Workflows and integrations
Seven AI Workflows for Manual Handoffs
Seven handoffs to evaluate for AI assistance, with clear inputs, permissions, review steps, and a responsible human owner.
By RUDI · Published
Updated
Define the handoff before connecting the tools.
A meeting ends, but its actions never reach the task list. A signed agreement arrives, but someone still has to create the onboarding project. AI can help interpret the source material at these handoffs. The surrounding workflow still needs to identify the right record, control access, and verify what was written.
The seven examples below are design patterns to evaluate, not ready-made integrations or claims about particular vendors. Availability depends on the host application, connector, account plan, permissions, and actions exposed by each service. Some implementations require engineering support.
What MCP provides
The Model Context Protocol architecture defines how an AI application connects through clients to servers that expose resources, prompts, and tools. A server can make a service’s information or actions available to the application. MCP is one integration route; native connectors, APIs, and existing automation platforms may also fit the job.
A connection does not by itself create an unattended workflow. A scheduler or event system may need to start the work; the implementation must manage authorization, retries, and records of completed actions. A read-only connector cannot create a task merely because the model proposes one.
The MCP tools specification calls for visibility and human control over tool use. Retrieved text and tool descriptions should not be treated as authorization. Define which actions are permitted, which require approval, and who can stop the workflow.
Seven handoffs to evaluate
Start each with a draft or review queue. The responsible human owner decides whether the evidence supports further automation.
Meeting → action list
Read an approved transcript and propose tasks with links to the relevant passages. Preserve stated owners and dates; mark missing ones as unresolved. The meeting owner confirms the assignments before tasks are created. Check recording permissions and who may see the transcript.
Email → CRM update
Summarize a permitted thread and propose an activity note against a verified contact or deal. The account owner checks the match and any suggested stage change. An ambiguous reply should remain a question, rather than silently becoming a sales commitment.
Payment → reconciliation queue
Match a payment event to existing customer, invoice, and transaction records. Use established accounting rules for posting; AI can help describe an exception for review. A finance owner checks unmatched or conflicting records. Prevent a repeated event from creating a duplicate entry.
Alert → incident briefing
Gather approved monitoring signals, recent changes, and source links into a time-stamped briefing. Separate observed facts from suggested causes. The on-call owner decides the response. Keep the existing alert path working if the AI summary fails or arrives late.
Signed agreement → onboarding draft
Extract stated deliverables, dates, and contacts into a project template. Link each commitment to its source and flag missing or conflicting terms. The delivery owner reviews the draft before assigning work or notifying a customer.
Prospect research → outreach draft
Use authorized research sources to prepare a draft with traceable company facts. Avoid inventing a personal connection or inferring sensitive traits. The sender checks relevance, accuracy, and applicable outreach requirements before sending. A research connection does not authorize scraping or bulk messages.
New document → knowledge entry
Summarize a permitted document, preserve its source link and date, and propose tags. The knowledge owner checks accuracy and the destination’s audience. A summary must not expose restricted material to people who cannot access the original. Plan updates when the source changes or is removed.
Test the whole handoff.
Use a small set of permitted examples that includes an ambiguous input, missing information, a duplicate event, and a destination that cannot be reached. Check whether a failed write is visible and whether retrying creates duplicate work. Record what was proposed, approved, and completed without copying unnecessary sensitive content into logs.
Keep an existing manual route available during the pilot. If a tool times out after a write, verify the destination before retrying. If source material conflicts, send the case to the owner. The workflow should explain its status clearly enough for someone to recover it.
Measure time saved after review and correction, completion accuracy, and operating cost. These measures help distinguish a useful integration from one that moves clerical work into a harder-to-see review queue.
Assign ownership before expanding.
Use Compliance, Competency, Cost to plan the pilot: agree on data and action rules, train people to inspect results and handle exceptions, and fund integration maintenance alongside model and application usage.
Every AI workflow has a responsible human owner, including one that runs unattended. That owner needs access to its records, authority to stop it, and a process for changing permissions. Review the workflow again when a provider changes its tools or data handling.
Continue with the three Cs of adoption, the RESPECT framework, or practice and coaching for faculty and staff.