY launched the EY.ai Agentic Platform, embedding 150+ specialized tax agents to support 80,000 professionals worldwide.

How it works

The platform functions as a digital tax colleague, combining EY’s deep tax expertise with the scalability of AI. It also illustrates the difference between AI bots and AI agents. 

While a bot might only automate a single form or calculate one tax figure, EY’s agents collaborate across complex workflows. They integrate legal updates, simulate multiple scenarios, and produce regulator-ready outputs.

• System design
  
  • Knowledge graph: Constantly updates global tax legislation
    
  • Compliance agents: Automates filings in multiple jurisdictions
    
  • Scenario engines: Runs simulations for transfer pricing and merger and acquisition (M&A) deals
    
  • Audit-ready reporting: Creates regulator-approved formats instantly
• Use cases
  
  • Preparing VAT submissions across Europe
    
  • Generating multinational transfer pricing documentation
    
  • Running tax exposure analyses before acquisitions

Market position

EY’s Agentic Platform is perhaps the most domain-specific among the Big 4 AI agents. Its focus on tax complexity makes it invaluable to global corporations facing regulatory uncertainty. Instead of replacing tax experts, it augments them, enabling EY professionals to shift from repetitive compliance to strategic advisory roles.

4. KPMG Workbench: Orchestrating digital audit teams

KPMG’s roots in audit shaped its strategy for AI adoption. Audit requires automation, assurance, transparency, and trust. In June 2025, KPMG launched Workbench, a multi-agent collaboration environment that mirrors human audit teams.

How it works

Workbench is unique among these big AI agents because it emphasizes the orchestration of multiple agents working together.

• Agent roles
  
  • Data agent: Ingests raw client data, runs anomaly detection
    
  • Compliance agent: Cross-checks data against regulatory standards
    
  • Drafting agent: Produces audit-ready deliverables
    
  • Supervisor agent: Ensures consistency, workflow sequencing, and audit trails
• Collaboration model
  
  • Agents hand tasks to one another like a human team.
    
  • Built-in logs document every decision, maintaining accountability.
    
  • It integrates with client portals for direct file exchange.
    

Market position

KPMG’s Workbench is less about speed and more about trust and collaboration. It is designed for industries such as finance, healthcare, and government, where transparency is as important as efficiency. 

In many ways, it delivers the same benefits that business process outsourcing (BPO) once promised—relieving human teams of repetitive, lower-value work. The primary difference is that expertise now remains internal, with AI enhancing it. 

Understanding the “why” behind Big 4 AI agents

Traditional automation and early AI models focused on single-use tasks, such as chatbots answering frequently asked questions (FAQs) or RPA handling invoices. By contrast, agentic AI systems can:

• Collaborate. Multiple agents can hand off tasks, like human teammates.
  
• Reason. They don’t just execute. They analyze, weigh options, and make decisions.
  
• Adapt. They learn from data and context, updating responses dynamically.
  
• Scale. They can be cloned or multiplied to handle thousands of simultaneous tasks.

Research has found that AI can already automate approximately one hour of daily activities, primarily chores and labor-intensive tasks. By 2030, as use cases expand and AI safety improves, that potential could rise to three hours per day. 

The implication is clear: AI will increasingly move from supporting roles to becoming integrated digital teammates. These big AI agents saw three urgent needs in their client base:

• Complexity. Tax codes, regulatory compliance, and global reporting cycles were too vast for static systems.
  
• Speed. Clients wanted near-instant insights and filings.
  
• Trust. Any AI solution must be governance-first, with transparency and audit trails.

Thus, the Big 4 AI agents were born, each tailored to its firm’s strengths, but all converging on the same principle: digital teammates that scale expertise globally.

Market impact: Workforce, trust, and client adoption

These AI agents are more than internal innovations. Collectively, they are shaping global business practices.

• Workforce transformation. Professionals are transitioning into roles as AI supervisors, strategists, and auditors, while firms invest in AI literacy to enable teams to focus on higher-value advisory work.
• Trust and compliance. AI agents create transparent audit trails, deliver standardized outputs across global offices, and reduce compliance risks through real-time regulation updates.
• Client adoption. Clients are replicating these models internally, and industries from banking to retail are adopting agentic ecosystems. By 2028, Gartner predicts 15% of daily work decisions will be made autonomously by agentic AI. 

This shift is not entirely new. Instead, it closely resembles how outsourcing works. For decades, businesses have relied on external partners to handle repetitive or labor-intensive processes, allowing internal teams to concentrate on higher-value strategies. 

The difference with the Big 4 AI agents is that these efficiencies are now kept inside the organization.

The bottom line

Together, the Big 4 AI agents represent a new standard for digital work. They show that AI is no longer experimental—it is now core infrastructure for global business.

For business leaders, the lesson is clear: the age of AI teammates is here. Those who adopt early, learning from the Big Four’s models, can reduce costs and unlock new ways to deliver value.

Want a pragmatic adoption plan or a pilot against your highest-value workflows? Let’s connect, map it, and launch.