Digital collaboration
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September 17, 2026
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How consultants can use Mural AI to improve client work

Use AI to streamline workshops, organize insights, and deliver results

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Consultants can use Mural AI to organize client insights, generate ideas and visual artifacts, summarize discussions, explore processes and scenarios, and turn collaborative work into clearer recommendations and next steps.

A single engagement may involve stakeholder interviews, client workshops, research synthesis, process analysis, strategy development, and a final set of recommendations. Moving between those stages often creates its own workload. Notes need to be organized. Workshop output needs to be synthesized, and ideas need to become plans people can understand and act on.

AI can reduce some of that work without taking judgment away from the consultant or client. The strongest use cases make complex information easier to structure, examine, and develop together.

With Mural AI for collaborative consulting work, consultants can keep client input, frameworks, AI-supported work, and decisions together on a shared visual canvas. The work does not have to move from a standalone AI tool into a separate collaboration space before the team can use it.

For teams that facilitate workshops, solve complex problems, and develop recommendations with clients, Mural for consultants provides a visual workspace for moving from discovery to action.

How Mural AI supports consulting workflows

Mural AI supports consulting workflows by helping consultants organize client input, generate ideas and visual artifacts, summarize discussions, explore possible approaches, and turn collaborative work into clear next steps.

Consultants can use AI across activities such as:

  • Organizing client research and workshop input
  • Generating ideas, questions, and hypotheses
  • Creating diagrams, mind maps, and other visual starting points
  • Summarizing complex discussions
  • Exploring processes, scenarios, and relationships
  • Turning working-session output into recommendations and next steps

Mural AI supports different ways consulting work begins and evolves on the canvas. Consultants can generate ideas, flow charts, and mind maps through guided creation flows, while Mural Compose turns meeting context into shared visual artifacts teams can keep working with. The Mural MCP Server brings AI agents into the same workflow, allowing MCP-compatible agents to read from and write to the canvas using context from connected tools.

Across these use cases, AI handles more of the creation and organization work while consultants and clients remain responsible for interpretation, judgment, and decisions.

Use Mural AI to support client discovery and proposal development

Mural AI can support client discovery and proposal development by helping consultants organize discovery notes, identify themes, generate follow-up questions, clarify goals and challenges, and turn early findings into a structured starting point for recommendations.

Discovery often produces a mix of stakeholder perspectives, customer needs, operational constraints, assumptions, and unresolved questions. The challenge is deciding what the information suggests about the client’s priorities and where the engagement should focus.

A shared visual workspace makes those connections easier to examine. Consultants can bring notes and observations into Mural, then use AI-supported creation to structure the material or explore relationships between ideas.

After an initial discovery session, a consultant might use Mural AI to:

  • Generate follow-up questions around unresolved issues
  • Build a mind map connecting goals, challenges, and dependencies
  • Organize observations into a visual framework
  • Develop hypotheses to test in later stakeholder conversations
  • Shape emerging themes into inputs for a proposal

Those outputs give the consultant a stronger starting point, but they do not determine the recommendation. The consultant still assesses which themes are meaningful, which assumptions need validation, and which problems deserve attention.

AI-assisted client discovery can shorten the distance between gathering information and turning it into a credible engagement plan.

Facilitate more effective client workshops

Consultants can use Mural AI before, during, and after client workshops to prepare prompts, generate visual starting points, expand ideas, organize contributions, capture themes, and turn the session into clear decisions and next steps.

Before a workshop, consultants can use AI to create a starting structure instead of building every artifact manually. A mind map, flow chart, or set of ideas can give participants something concrete to react to from the beginning.

During the session, participants can work directly with those artifacts, adding context, challenging assumptions, reorganizing ideas, and developing the work together rather than treating the AI-generated output as finished.

For an ideation session, a consultant might combine Mural AI with the brainstorm and idea prioritization template. AI-generated ideas can widen the field of possibilities, while the consultant guides the group through discussion, evaluation, and prioritization.

After the session, the work shifts from generating input to making sense of it. Consultants can organize the output into themes, decisions, and next steps.

AI for client workshops works best when it reduces preparation and synthesis overhead and leaves more room for the consultant to guide the discussion.

Analyze complex client problems and customer insights

Mural AI can help consultants analyze complex client problems by organizing input, summarizing discussions, creating visual structures, and making themes, relationships, root causes, and customer pain points easier to examine with stakeholders.

The evidence behind a client problem is often scattered across interviews, workshop notes, customer feedback, research, and competing stakeholder perspectives. Putting that information into a shared visual structure can expose connections that are harder to see in separate documents.

For competitive analysis, consultants can use a competitive analysis template to bring observations about several competitors into one view. AI-supported synthesis can help structure those inputs before the team compares positioning, strengths, weaknesses, and opportunities.

For root-cause analysis, a problem tree analysis can separate a visible issue from the factors contributing to it and the downstream effects it creates. AI can help organize the observations, while the consultant and client test which relationships hold up and which need more evidence.

For customer experience work, a customer journey map can connect feedback to specific stages of the journey. Consultants can then compare pain points, recurring themes, and possible areas for improvement in one shared view.

AI-assisted client insight synthesis is most useful when it gets raw information into a form people can work with. Once the material is visible, consultants and clients can question the patterns, compare perspectives, and decide which findings should shape the recommendation.

