Review the workflow before deciding what AI should automate.

Do not automate what you do not understand.

Before a team builds an automation, creates an internal assistant, or experiments with an agent-style workflow, it needs a clear view of how the work happens today.

Where does the work start? Who owns each step? What information is used? Where do handoffs happen? Where do errors or delays appear? Which decisions require human judgment? What should be reviewed before anything is sent, filed, published, or acted on?

The AI Workflow Redesign Sprint helps teams answer those questions before deciding whether AI support belongs in the workflow.

It is a practical method for mapping current work, identifying friction, clarifying human review, and deciding whether a workflow should be improved, redesigned, supported by AI, or reviewed for automation readiness.

It does not include automation buildout, systems integration, deployment, or custom assistant development unless those items are separately scoped.

Why workflow review matters

AI can make a good workflow easier to repeat. It can also make a messy workflow faster in the wrong direction.

If the process is unclear, the data is unreliable, the handoffs are confusing, or the review points are missing, adding AI may increase risk instead of creating useful capacity.

A workflow redesign conversation helps leadership and teams slow down enough to see what is really happening.

It helps ask:

• What work is actually being done?
• Which steps are repeated often enough to matter?
• Where does friction appear?
• What information or context does the work depend on?
• Where is human judgment required?
• What should never be automated without review?
• Where might AI support be useful now?
• What needs redesign before AI or automation should be added?

This is the difference between useful AI adoption and automation theater.

What the sprint helps map

The AI Workflow Redesign Sprint may help map:

• current workflow steps;
• handoffs and ownership;
• decision points;
• friction, delays, rework, and exceptions;
• source materials and business context;
• missing instructions or unclear rules;
• human review requirements;
• output-checking needs;
• escalation paths;
• maintenance responsibilities;
• AI support opportunities;
• automation readiness questions.

The method is most useful when it focuses on a real workflow, not a broad idea like “use AI in operations” or “automate customer service.”

Speed up or redesign?

Not every workflow should be automated. Not every workflow even needs AI.

Some workflows simply need a faster draft, summary, checklist, or review routine. Others need a better process before AI should touch them. A few may be ready for automation review after the team understands the work clearly.

The sprint helps separate three different paths.

Speed up the current workflow

This may fit when the workflow is already clear, low-risk, and repetitive. AI might help with drafting, summarizing, organizing, reviewing, or preparing routine material while humans remain responsible for review and final decisions.

Redesign the workflow

This may fit when the workflow has too many handoffs, unclear ownership, missing context, repeated rework, or confusing review steps. In this case, the better first move is process improvement before automation.

Review for automation readiness

This may fit when the workflow is clear enough, the inputs are reliable enough, the human review points are known, and the organization understands what would need to be scoped, integrated, monitored, and maintained.

The goal is to choose the right path, not to force automation.

How this connects to the Governed AI Adoption Pilot

The Governed AI Adoption Pilot often surfaces workflow questions.

As participants practice AI on real work, they may identify recurring tasks, use cases, bottlenecks, or prompts that seem worth repeating. Some of those ideas may be simple enough for continued training and prompt refinement. Others may need workflow review before the organization decides whether AI support should go further.

The AI Workflow Redesign Sprint can follow a pilot when leadership needs to understand:

• which use cases are worth repeating;
• which workflows are too messy for automation;
• where guardrails need reinforcement;
• where human review is essential;
• where better context or cleaner source material is needed;
• whether an automation readiness review makes sense.

The sprint helps turn pilot observations into workflow decisions.

How this connects to AI Automations and Agents

AI Automations & Agents should usually come after readiness, training, workflow review, and guardrail clarification.

The workflow redesign sprint can help determine whether a workflow is ready for:

• simple AI-assisted support;
• a reusable prompt or knowledge asset;
• workflow redesign;
• automation readiness review;
• an internal assistant concept;
• an agent use-case brief;
• separate technical scoping.

This protects the organization from jumping straight from “AI might help here” to “build an automation” before the process is ready.

What the sprint may produce

Depending on scope, the AI Workflow Redesign Sprint may produce:

• a current-state workflow map;
• friction and bottleneck notes;
• handoff and ownership observations;
• human review points;
• context and source material gaps;
• AI support candidates;
• automation readiness notes;
• guardrail or escalation needs;
• recommended next steps;
• items to repeat, refine, pause, redesign, or scope separately.

Exact deliverables should be confirmed before the engagement begins.

What this tool does not do

The AI Workflow Redesign Sprint tool does not include by default:

• automation buildout;
• systems integration;
• deployment;
• custom GPT development;
• agent development;
• production workflow engineering;
• cybersecurity review;
• compliance review;
• privacy review;
• legal review;
• guaranteed time savings;
• guaranteed productivity gains;
• guaranteed ROI;
• guaranteed adoption success.

Those decisions require separate review and scoping.

The tool helps teams understand the workflow before deciding what should happen next.

Common signs a workflow needs review

A workflow may need redesign or deeper review when:

• nobody owns the full process;
• the work depends on scattered documents;
• the same information is entered multiple times;
• employees use different versions of the same process;
• outputs require repeated correction;
• approval steps are unclear;
• sensitive information is involved;
• the team is unsure what AI can safely use;
• automation is being discussed before human review points are clear.

These signs do not mean AI is a bad fit. They mean the workflow needs to be understood first.

Tool versus service

A service is the facilitated engagement, advisory support, training, pilot, or scoped work Sixth City AI provides.

A tool is the worksheet, diagnostic, tracker, planning aid, map, or working asset used inside that work.

The AI Workflow Redesign Sprint method is a tool. It may be used inside services such as AI Automations & Agents, AI Strategy & Advisory, AI Readiness & Context, the Governed AI Adoption Pilot, or ongoing advisory support.

The tool organizes the workflow review. The service provides facilitation, interpretation, recommendations, and next-step planning.

When this tool is useful

This tool is especially useful when:

• a pilot has surfaced several possible AI use cases;
• employees are using AI in a recurring workflow;
• leaders are considering automation;
• managers want to reduce friction or rework;
• human review points are unclear;
• workflow ownership is scattered;
• the organization is considering an internal assistant or agent concept;
• the team needs to decide whether to speed up, redesign, pause, or scope a workflow.

A practical next step

If your team is talking about automation but has not mapped the workflow, start with the workflow.

A readiness conversation, governed adoption pilot, or workflow redesign sprint can help clarify whether AI support belongs in the current process, whether the process should change first, or whether the idea needs separate technical scoping.

Review the work. Clarify the review points. Then decide what AI should and should not do.

Related tool and service links