As November settles in, teams naturally shift into long-view mode. It’s the season for pruning, strengthening roots, and harvesting insights from the year so we can plant smarter in the next one. That rhythm is tailor-made for the kind of thinking AI transformation actually requires—systems thinking. Because while AI can accelerate what works, it can also amplify what doesn’t. If you adopt it as a series of isolated tools, you risk scaling the very patterns you’re trying to change.

This month, we invite you to step back and see the whole. AI transformation is not a tool swap; it’s a chance to redesign roles, rituals, rules, and boundaries across your organization. When you map the system together—actors, relationships, flows, and incentives—you uncover bottlenecks before they appear, create better decision pathways, and frame experiments that compound learning rather than stall in governance fog.

Our Activity of the Month is Systems Mapping, inspired by the session Erik Skogsberg and Dirk Van Onsem led at the Facilitation Lab Summit 2024. If you’ve never mapped a system with your team, this is the perfect time to try. If you’re already mapping, this is the perfect time to revisit your map, stress-test your future state, and align on experiments that everyone can rally around.

Below, you’ll find a practical, seven-part guide to approach AI with a systems lens—complete with an activity you can run in 60–90 minutes, ways to anticipate tomorrow’s bottlenecks today, and facilitation moves that turn digital transformation teams into conveners of clarity. Let’s get you set to map before you move.

See The Whole To Change The Parts

AI adoption tends to enter organizations as a noun—a new platform, pilot, or policy. But sustainable transformation lives in the verbs—how we decide, coordinate, hand off, learn, and adapt across the system. If you focus on “the tool” you’ll optimize pockets of work. If you focus on “the work,” you’ll redesign the moves that matter most—especially the moves between people and teams where friction and value compound. Verbs over nouns is the mental shift that keeps AI from amplifying yesterday’s patterns.

That shift is only possible when you broaden your container. Instead of asking what AI can do for one role or function, ask what becomes possible across roles, rituals, rules, and boundaries. Where are decisions waiting on a single person? Which incentives reward local wins at the expense of system outcomes? Which rules were written for old constraints that no longer apply? Seeing those dynamics is what lets AI actually change the system, not just accelerate it.

It helps to imagine your organization as an ecosystem, not an org chart. Ecosystems thrive through flows—of information, decisions, value, trust. When we talk about AI adoption, we’re really talking about ecosystem gardening, not gadget shopping. It’s the work of cultivating healthy relationships, pruning outdated norms, improving the soil of incentives, and introducing new capabilities with intention.

Most important, a systems view honors human needs. Change lands well when people feel safe, skilled, and significant. If fear is present, judgment narrows and teams retreat to what they can control. That’s why a facilitative stance matters. Check-ins, working agreements, and visual artifacts create a shared field of view. They lower the waterline of uncertainty so teams can engage, learn, and own the change together.

Make It Visible Together

Systems are invisible until you draw them. The fastest way to move from assumptions to alignment is to make your work visible—actors, relationships, dependencies, decision points, and feedback loops. When it’s out on the board, you can collectively see where latency piles up, where incentives subtly pull teams apart, and where a small change could unlock major flow.

We love Miro as a base container for this work because it supports both divergence and convergence in one place. You can invite many perspectives, surface assumptions quickly, then converge on the parts that matter for your next move. With Miro’s AI features, you can even bring in an “extra lens” to help spot patterns—emerging loops, clusters, or contradictions—that the group can then interpret, validate, and refine.

A critical step is asking whose voices are missing from the container. If you’re mapping a process without someone who lives its pain points, you’ll miss essential nuance. If you’re designing decision rules without folks who actually carry them out, you’ll create elegant bottlenecks. Make your invitations explicit: who co-owns this map, what benefits and responsibilities come with participation, and how the artifact will be used beyond the workshop.

Finally, remember that maps are prototypes. The goal isn’t a perfect diagram, it’s collective insight. A good systems map gives you enough clarity to move, learn, and iterate. Hold it lightly. Update it as you test, so your shared understanding grows. When the map changes, that’s not rework; it’s progress.

Activity Of The Month: Systems Mapping

If you run just one session this month, make it a 60–90 minute systems mapping workshop. This is a practical, low-lift way to transform big conversations about AI into concrete decisions and experiments. Our facilitation team has been running versions of this for years, and the moves are straightforward to adapt to your context.

Start by clarifying purpose and boundaries. In 10 minutes, align on what system you’re mapping and where it starts and ends for this session. Then list actors—teams, roles, customers, partners, tools, policies—who impact or are impacted by this system. In the next 20–30 minutes, map flows: how work actually moves today. Surface handoffs, delays, and decisions. Highlight where information waits, where approvals stack up, and where “ghost rules” create drag.

In 20 minutes, annotate the map with friction points and incentives. Where are people rewarded for local optimization? Where are norms or policies written for constraints that no longer exist? Where does trust have to be rebuilt for a new move to stick? As you talk, capture opportunities for AI to help at the system level: better triage at handoffs, improved decision support at key thresholds, smart routing to reduce latency, or lightweight automation where waste is predictable.

Close by harvesting experiments and decision rules. Choose 2–3 experiments you can run within 30–45 days. For each, name the owner, success signal, consent threshold, and a safety check or ethical red line. Define how you’ll make the decision to scale, reverse, or sunset. This small governance layer keeps learning fast and trust high. For more background and inspiration, watch the Activity of the Month video and revisit Erik Skogsberg and Dirk Van Onsem’s 2024 Facilitation Lab Summit talk on systems mapping:

Find Tomorrow’s Bottlenecks Today

The most valuable maps don’t just describe today; they help you see around corners. As AI introduces new capabilities, bottlenecks move. You may reduce time on a task and inadvertently flood a downstream team. You may open access to information and discover that decision rights—not data—are your new constraint. Mapping lets you anticipate those shifts so you’re not surprised when your pilot meets friction.