Develop strategy roadmaps and explore scenarios

Mural AI can support strategy development by helping consultants generate and refine strategic ideas, visualize relationships between initiatives, explore scenarios, compare options, and turn workshop findings into structured priorities and next steps.

Strategy work depends on choices. Research may point to several possible directions, but the consultant and client still need to understand the assumptions, dependencies, tradeoffs, and risks behind each one.

Mural AI can help create the structures used to examine those choices. A mind map can show relationships between objectives and initiatives. A flow chart can make dependencies visible. Generated ideas can introduce additional approaches for the team to evaluate.

Scenario planning gives consultants another way to test a recommendation before committing to it.

Using a scenario map, consultants can explore how a proposed strategy might change if customer demand shifts, resources tighten, a dependency fails, or a key assumption proves wrong.

Once a direction is selected, the same canvas can support the move into planning by organizing goals, initiatives, priorities, dependencies, and next steps.

Map processes and find opportunities to improve them

Mural AI can support process mapping by turning descriptions into editable flow charts, organizing observations about an existing workflow, and giving consultants and clients a visual starting point for identifying bottlenecks, redundancies, and improvement opportunities.

A process flowchart can document how work moves between people, teams, and systems. Stakeholders can then add the exceptions, workarounds, delays, and handoffs that formal process documentation often leaves out.

The AI Creation Hub can accelerate the first draft by generating a flow chart directly on the canvas from a description of the process. Because the result remains editable, consultants can validate it with the people who know the workflow and correct it as new information emerges.

From there, the team can examine questions such as:

  • Where does work repeatedly slow down?
  • Which steps are duplicated?
  • Where are decision points unclear?
  • Which handoffs create unnecessary friction?
  • Which dependencies create risk?
  • What could be simplified in the future-state process?

A workflow diagram provides a framework for designing an improved process once the current state is understood.

AI for process mapping reduces the effort required to create and revise the visual model. The consultant and client still determine what the model reveals and which changes are worth making.

Turn collaborative work into clear client deliverables

Mural AI can help consultants turn collaborative work into client deliverables by organizing recommendations, clarifying decisions, structuring next steps, and keeping the context behind those outputs connected to the work that produced them.

A client deliverable should not require the consultant to reconstruct an engagement from workshop screenshots, transcripts, scattered notes, and separate documents.

When research, diagrams, workshop output, decisions, and planning artifacts stay together on the Mural canvas, the path from working session to recommendation becomes easier to follow.

Consultants can use that shared context to synthesize:

  • Key findings
  • Recommended actions
  • Strategic priorities
  • Decision rationales
  • Owners and next steps
  • Roadmaps or implementation plans

AI can accelerate the organization of that material. The consultant still decides what belongs in the final recommendation, how strongly the evidence supports it, and how it should be communicated to the client.

The Mural MCP Server can also connect the collaborative work in Mural with tools where execution continues. An MCP-compatible AI agent can read what is on the canvas and work with other connected systems.

After a planning session, for example, an agent could work from decisions or action items captured in Mural and use its connected tools to continue the workflow.

That reduces the amount of context that has to be recreated when the work moves from collaboration into execution.

Why consultants use Mural AI in a visual workspace

Consultants use Mural AI in a visual workspace because client work depends on shared understanding. Insights, AI-generated outputs, decisions, and recommendations need to be visible and editable by the people responsible for evaluating them.

Standalone AI tools can be useful for individual drafting, research, or analysis. Their output still has to enter the client conversation before it can influence a decision.

Mural keeps that work on the shared canvas.

Stakeholders can correct a generated flow chart when it misses part of the process. A team can reorganize a mind map as the strategy changes. Meeting context can become a visual artifact people annotate and develop together. An AI agent can contribute to the same collaborative space instead of handing back an isolated result.

The progression stays connected from one stage of the engagement to the next. Client input becomes shared context. Shared context supports decisions. Decisions become recommendations and next steps.

The consultant continues to own the work that requires judgment, including framing the problem, evaluating evidence, facilitating difficult conversations, assessing tradeoffs, and making credible recommendations.

Explore Mural AI or learn more about Mural for consultants.

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FAQs

How can consultants use Mural AI?

Consultants can use Mural AI for client discovery, workshops, insight synthesis, strategy development, process mapping, and deliverables. It can organize information, generate visual starting points, explore ideas and scenarios, and turn collaborative work into clearer recommendations and next steps.

What can Mural AI do for client workshops?

Mural AI can support client workshops by helping consultants prepare prompts and visual starting points, generate and expand ideas, organize workshop input, and turn session output into clearer themes and next steps. Because the work stays on the shared canvas, participants can review and refine it together.

How does Mural AI help consultants organize client insights?

Mural AI can help consultants structure research, workshop input, and stakeholder observations into visual artifacts that are easier to examine. Consultants and clients can then use those shared views to identify themes, compare perspectives, explore relationships, and decide which insights should influence recommendations.

Can Mural AI help consultants develop strategy roadmaps?

Yes. Mural AI can help consultants generate strategic options, visualize relationships and dependencies, explore scenarios, and create starting structures for planning. Consultants and clients can then refine those artifacts into priorities, initiatives, roadmaps, and next steps.

How does Mural AI support consulting teams?

Mural AI supports consulting teams by keeping AI-assisted work inside the same visual workspace where consultants and clients collaborate. That makes it easier to move from discovery and workshops to analysis, decisions, recommendations, and delivery without separating AI output from the people and context needed to evaluate it.

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