AI Opportunity Assessment

AI Opportunity for Berdon: Driving Operational Efficiency in New York Accounting

AI agent deployments can significantly enhance operational efficiency for accounting firms like Berdon. By automating routine tasks, improving data processing, and streamlining client communications, AI agents empower staff to focus on higher-value advisory services and strategic client engagement.

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20-30%

Reduction in time spent on manual data entry

Industry Accounting Benchmarks

10-15%

Improvement in audit accuracy

Global Audit Technology Reports

2-4 weeks

Faster tax return processing times

Tax Automation Studies

3-5x

Increase in client query resolution speed

Customer Service AI Benchmarks

Why now

Why accounting operators in New York are moving on AI

In New York City's competitive accounting landscape, firms like Berdon face mounting pressure to enhance efficiency and client service as AI adoption accelerates across the professional services sector.

The Staffing Math Facing New York City Accounting Firms

Accounting firms in New York City, particularly those with 300-400 employees like Berdon, are navigating significant labor cost inflation. Industry benchmarks indicate that labor represents 50-65% of total operating expenses for mid-size accounting practices, according to recent surveys by the AICPA. The ongoing competition for skilled tax and audit professionals has driven salary expectations upward, with some specialized roles seeing 10-15% annual increases in compensation, per data from Robert Half. This makes efficient resource allocation and automation of routine tasks critical for maintaining profitability, especially when considering the average revenue per employee benchmark, which typically falls between $150,000-$220,000 for firms of this size.

AI Adoption Pressures in the New York Professional Services Market

Competitors and adjacent professional services firms, including large law firms and wealth management groups in the New York metropolitan area, are increasingly integrating AI for operational lift. Early adopters are reporting 15-25% reductions in processing time for document review and data entry tasks, according to a 2024 study by Deloitte on AI in professional services. Firms that delay AI integration risk falling behind in service delivery speed and cost-competitiveness. This trend is particularly acute in New York, where market expectations for responsiveness and data-driven insights are exceptionally high. The imperative to adopt AI is no longer a future consideration but a present necessity to maintain market share against more technologically advanced peers.

Navigating Market Consolidation in New York Accounting

The accounting industry, much like the adjacent tax preparation and business advisory segments, is experiencing a wave of consolidation. Larger firms and private equity-backed consolidators are acquiring smaller and mid-sized practices, often leveraging technology to achieve economies of scale. This PE roll-up activity is reshaping the competitive landscape across New York State. For firms like Berdon, staying competitive means demonstrating superior operational efficiency and specialized service offerings that differentiate them from larger, consolidated entities. Benchmarks suggest that firms with higher profit margins, often 20-30%, are better positioned to either acquire or resist acquisition, and operational efficiency driven by technology is a key lever for margin improvement. Peers in this segment are exploring AI to automate compliance work and enhance client reporting, thereby freeing up high-value staff for strategic advisory roles.

Evolving Client Expectations and Regulatory Demands in Accounting

Clients in New York and across the nation now expect more proactive, data-driven insights and faster turnaround times, driven by the digital transformation in other sectors. Simultaneously, regulatory compliance requirements continue to grow in complexity. AI-powered agents can significantly improve the accuracy and speed of tax compliance and audit procedures, reducing the risk of errors and penalties, which can often run into tens of thousands of dollars for significant oversights. Furthermore, AI can enhance client communication by providing instant answers to common queries and personalized financial updates, improving overall client satisfaction scores. Industry reports from Gartner indicate that businesses leveraging AI for client-facing interactions see up to a 10% improvement in client retention rates.

Berdon at a glance

What we know about Berdon

What they do

Berdon LLP is a full-service accounting, tax, and advisory firm based in New York, established in 1917. The firm has a long history of serving high-profile clients with a focus on a collaborative approach that integrates accounting, tax, and business expertise. Berdon has grown through various economic challenges and has diversified its services across multiple sectors, including law, entertainment, and construction. The firm offers a wide range of services tailored to clients at all stages of growth. These include assurance and accounting, tax services, and specialized advisory services such as trust and estate planning, business valuation, and digital asset advisory. Berdon emphasizes innovative solutions and industry-focused support, catering to clients in real estate, manufacturing, retail, and professional services. With a team of around 420-528 professionals, Berdon is recognized among the top accounting firms in the U.S.

Where they operate

New York, New York

Size profile

regional multi-site

AI opportunities

6 agent deployments worth exploring for Berdon

Automated Client Document Ingestion and Classification

Accounting firms handle vast volumes of client documents daily, including financial statements, tax forms, and supporting schedules. Manual sorting and classification are time-consuming and prone to error, delaying client onboarding and tax preparation cycles. AI agents can rapidly process these documents, extract key data, and categorize them accurately, improving workflow efficiency.

Up to 30% reduction in manual data entry time— Industry benchmarks for document processing automation

An AI agent that monitors client-provided document repositories (e.g., secure portals, email attachments). It identifies document types, extracts relevant financial data points, and automatically files them into client-specific digital folders, flagging any anomalies or missing information for human review.

AI-Powered Tax Research and Compliance Assistance

Tax laws and regulations are complex and constantly evolving. Accountants must stay abreast of changes to ensure accurate filings and provide timely advice. Performing comprehensive tax research manually is a significant drain on billable hours. AI agents can quickly scan and summarize relevant tax codes, rulings, and case law.