One powerful move is to run a premortem on your future state. Sketch the improved flow you want with AI in place. Then ask, “It’s three months from now and the pilot failed—what happened?” Look specifically at four areas: data access, decision latency, policy gates, and trust. Where will approvals slow you down? Where is risk-threshold clarity missing? What new handoffs appear that weren’t there before? This is how you “pre-mortem the future” so the future doesn’t mortem your pilot.

This is also where governance benefits from a reframing. Many teams get stuck because governance shows up as a heavy brake. Try treating governance as choreography—the roles, rules, and rhythms that keep you moving responsibly. Define consent thresholds for experiments, decision rights for scaling, safety checks for sensitive data, and clear reversibility criteria so decisions can be unmade with minimal cost. When governance clarifies motion, momentum follows.

Finally, watch for latency loops that quietly drain energy. When decisions repeatedly wait on one person, consider role-based or rule-based approaches that preserve accountability without creating single points of failure. When a policy meant to protect inadvertently blocks benign learning, craft lightweight “sandbox” zones with clear boundaries. Each constraint you make explicit lowers the cognitive load on your team and raises your chance of compounding wins.

From Commanders To Conveners

Digital transformation teams are increasingly being asked to lead AI strategy and enablement. The temptation is to become the owner of the answers—publish standards, pick platforms, roll out roadmaps. But in complex environments, invitations beat mandates. The most effective transformation teams act as conveners of clarity, not commanders of compliance.

Being a convener means you design the spaces where cross-functional sensemaking happens. You set cadence, craft agendas that surface trade-offs, and make the work visible. Decision logs, journey maps, and systems maps become the living artifacts that align stories when memories diverge after the meeting. Instead of “big announcement” heroics, you build trust through reliable rituals and transparent artifacts that anyone can reference.

Co-ownership is key. Ask yourself: who needs to co-create and co-own the map for it to matter? Which leaders and operators must be present for decisions to stick? Spell out the benefits and responsibilities of participation in plain language. This sense of authorship is what turns alignment into commitment. When people see themselves in the work, they carry it forward without extra push.

This stance also transforms your messaging. Rather than “Here’s the tool we’re rolling out,” try “Here’s what we want to get better at doing together, and here are the experiments we’ll run to learn how.” Verbs over nouns. Process over prescriptions. In our experience, the more your team is asked for answers they can’t hold alone, the clearer the signal that it’s time to convene the system.

Incentives, Norms, and Skill Building

Many AI “adoptions” stall because the organization’s incentives are tuned for local optimization. A team gets rewarded for shipping more tickets, so they resist a change that would slow their queue to speed value end-to-end. Or a policy written for old constraints blocks safe experimentation under new constraints. Systems mapping helps you spot these misalignments so you can adjust rules and rewards to fit the era you’re actually in.

When you identify friction on the map, treat it as a design clue, not a personal failure. Ask, “What agreement, norm, or slight boundary change would unclog this without shifting the burden somewhere else?” That last part matters. A superficial fix often moves the problem downstream. The systems view helps you see those second- and third-order effects before you pull a lever.

Skill-building belongs inside the work, not outside of it. Instead of one-off trainings, create peer-led practice circles that meet regularly. Turn early adopters into coaches without anointing them gatekeepers by pairing them with peers and rotating roles. Use check-ins to surface where people feel unsafe or unskilled, then scaffold practice moves into your routines. When people feel safe, skilled, and significant, they try new things. That’s the engine of transformation.

Finally, clarify decision-making patterns so experiments don’t stall. Define when consent is sufficient, when advice is required, and when a higher threshold is needed. Make decisions visible and, where possible, reversible. The goal is not reckless speed; it’s responsible velocity—the discipline to go fast where it’s safe and slow where it’s wise, with clarity everyone can trust.

Cadence, Artifacts, and the Power of Visible Agreements

Cadence builds trust. Sporadic heroics and big-bang announcements breed resistance; steady, predictable rhythms build reliability. Think weekly mapping huddles, biweekly experiment reviews, and monthly retros that refine working agreements. This isn’t ceremony for ceremony’s sake. It’s the social choreography that turns insight into practice and practice into capability.

Artifacts align stories when memories diverge. After a workshop, each person carries a slightly different recollection of what was decided. A living map, a simple decision log, and a one-page experiment sheet reduce rework and confusion. Ask, “Which artifact would most reduce rework this month?” Then keep it live—visible, updated, and used—rather than letting it become a static prop.

Co-own your artifacts to strengthen buy-in. If the transformation team is the sole author, artifacts can feel like compliance documents. When leaders and operators co-create, artifacts become references people trust. Make sure each artifact lives where the work lives, not tucked into an obscure folder. Visibility is an invitation.

And let’s talk cadence that sustains momentum without fatigue. Use check-ins to tune pace and focus. If your rituals are creating drag, prune them. If they’re building clarity and confidence, strengthen the roots. This is the season to ask: what cadence serves our goals, and what can we let go of to protect energy and attention for the work that matters most?

November Harvest and Your Next Move

November is a natural time to harvest insights and prune scope so new growth can thrive. Look across your meetings, decision rules, and flows. What will you sunset to make space for better practices? Which rules were written for constraints that AI has lifted? Which norms reward silo wins over system outcomes? Retire rituals gracefully. Name what you’re letting go of and why. That story helps people release the old to welcome the new.

Use your map to make smart trade-offs explicit. When you reduce scope, show the dependencies you’re preserving and the risks you’re accepting. When you create a sandbox for safe learning, document the boundaries and the reversibility. Transparency compounds trust. The more clearly you visualize trade-offs, the more confidently your team can move.

As you look ahead, ask a few focusing questions: What cadence will sustain momentum without fatigue? Where are skills uneven across roles, and how might peer-led practice close the gap without creating gatekeepers? How will we connect AI use cases to our purpose and values so participants carry a clear story back to their teams? Those stories are how change scales.

