AuditDashboard, a provider of client engagement management technology, launched AI Connectors, which give accounting firms the ability to connect Claude, ChatGPT, or Microsoft Copilot directly to their engagements so agents can flag missing, incorrect, or inconsistent evidence; follow up with clients; and use PBC files while drafting working papers.
Built on the Model Context Protocol (MCP), an open standard for securely connecting AI models to software, AI Connectors let firms’ AI agents read from and write to their AuditDashboard engagements.
The following are examples of what users are doing with their AI tool of choice, with the AuditDashboard connection enabled:
- Account admin: Add client companies and invite or deactivate users.
- Engagement setup: Create or roll forward engagements and assign teams.
- Overview: Summarize portfolio status, performance, and identify engagements at risk.
- Evidence review: Flag missing, incorrect, or internally inconsistent evidence.
- Client follow-up: Draft follow-up questions and requests for clients.
- Fieldwork: Pull populations, select and upload samples, and draft working papers for auditor review using PBC files.
“Firms don’t want another AI tool,” Dave Mundy, founder and CEO of AuditDashboard, said in a statement. “What they want is a secure AI connection to the tool they already use. Most accounting firms are focused on harnessing the power of Claude, ChatGPT, and Microsoft Copilot, so we built AuditDashboard’s AI Connectors to point to the actual engagement and PBC data. That’s the difference between an AI experiment and a connected AI workflow.”
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The AI Connectors are built on AuditDashboard’s role-based architecture. Users sign in via OAuth with their existing AuditDashboard credentials, and agents can only see and do what their role already allows. This control is enhanced by an AI client’s fine-grained permissions, which specify what agents can read, write, and execute. AuditDashboard doesn’t use firm data to train AI models. How the AI handles data is governed by the firm’s agreement with its AI provider, the company says. Every action is logged in the audit trail and visible in engagement activity feeds.
“Getting started is easy because firms are enabling the connectors in AI tools that their IT teams have already approved,” Mundy said. “User roles and permissions don’t change. The AI can’t see anything you can’t see. The auditor still owns the judgment, review, and quality of the work.”
Why should this matter to accounting firms? AuditDashboard says, “First, it improves the quality of the output. An AI model working from manually exported files has limited context. An AI model connected to the engagement can work with the request list, statuses, history, and PBC files as they currently stand, improving the quality of everything it drafts.
“Second, it helps firms maximize return on their AI investments by enabling teams to move beyond general-purpose prompting and build repeatable use cases around real jobs to be done. Practical use cases can be realized when AI is connected to where the work is happening, rather than treating it as a separate destination.
“Third, it protects the firm’s flexibility. The AI landscape is changing quickly. An open, standardized connection to engagement and PBC data enables firms to adopt better models as they emerge without rebuilding their entire technology stack or renegotiating with a vendor that controls the connection.”
AuditDashboard’s AI Connectors are immediately available for customers. More information can be found here.
Photo caption: AuditDashboard Founder and CEO Dave Mundy
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