10-20% faster research cycles for complex tax queries— Surveys of tax and accounting professionals

An AI agent that acts as an intelligent research assistant. It can answer specific tax-related questions by querying vast databases of tax legislation, IRS publications, and court decisions, providing concise summaries and links to authoritative sources.

Automated Audit Evidence Gathering and Analysis

Auditing requires extensive collection and analysis of financial data and supporting documentation from clients. This process is often manual, iterative, and requires significant staff time. AI agents can automate the request and collection of certain documents and perform initial analysis to identify potential risks or discrepancies.

15-25% improvement in audit efficiency for routine tasks— Accounting industry reports on audit automation

An AI agent that interacts with client systems or portals to request specific financial data and documents. It can perform preliminary checks for completeness, consistency, and flag unusual transactions or patterns for auditor review, streamlining the evidence gathering phase.

Client Query Triage and Response Augmentation

Accounting firms receive numerous client inquiries via email and phone, ranging from simple status updates to complex accounting questions. Staff spend considerable time responding to common queries, taking away from higher-value advisory work. AI agents can handle initial triage and provide draft responses for routine questions.

20-35% reduction in response time for common client queries— Customer service benchmarks for professional services

An AI agent that monitors client communication channels. It can categorize incoming queries by complexity and topic, provide instant answers to frequently asked questions, and draft responses for more complex inquiries based on firm knowledge bases, which are then reviewed by staff.

Internal Knowledge Management and Best Practice Dissemination

With a large staff, ensuring consistent application of firm methodologies, accounting standards, and best practices is challenging. Accessing relevant internal guidance or past project insights can be difficult. AI agents can create a searchable, intelligent repository of internal knowledge.

10-15% increase in staff efficiency through faster knowledge retrieval— Internal process improvement studies in professional services

An AI agent that indexes internal firm documents, training materials, and past project files. It allows staff to ask natural language questions about firm policies, technical accounting issues, or industry-specific considerations and receive accurate, context-aware answers drawn from the firm's collective knowledge.

Automated Engagement Letter Generation and Management

Creating and managing engagement letters for a diverse client base is a repetitive administrative task. Ensuring all necessary clauses are included and that letters are tracked for signing and filing consumes valuable administrative and professional time. AI can streamline this process.

25-40% reduction in time spent on engagement letter administration— Operational efficiency studies in professional services firms

An AI agent that generates draft engagement letters based on client type, service scope, and firm templates. It can track the status of sent letters, send automated reminders for signatures, and file executed copies, reducing manual oversight.

Frequently asked

Common questions about AI for accounting

What tasks can AI agents automate for accounting firms like Berdon?

AI agents can automate routine, data-intensive tasks such as data entry, document classification, initial review of financial statements, reconciliation of accounts, and preparation of standard reports. They can also assist with client onboarding by gathering and verifying information, and streamline internal processes like expense report processing and vendor invoice management. This frees up human staff for higher-value advisory and client service roles.

How do AI agents ensure data security and compliance in accounting?

Reputable AI solutions are designed with robust security protocols, including data encryption, access controls, and audit trails, meeting industry standards like SOC 2. For accounting, AI agents can be configured to adhere to strict data privacy regulations (e.g., GDPR, CCPA) and professional standards. Compliance is maintained through careful configuration, regular security audits, and ensuring the AI operates within defined parameters, often with human oversight for critical decisions.

What is the typical timeline for deploying AI agents in an accounting practice?

Deployment timelines vary based on complexity, but initial pilot programs for specific functions, such as accounts payable or document processing, can often be launched within 2-4 months. Full-scale deployments across multiple departments might take 6-12 months. This includes phases for planning, integration, testing, training, and phased rollout to ensure smooth adoption and minimal disruption.

Are there options for piloting AI agents before a full commitment?

Yes, pilot programs are a common and recommended approach. Firms typically start with a pilot focused on a well-defined process, like automating a portion of tax document review or client communication follow-ups. This allows the firm to evaluate the AI's performance, gather user feedback, and quantify benefits before committing to a broader deployment, often lasting 1-3 months.

What data and integration capabilities are needed for AI agents?

AI agents require access to structured and unstructured data sources, including accounting software (e.g., QuickBooks, Xero, SAP), ERP systems, document management systems, and email platforms. Integration is typically achieved through APIs or secure data connectors. The quality and accessibility of data are crucial for AI performance. Firms often need to ensure data is clean, standardized, and readily available for the agents to process effectively.

How are accounting professionals trained to work with AI agents?

Training typically focuses on how to interact with the AI, interpret its outputs, and manage exceptions. This includes understanding the AI's capabilities and limitations, providing feedback for continuous improvement, and focusing on the strategic tasks that AI enables. Training sessions are often role-specific and can be delivered through online modules, workshops, and on-the-job coaching, with an emphasis on collaboration rather than replacement.

Can AI agents support multi-location accounting firms effectively?

Absolutely. AI agents are inherently scalable and can be deployed across multiple locations simultaneously. They provide consistent processing and support regardless of geographic location, helping to standardize workflows, improve communication between offices, and ensure uniform service delivery. Centralized management of AI agents also simplifies updates and maintenance for firms with distributed teams.

How do accounting firms typically measure the ROI of AI agent deployments?

Return on Investment (ROI) is commonly measured by tracking key performance indicators (KPIs) such as reduction in processing time for specific tasks, decrease in error rates, improved staff utilization, faster client response times, and increased capacity without proportional headcount growth. Firms often benchmark pre-AI deployment metrics against post-deployment results to quantify efficiency gains and cost savings.

Industry peers