Call to action: Run a 60–90 minute systems mapping session before the month ends. Clarify your purpose and boundaries. List actors. Map flows, handoffs, and decision points. Identify friction and incentives. Harvest two or three experiments with clear decision rights and safety checks. Watch our Activity of the Month video to guide your session, and revisit our write-up on facilitating change by mapping systems. Then share your map and learnings with your broader org to build momentum. If you want a partner, Voltage Control can facilitate your first mapping session or coach your team to lead its own. Let’s map before we move—so your AI transformation amplifies what you value most and your system is ready for what’s next.

Resources:

Facilitating Change by Mapping Systems

Summit talk video

Activity of the Month Video Systems Mapping

Ready to convene clarity? Reach out to schedule a mapping clinic, join an upcoming facilitation certification, or bring Voltage Control in to help your digital transformation team lead with a systems lens.

The post Map Before You Move appeared first on Voltage Control.

A New Chapter in Collaboration

As Miro unveils its next chapter in collaborative AI at Canvas 2025, we’re reflecting on a journey that began not with code, but with a question:

In an era when most AI tools promised to make individuals faster, we wondered how AI could make teams better. After years of running facilitation workshops around the world, one truth was clear: most innovation problems aren’t about ideas—they’re about alignment. People don’t struggle to think creatively; they struggle to think together.

That’s the problem we set out to solve. And that’s where this story begins.

The Vision Before the Tools

Back at SXSW 2025, we invited a room full of innovators, facilitators, and technologists to imagine a new kind of collaboration—one where artificial intelligence wasn’t a tool outside the circle but a teammate inside it.

Our session, AI Teammates: Facilitating Human Connection in the AI Era, wasn’t about automation or productivity hacks. It was about relationship. We staged a live experiment: participants interacted with fictional “AI teammates”—each with a personality and role to play in the group dynamic.

• There was The Challenger, who surfaced hard truths.
• The Synthesizer, who connected patterns across ideas.
• The Optimist, who expanded possibility.
• And The Historian, who anchored choices in precedent.

These personas weren’t chatbots. They were conversation archetypes designed to stretch how people think together.

As the session unfolded, something remarkable happened. The room came alive—not because of any output the “AI” produced, but because people started thinking differently about how they thought together.

When the exercise ended, one participant said, “I’ve never seen AI make a conversation feel more human.”

That comment stuck with us. It wasn’t about speed; it was about sensemaking. And yet, at the time, there was no product to make this vision tangible. It was still a simulation—a facilitation experiment about what could be.

The Moment Miro Made It Real

Fast-forward to the summer of 2025. When Miro invited us into the early beta of AI Flows and Sidekicks, we instantly recognized it as the missing bridge between concept and capability.

Here, finally, was the interface we had imagined at SXSW:
AI that could listen, synthesize, and act alongside humans, right inside the collaborative canvas.

We began experimenting in August, building facilitation patterns and testing how Miro’s new AI could support real-time group work. What we discovered was transformative.

AI Flows acted as intelligent pipelines—automating the translation of inputs (research, briefs, notes) into structured, visual outputs like user journeys, prototypes, or summaries.

AI Sidekicks took it a step further. They gave form to something we’d imagined months earlier at SXSW: AI as a teammate, not a tool. With Miro’s Sidekick framework, we could finally bring our original AI Teammate personas—The Challenger, The Synthesizer, The Optimist, The Historian—directly into the canvas as participants that offer voices often missing in the room. Whether surfacing dissent, expanding optimism, or connecting overlooked patterns, these AI teammates help facilitators create richer, more balanced conversations. What had been a facilitation exercise in Austin became an intelligent, inclusive system teams can now use in real sessions.

It was the perfect realization of our SXSW philosophy:

We brought our original AI Teammate personas—The Challenger, Synthesizer, Historian, and Optimist—into Miro as Sidekicks. We even added new ones:

• The Sketcher, who makes structure visible.
• The Co-Facilitator, who guides process and inclusion.

Each Sidekick embodied a mindset we teach in facilitation—listening deeply, synthesizing meaning, and supporting clarity.

For the first time, AI could actively participate in a team’s thinking process rather than merely executing after the fact.

Behind the Scenes: Building the Bridge

Our collaboration with Miro’s product and partner teams felt like a masterclass in co-creation. We shared prototypes, tested facilitation flows, and offered feedback on how facilitators actually use AI in live settings.

Our earliest conversations centered on one key distinction:

That question shaped our approach to every prototype.

We realized that the future of collaboration isn’t about speeding up work—it’s about amplifying shared understanding. AI should help teams see patterns sooner, articulate assumptions faster, and move forward together more confidently.

It’s not automation for automation’s sake. It’s augmentation for alignment.

Instant Prototyping: From Insight to Alignment in Minutes

To prove this approach, we built Instant Prototyping—a Miro AI Flow designed to help teams move from an opportunity to a prototype in minutes.

Instant Prototyping turns messy beginnings into momentum.
You paste your opportunity brief, add any research, and click “Run.” Within moments, the Flow generates:

1. Research Insights — a synthesized view connecting what you know.
2. User Flow — a map of how someone might engage with your solution.
3. Screen Requirements — what each step needs to deliver.
4. Prototype — a visual concept you can immediately react to.
   

The process feels facilitative: review, adjust, and re-run. Each iteration invites reflection and sharper focus. When the AI gets it wrong, that’s useful—it reveals assumptions, gaps, and preferences faster than traditional review cycles ever could.

“When the AI is wrong, it’s useful—it surfaces gaps and preferences fast, accelerating alignment.”

This pattern—speed plus direction—has become the backbone of how we help teams build clarity in real time.

Proof of Concept: Breakout Buddy

The first major product we built using Instant Prototyping was Breakout Buddy, a revolutionary Zoom facilitation app that gives hosts unprecedented control over breakout sessions.

In just a few weeks, we went from a blank canvas to a working prototype. Using AI Flows, we synthesized user research, mapped facilitator pain points, and visualized solutions—all inside Miro.

Each iteration made the design clearer. By the end of the first session, we weren’t debating what to build—we were deciding how to make it real.*

That clarity paid off. Breakout Buddy is now in review at Zoom’s marketplace, a tangible example of how facilitation-guided AI can accelerate both design and decision-making.

