AI Agent Operational Lift for Cohnreznick in New York, New York

Why AI matters at this scale

CohnReznick LLP is a leading advisory, assurance, and tax firm serving clients across numerous industries. With over a century of operation and a workforce in the 5,001-10,000 band, the firm manages vast volumes of complex, unstructured financial data for its clients. At this scale, manual processes in audit, tax preparation, and advisory services create significant cost pressures and limit the capacity for high-value strategic counsel. AI presents a transformative lever to enhance service quality, improve operational margins, and redefine the client relationship from compliance-focused to insight-driven.

For a firm of CohnReznick's size, AI adoption is not about replacing professionals but augmenting them. The sheer volume of transactions auditors must review and the complexity of modern tax codes make manual methods increasingly untenable. AI can automate routine tasks, analyze complete datasets rather than samples, and surface hidden risks and opportunities. This allows the firm's experts to focus on areas requiring professional judgment, complex problem-solving, and deeper client interaction. The competitive landscape in professional services is intensifying, with clients demanding more proactive insights and efficiency. Firms that harness AI effectively will differentiate on quality, speed, and value, protecting and growing their market share.

Concrete AI Opportunities with ROI Framing

1. AI-Enhanced Audit Analytics

Implementing machine learning models to perform continuous audit monitoring and full-population testing can dramatically reduce the hours spent on manual sampling and vouching. The ROI is direct: a 20-30% reduction in time spent on substantive testing translates to millions in recovered capacity, which can be redirected to higher-margin advisory work or used to handle more client engagements without linearly increasing headcount. It also reduces audit risk by identifying anomalous patterns a human might miss.

2. Intelligent Tax Automation

Natural Language Processing (NLP) and Optical Character Recognition (OCR) can be deployed to automatically extract data from client-provided documents—such as W-2s, 1099s, and expense reports—and populate tax workflows. This reduces manual data entry errors, cuts preparation time, and allows tax professionals to focus on complex planning and strategy. The ROI manifests in faster turnaround times, improved accuracy (reducing costly amendments), and enhanced client satisfaction through a smoother process.

3. Predictive Client Advisory Services

By building models that analyze a client's historical financial and operational data alongside market trends, CohnReznick can offer predictive insights on cash flow, inventory management, or potential M&A targets. This shifts the service model from retrospective reporting to forward-looking partnership, justifying premium fees and deepening client stickiness. The ROI is in client retention, expansion of service lines, and differentiation from competitors who offer only compliance services.

Deployment Risks Specific to This Size Band

For a firm with 5,000+ employees, change management is the paramount risk. Rolling out AI tools requires convincing seasoned partners and managers—whose expertise is built on traditional methods—to trust and adopt new systems. A clear communication strategy and demonstrating quick wins are essential. Data governance is another critical challenge; client data is often siloed within engagement teams and may be in inconsistent formats. Establishing a centralized data strategy with strong security and privacy controls is a prerequisite for scalable AI. Finally, there is regulatory and liability risk. The firm must ensure AI-assisted conclusions, especially in audit opinions, are explainable and defensible, maintaining strict adherence to AICPA and PCAOB standards. A phased, pilot-based approach, starting with lower-risk internal or advisory applications, is the most prudent path to mitigate these risks while building institutional knowledge.