Instant Prototyping didn’t just make us faster; it made us truer to our facilitation roots—inviting multiple perspectives, clarifying intent, and turning conversation into shared artifacts.

Field Testing with Real Clients

Following the success of Breakout Buddy, we began testing Instant Prototyping and AI Flows with select clients in diverse industries.

• Financial Futures Planning App: A fintech startup used our Flow to translate complex customer research into clear decision journeys. Within a day, they had multiple prototype directions visualized—something that previously took weeks of back-and-forth between product and design teams.
• Local Home Services Platform: A startup supporting plumbers, electricians, and home service professionals used Instant Prototyping to map their booking experience. The team went from vague strategy discussions to a concrete, visual service flow in a single session.

These pilots validated what we believed all along:

Each engagement reaffirmed that the goal isn’t to replace human thinking—it’s to surface it faster, make it visible, and align around it collaboratively.

AI Teaming: A New Paradigm

At Voltage Control, we call this shift AI Teaming.

It’s the practice of designing relationships between humans and AI systems that are purposeful, participatory, and aligned with facilitation principles.

Most organizations treat AI as a personal productivity tool. But true transformation happens when AI becomes part of the collective intelligence of the group.

Facilitation provides the ethical and practical structure for that shift. It defines:

• How we listen to AI (and each other).
• When to pause automation for reflection.
• How to ensure every voice—including digital ones—is used responsibly.

AI Teaming is not about doing the same things faster. It’s about working differently:
more conscious, inclusive, and experimental.

“Facilitation has always been about helping groups find clarity together. Now AI can help us see that clarity forming in real time.”

AI Teaming, Not AI Tooling

There’s a quiet but crucial distinction shaping the future of work: AI tooling is about personal productivity. AI teaming is about collective intelligence.

Most organizations still think of AI as something individuals use to move faster — a personal assistant, a summarizer, a generator. Helpful, yes. But when every person uses their own AI tool in isolation, the result isn’t alignment; it’s fragmentation. Ten people might leave a meeting with ten versions of truth.

That’s why facilitation matters.

AI Teaming is built on three principles we’ve practiced for years in facilitation:

1. Inclusion: Everyone — human or machine — has a voice, but not every voice should dominate. The facilitator’s role is to balance inputs and create psychological safety for contribution.
2. Transparency: The group should always see how conclusions are reached. Hidden algorithms are the enemy of trust. That’s why we design Miro Sidekicks to work in the open — you see every prompt, every output, every change.
3. Purpose: AI should never be busywork. It exists to clarify, not to clutter. When used well, AI helps teams focus on why they’re doing something, not just how fast they can do it.

In practice, this means running meetings where AI participates visibly and democratically:

• The Synthesizer summarizes insights, and the group edits or corrects it together.
• The Challenger surfaces risk, and participants discuss trade-offs transparently.
• The Optimist explores new possibilities, and the team refines them collectively.
• The Historian recalls precedent, and the group draws lessons from what’s come before.
• The Sketcher maps structure, and the team spots patterns, gaps, and next steps.
• The Co-Facilitator proposes next moves, and the team stays aligned and engaged.

When AI joins the conversation like this, facilitation becomes the safeguard that keeps collaboration human.

We’ve seen how powerful this is in action. In workshops where we introduced Sidekicks as participants, teams reported higher engagement and greater confidence in their decisions. It’s not just that the AI saved time; it changed the tone of dialogue.

Participants started talking to each other more — not less — because they had a shared reference point to react to. That’s the paradox of AI Teaming: the more intelligence you add, the more human the process becomes.

“The future of collaboration isn’t human versus AI. It’s human with AI — guided by facilitation.”

Miro Transformation: Turning Capability into Culture

Technology adoption often fails because teams layer new tools on top of old habits.
Our Miro Transformation programs exist to prevent that.

We guide organizations through a facilitation-first approach to integrating Miro’s new AI capabilities responsibly.

• Step 1: Assess How Teams Work
  We observe how information flows, how decisions are made, and where collaboration breaks down.
• Step 2: Introduce AI Intentionally
  We co-design flows and Sidekicks that enhance—not replace—human judgment. This means creating ethical automations that preserve context, learning, and inclusivity.
• Step 3: Measure Real Value
  We focus on results that matter: shorter meetings, higher engagement, faster synthesis, and clearer outcomes.

Transformation in Action

• A global innovation team reduced alignment time by 60% by using Sidekicks like The Synthesizer and The Coach during workshops.
• A leadership group adopted AI Flows for decision documentation, cutting weekly update time in half.
• A product team transformed sprint planning from frustration to flow by running Instant Prototyping to visualize priorities on the spot.

Each story reflects the same truth: facilitation is what makes AI collaboration work—ethically, efficiently, and humanely.

Responsible AI: Designing for Trust and Inclusion

As the world rushes toward automation, facilitation is the counterbalance that keeps technology human.

In our AI Strategy Workshops, we help leaders define what responsible AI looks like in their organizations. Together, we explore questions like:

• How do we make AI reasoning transparent to the team?
• When should a facilitator—not an algorithm—make the call?
• How do we ensure that speed doesn’t silence diversity of thought?
  

Responsible AI begins with inclusion and ends with trust. It’s not a checkbox—it’s a culture.

By grounding AI use in shared principles, we ensure it supports the behaviors that make teams thrive: curiosity, dialogue, and accountability.

Product × Practice × Purpose

At Voltage Control, our partnership with Miro rests on a simple but powerful equation:

• Product gives teams intelligent scaffolding for synthesis and action.
• Practice ensures those tools are used with intention and care.
• Purpose keeps it all rooted in why we collaborate in the first place: to connect, create, and contribute meaningfully.

This triad—Product × Practice × Purpose—is the DNA of AI Teaming. It’s how we turn new technology into new ways of working.

Facilitator Reflections

When we facilitate, we tune into the subtle shift—the instant confusion gives way to clarity. You can see the spark. You can feel the room align.

Seeing that same shift occur with AI present on the canvas is extraordinary. It’s not about replacing intuition; it’s about scaling it.

Facilitators now have new instruments to play with—flows that structure conversation, Sidekicks that spark reflection, and automations that handle logistics so humans can focus on what matters most: the quality of connection.

That’s the art and science of facilitation in the AI era.

The Full-Circle Moment

From SXSW to Canvas, we’ve witnessed a transformation that began as a thought experiment and matured into a new practice of working together.

Today, every team can experience it firsthand:

• Run a Miro AI Flow to turn insights into prototypes.
• Invite AI Teammates like The Challenger or Synthesizer to expand group thinking.
• Use Utility Sidekicks to manage the board and free up human attention.

This isn’t a simulation anymore. It’s collaboration—amplified.

“AI teaming was once an idea we simulated.  Now it’s something every team can do—live, visual, and human with Miro.” —Douglas Ferguson, Founder & CEO, Voltage Control

Join the Movement

Explore how facilitation and AI come together to unlock team potential:

• Explore Voltage Control’s Miro AI Collection
• Join the Instant Prototyping Waitlist
• Discover Miro Transformation Programs
  

Because the future of collaboration isn’t about replacing people,  it’s about inviting AI in to help people work better, together.

The post AI Teaming Comes Alive on the Miro Canvas appeared first on Voltage Control.

As the air turns crisp and the nights arrive sooner, the horizon can feel a bit foggy—especially when teams are staring down big bets and competing priorities. October is a season for lanterns, and in our world of collaborative leadership and facilitation, AI Teammates are exactly that. They throw light just far enough down the path to reveal the next steps with confidence. Not because they’re perfect, but because they are tangible. A first draft beats a first debate, every time.

If you’ve felt the growing tension between moving faster and staying customer-rooted, we’ve been there too. That’s why we’ve doubled down on AI Teaming—collaborating with AI in the room so teams can shift from abstract concepts to concrete artifacts in minutes. Ambiguity becomes visible, discussable, and solvable. You see what you want—and just as often, what you don’t. Either way, you move.

This month, we’re excited to showcase how Miro’s new AI features make collaborating with AI not just possible, but exceptionally practical for facilitators and leaders. We’re Platinum Sponsors at the Miro Canvas Conference, partnering to deploy facilitator-focused product innovation tools on top of these new features. These all roll out into the Miroverse soon; for now, there’s a waitlist as Miro completes the feature release process. Consider this your early lantern beam—what’s now possible and how to harness it for your team.

In the Room

Most organizations still treat AI as an individual productivity tool—something to use before the meeting to prep and after the meeting to summarize. That’s helpful, but it also isolates the learning and amplifies misalignment. You wind up with fast individuals heading in slightly different directions, creating more fog for the group. What teams need is shared momentum, not solo velocity. Bringing AI into the meeting—live, visible, and facilitation-ready—changes everything.

We’ve been experimenting with that shift for the past year. Some of you joined us at SXSW for our AI Teammates workshop, where we introduced AI personas to enrich team conversations. We imagined what it would look like to treat AI as a dynamic teammate, contributing perspective at just the right moment. Now, with Miro AI Flows and Sidekicks, that vision is ready for prime time. You can strategically place one-click buttons on your board to generate artifacts, synthesize research, or introduce a missing viewpoint—right in front of everyone. No toggling. No mysterious magic. It’s collaborative, transparent, and grounded in your team’s context.

This is a competency-building moment for teams. Instead of optimizing individual AI hacks, codify your best prompts and patterns as Sidekicks embedded in your templates and team spaces. That builds a shared library and spreads capability beyond a few power users. You’ll see your facilitation hygiene get sharper: clearer decision rules, tighter timeboxes, faster cycles of consent-based iteration. And most importantly, you’ll collectively build the muscle of collaborating with AI, not just using it.

Think of it like this: AI Teaming speeds up the “what” and “how,” giving you back time and attention for the “who” and the “why.” In a world filled with AI fog machines, your job as facilitator is to design a container where evidence is visible, decisions are crisp, and the team experiences AI as a lantern—lighting the next few steps together.

Activity of The Month: Instant Prototyping

Our new Instant Prototyping Template is a practical example of an AI-powered flow that transforms research insights and strategic vision into tangible prototypes. In minutes, you’ve created the full stack of artifacts needed to move from hypothesis to something the team can react to.

Then the facilitation begins. We pause for structured reviews and workshopping between each step—not to slow things down, but to build confidence. The first draft is a litmus test. It’s usually wrong in useful ways, surfacing gaps in context or fuzzy assumptions that would have stayed hidden for weeks.

Two practical tips make this flow sing. First, version as you go: duplicate frames before regenerating and version-label them (e.g., Flow v1.2). Second, trace decisions back to evidence. As you review outputs, highlight where a flow step or screen requirement connects to a direct quote, a research insight, or a JTBD. Decision clarity grows when the evidence is visible and near. You move faster because you trust the direction.

Speed matters. But what matters more is direction. Instant prototypes give you both—an initial draft to react to, and a concrete way to align around user-centered evidence. You’ll move from research insights to confident product decisions faster, with less debate and more learning. When the fog is thick, create a draft and let the team see the next step together.

From Draft to Decision 

When drafts are easy to generate, the bottleneck shifts from creation to decision. That’s a good shift—as long as you’re working with clear decision rules. We encourage teams to adopt consent-based iteration in place of endless consensus-seeking. Consent asks, “Is this good enough to try for now?” rather than “Do we all love this?” It privileges learning and movement over perfect alignment – small bets beat big arguments.

Put this into practice with lightweight, recurring moves. After each auto-generated artifact, timebox a three-part review: What’s useful here? What’s missing? What will we try next? Use dot votes to prioritize the top two or three changes and capture them as prompt updates or flow adjustments. Then re-run the relevant step. If a stakeholder says, “This isn’t it,” ask them to point to the evidence and translate their feedback into a prompt tweak or a research addition. 

Facilitators, this is where your craft shines. Name the decision up front. “By the end of this session, we’ll have a directionally correct prototype of onboarding plus a short list of open questions.” Timebox the creation of first drafts via the flow, then spend your energy facilitating the review and remix moments. Keep a visible decision diary on the board to track how evidence drove changes. The more you practice this loop, the more your team’s AI competency grows—and the more everyone experiences AI as a teammate rather than a mystery box.

Case Study: Breakout Buddy

We recently used the Instant Prototyping flow to build something our community has wanted for years—a Zoom app we’re calling Breakout Buddy. Many of you have joined our Facilitation Lab Mates events where we run speed networking and match people with accountability partners. The experience is energizing, but the logistics are painful. Zoom doesn’t design breakouts the way facilitators think. There’s no drag-and-drop. Timers are limited. You select number of rooms instead of people per room. And running patterns like 1-2-4-All requires manual, error-prone steps. We had a hunch that a facilitator-first tool could change the experience.

To build it, we gathered research from community listening sessions and Huddles, collected wish lists and gripes, and wrote an Opportunity Brief that detailed use cases like speed networking, group merge and split, and easy time extensions. We dropped all of that into the board and clicked once. The first pass got plenty wrong—exactly what we needed. It misinterpreted “preformatted” in a way that wasn’t helpful and didn’t yet account for saving and recalling group configurations. Those misses illuminated what we hadn’t explicitly included. We added precise requirements, traced the needs to specific quotes, and reran the flow. Within a few hours, we had a prototype that captured the core facilitator workflows, ready for a designer to polish.

Here’s what’s inside Breakout Buddy. You can rapidly set the number of people per room, merge or split groups to run patterns like 1-2-4-All, extend time with a single click, and mark participants who shouldn’t be assigned (think observers or folks with connectivity constraints). It remembers those choices so your cognitive load drops each round. The goal is simple—free you from tedium so you can focus on relationships, process, and purpose. The app is now in Zoom’s approval pipeline. We’ll offer it free to facilitators once it’s live; newsletter readers will hear first. In the meantime, the story behind it is the point: Instant prototypes helped us get from idea to clarity to build in days, not months, and kept us anchored in real facilitator needs every step of the way.

Run Your First Instant Prototype

If you want to try this with your team, block about 90 minutes and pick a clear decision to make. Load an Opportunity Brief and your best research, then run the flow together. The first set of artifacts—Research Insights, User Flow, Screen Requirements, Prototype—will land in minutes. Don’t rush past them.

Facilitate three quick reflections: What’s useful? What’s missing? What feels ready to test? Treat each draft as a conversation starter, not a verdict. Capture insights, update prompts, and re-run the step to see what changes. Keep early versions visible so you can remix later—seeing your evolution builds confidence.

Wrap with a simple consent check: Is this good enough to try for now? Record the decision and next steps in a quick decision diary. Even one or two cycles will shorten time-to-tangible dramatically and strengthen your team’s collaboration muscles.

Advanced Moves

Once you’ve got the basics down, keep evolving your flow:

• Codify what works. Turn great prompts into shared Sidekicks so others can build on them.
• Keep evidence close. Link research and prototypes so every choice traces back to insight.
• Remix intentionally. Combine the best of multiple drafts into a stronger version.
• Slow down to learn. Instant doesn’t mean reckless—pause for reflection where it adds value.
  

The goal isn’t to automate creativity, but to amplify it. Each run builds sharper instincts and a stronger rhythm for thinking with AI, not just through it.

The Facilitation Edge

The more AI accelerates creation, the more facilitation matters. Instant prototypes don’t eliminate the need for structure; they heighten it. Without clear decision rules, timeboxes, and roles, teams will still spin—only faster. The good news is that these AI-powered flows free you from tedium so you can lean further into the work that requires human judgment and relationship-building. You’ll spend less time herding tabs and more time helping people make sense together.

Treat your board like a living workshop. Place buttons where you want to trigger generative moments. Add visible agreement frames to capture consent checks and decision diaries. Name the decisions for each session and timebox the creation. Facilitate critique as remix. When the prototype is wrong—and it will be at times—frame it as a lantern in the fog that illuminates what matters next. Mistakes become maps.

And remember, bringing AI into the meeting is the unlock for team-level competency. Individuals optimizing alone will always struggle to align. Teams practicing together can develop shared habits that stick. We’ve been revitalizing our AI Teammate personas for Sidekicks so you can easily bring missing perspectives into the room. Imagine clicking a button to hear from a skeptical CFO persona or a privacy-conscious legal voice, grounded in your actual company context. That’s not science fiction anymore. It’s simply good facilitation—expanded.

Ready to bring this magic to your team?
Join the AI Teammates waitlist for early access when it launches in the Miroverse.

The post A Lantern in the Fog appeared first on Voltage Control.

I’ve lived in Austin for 25 years, and while I haven’t immersed myself in every SXSW, I’ve managed to participate somewhat every single year I’ve been here. It’s been a big part of my Austin experience. As a musician, I’ve played official showcases, unofficial showcases and even alternative outsider festivals. As a startup founder, I’ve attended VC parties, client activations, networking events, and the beloved Fogo De Chow“meat-ups”, if you know, you know! In recent years, I have mainly been volunteering as a mentor and judge, which has been a wonderful experience in contributing to the ecosystem.

This year, Voltage Control partnered with SXSW to offer our Workshop Design process to all of their workshop facilitators, where we hosted several live sessions in January to help workshop facilitators prepare for their SXSW sessions. With the global success of our Facilitation Lab meetups we also thought it was a great opportunity to bring the meetup to SXSW as an official meetup. Then, just because we had to go all in, we ran a workshop on AI Teammates, to explore team collaboration use cases for generative AI. 

SXSW is always brimming with innovation, creativity, and connection. However, this year through our meetup and workshop we had the opportunity to observe something especially compelling—a deep yearning for genuine, meaningful human-to-human interactions amid all of the passive talks and media consumption. Both of our sessions offered rich insights and genuine connections that we felt were important to share more broadly with the community. Read on for a detailed exploration of the key topics and themes that emerged as we reflected on our SXSW activations.

Creating Meaningful Connections

Our Facilitation Lab meetup sought to elevate interaction beyond the typical exchanges of business cards and superficial networking. As attendees entered, we warmly greeted each person, handing out customized “We Connect” name tags that featured prompts like “Something that’s on my mind right now…” or “I’m curious about…” This simple yet thoughtful intervention quickly transformed initial interactions from polite small talk to engaging conversations rooted in personal interests and genuine curiosity. For instance, one participant humorously noted he spent the entire day with his prompt about ‘remaining grounded under pressure,’ sparking deeper conversations even outside the meetup context. These intentional threshold moments proved pivotal, shifting the energy in the room and setting the tone for sustained and meaningful connections throughout the event.

Erik mentioned to me that he’d forgotten to remove his name badge, and it continued sparking meaningful conversations throughout the day. Inspired by a recent coaching session on the power of silence as a facilitation tool, I chose “Silence” as my own badge prompt. Interestingly—and humorously—some attendees interpreted this as me signaling a need for quiet reflection rather than a conversation starter. Clearly, it’s worth choosing your prompt carefully!

Equally impactful were the interactive posters that posed provocative “How Might We” questions around the room. Participants eagerly engaged with these prompts, leaving behind sticky notes filled with thoughtful observations, authentic vulnerabilities, and creative ideas. These carefully structured, yet simple, tools effectively lowered conversational barriers, inviting authentic exchanges and meaningful reflections.

Notably, we observed attendees continuing their conversations long after the scheduled meetup ended, underscoring the success of our deliberate design in fostering sustained engagement. This experience reinforced for us—and hopefully our attendees—that intentional facilitation of human connection can lead to powerful, lasting interactions that extend far beyond any singular event.

Exploring Loneliness & Vulnerability

One unexpectedly resonant theme from our meetup was loneliness—a timely topic that surfaced repeatedly, even before Michelle Obama’s keynote on the subject. Participants openly shared their experiences of loneliness, highlighting its prevalence and impact across professional settings. Discussions around this theme revealed how critically loneliness intersects with facilitation, community building, and organizational leadership.

Participants emphasized the importance of creating environments where vulnerability is not only permitted but encouraged, seeing it as a catalyst for combating isolation and fostering deeper connections. Many suggested practical strategies, including dedicated moments within events for genuine personal exchange, structured affinity groups, and conscious efforts to normalize sharing vulnerabilities as part of organizational culture.

One compelling nuance that emerged in our discussions was the particular isolation facilitators often experience. While facilitators dedicate themselves to creating inclusive spaces that support and encourage vulnerability among others, attendees openly acknowledged how rarely facilitators themselves receive reciprocal support. This dynamic sparked insightful exchanges around the critical need to intentionally build community and support networks specifically for facilitators—spaces designed to nurture and sustain those whose roles inherently involve emotional labor and continuous support of others. This recognition deepened the collective understanding that addressing loneliness is not only about structured team-building but also about providing consistent, authentic support for those who hold space.

Reimagining the Art of Meetings

Meetings often carry negative connotations—viewed as tedious obligations rather than opportunities for genuine collaboration and innovation. During our meetup, attendees enthusiastically discussed ways to reinvent meetings using facilitation principles. The message was clear: stop “meeting” and start “designing collaboratively,” shifting from passive consumption of content toward active participation.

Innovative ideas emerged, including flipping traditional meeting agendas—prioritizing interactive engagement before addressing routine content—to ensure participant energy and creativity are maximized. A provocative attendee suggestion humorously yet pointedly captured this sentiment: “Any meeting over one hour is a waste of time.” This underscored a shared desire among attendees to prioritize engagement, interactivity, and co-creation in all meeting formats.

Our discussions also highlighted the necessity of making meetings purpose-driven, interactive, and intentional, transforming them from informational sessions into collaborative experiences that actively engage all participants. The clear takeaway for facilitators and business leaders is that intentionality and thoughtful design dramatically improve outcomes, making meetings more impactful and deeply satisfying for everyone involved.

Harnessing Conflict for Growth

One particularly insightful conversation during the meetup revolved around the theme of conflict—often perceived negatively but recognized here as a powerful opportunity for growth and stronger relationships. Attendees expressed the importance of normalizing conflict within teams, treating it not as a failure but as a natural byproduct of diverse perspectives working toward innovation.

To better leverage conflict, participants recommended simulating difficult conversations and scenarios proactively. Such practice not only prepares teams to handle future challenges constructively but also helps establish trust and clear boundaries around how conflicts can be handled effectively. This proactive approach allows teams to feel secure exploring differing opinions, leading to breakthroughs rather than breakdowns.

Further, principles of non-violent communication, depersonalizing disagreements, and establishing trust were frequently suggested as essential facilitation skills. This collective insight reinforced the power of intentional conflict management as a critical facilitation capability, ultimately fostering team cohesion, mutual respect, and collective resilience.

AI as a Dynamic Teammate

At our AI Teammates workshop, the conversation shifted dramatically as participants reconsidered their perceptions of AI—transforming their view from seeing it merely as a utilitarian tool to recognizing its potential as a dynamic teammate. This shift was vividly illustrated when an attendee, deeply familiar with AI in his professional life, experienced an “aha” moment, expressing excitement at recognizing AI’s fuller potential to engage and facilitate.

This cognitive shift emerged through our intentional design. We strategically used persona cards to introduce participants to new perspectives on AI, prompting deeper reflection on roles like historian, synthesizer, challenger, and optimist. Attendees discovered how leveraging AI in these roles could greatly enrich team discussions, sparking creativity and critical reflection.

A particularly powerful moment illustrating this cognitive shift occurred during our AI Teammates workshop. One attendee, who identified himself as deeply embedded professionally in AI technologies, experienced a profound “aha” moment as we explored AI’s collaborative roles. He candidly shared with the group that, despite his extensive use of AI tools, this workshop was the first time he genuinely saw AI’s deeper collaborative potential—not merely as a functional assistant but as an authentic partner in team interactions. Emotionally moved by this realization, he said the experience gave him “goosebumps,” capturing perfectly the transformative possibilities when facilitators intentionally design experiences that prompt meaningful shifts in perspective.

The workshop highlighted how AI, when positioned thoughtfully, could initiate conversations and engage team members who might otherwise hesitate to participate. In essence, AI provided a neutral voice, catalyzing richer dialogue and deeper insights. For teams hesitant about direct engagement, AI offered a safe starting point, a powerful insight into how technology can be a genuine collaborator rather than merely an information tool.

Exploring Practical Applications and Concerns with AI

Participants left our workshop inspired to experiment with new AI tools such as Claude, Perplexity, and Miro Sidekick, seeing firsthand their potential to enhance real-time facilitation. The excitement was palpable as attendees brainstormed practical uses—such as using AI to facilitate deeper reflections, structure conversations, and provide new insights during collaborative sessions.

Yet, despite widespread enthusiasm, participants also candidly discussed concerns around security, privacy, and integration of AI into organizational practices. Attendees from Germany notably highlighted slower regional adoption due to institutional hesitance and rigorous privacy standards. Addressing these concerns became a vital element of our workshop, emphasizing the importance of thoughtful, context-sensitive integration of AI into diverse organizational cultures.

Despite these valid concerns, the workshop’s overwhelming takeaway was excitement about AI’s untapped potential. Attendees saw clear opportunities to enrich their practices through these emerging technologies, feeling empowered and equipped to thoughtfully advocate for and practically implement AI as a meaningful participant in their teams and meetings.

Crossing Thresholds for Transformation

Both our meetup and workshop underscored the critical importance of thoughtfully designed thresholds—both physical entry into spaces and cognitive entry into new ideas. By consciously crafting these moments, we enabled attendees to shift from routine thinking into new possibilities, deeply enhancing their event experience.

Participants expressed gratitude for small yet impactful interventions, such as the persona cards we handed out while attendees were waiting in line for the workshop. Given the unique context of SXSW, where attendees often queue up 45 minutes or more in advance, the cards provided a delightful and unexpected moment of connection and reflection. As participants selected a card that best represented their approach or attitude toward AI, spontaneous conversations quickly blossomed among previously disconnected attendees. People eagerly compared their chosen personas—whether Historian, Synthesizer, Challenger, or Optimist—sparking curiosity, laughter, and immediate bonds. These thoughtfully designed threshold experiences didn’t just occupy waiting time; they actively reshaped the atmosphere, transitioning attendees from passive anticipation to active engagement and collaboration, dramatically influencing their openness, interactions, and reflections throughout the rest of the workshop.

And the big payoff was crossing cognitive thresholds around their use of AI demonstrated facilitation’s power to shift perspectives profoundly. Attendees repeatedly shared that thoughtfully guided experiences allowed them to see familiar tools and interactions in entirely new ways, demonstrating how effective facilitation can lead to significant shifts in understanding and collaboration practices.

Reflect, Experiment, and Engage

Our experiences at SXSW demonstrated the incredible potential at the intersection of human connection, vulnerability, thoughtful facilitation, and AI integration. These moments provided rich insights and clear evidence that intentional facilitation can profoundly reshape organizational culture and interpersonal dynamics.

We invite you—our community of facilitators, leaders, students, and alumni—to embrace and carry these insights into your own practice. Experiment boldly with facilitation techniques, reimagine your meetings for deeper impact, navigate conflict constructively, and thoughtfully explore AI as an active, engaged teammate.

Join us at our upcoming Facilitation Lab events and continue exploring these themes with us. Together, let’s facilitate spaces where human connection, innovation, and meaningful change flourish.

The post Facilitating Human Connection in the AI Era appeared first on Voltage Control.

Artificial Intelligence (AI) is revolutionizing how teams collaborate and innovate. As we move beyond viewing AI as a mere tool, the concept of treating AI as an active team member is gaining traction. This perspective shift opens up a world of possibilities for enhancing the depth and breadth of our collaborative efforts. By involving AI in brainstorming sessions, refining ideas, and generating creative stimuli, we can unlock new potentials that were previously unattainable.

In this blog post, we’ll explore how AI can be effectively integrated into facilitation processes, the benefits it brings, and practical applications that demonstrate its transformative power. From preparing AI with the right context to training teams to engage with it meaningfully, we will delve into the various aspects that make AI a valuable ally. Additionally, we’ll share insights from real-world applications, including a case study with the US SOCOM Innovation Foundry, to illustrate the practical benefits of AI in facilitation.

Rethinking AI as a Team Member

In the evolving landscape of facilitation, AI has emerged as a powerful tool. However, instead of viewing it merely as a task executor, what if we treated AI as an additional team member? Imagine having a seven-person team where an AI like ChatGPT or Claude is the eighth member. This shift in perspective can unlock new potentials in how we collaborate and innovate.

By posing the same questions to AI as we do to our human team members, we can generate a diverse range of insights. For instance, during brainstorming sessions, AI can contribute ideas that might inspire “Yes, and” thinking, akin to the dynamic flow of a collaborative team. Similarly, AI tools like Midjourney can provide visual stimuli that spur further creative exploration.

Treating AI as a collaborator enriches the facilitation process, helping us to prompt better and receive more nuanced feedback. This approach not only broadens the scope of our inquiries but also enhances the depth of our engagements, making the AI a valuable ally in our collective efforts.

Consider the implications of integrating AI into various stages of facilitation. From the initial brainstorming phase to the execution of ideas, AI can act as a catalyst for creativity and innovation. How are you currently integrating AI into your team dynamics? Share your experiences and thoughts.

Preparing AI for Collaboration

Reframing our interaction with AI from a simple input-output model to a more collaborative process can significantly enhance our facilitation outcomes. When we view AI as a collaborator, we’re encouraged to provide it with comprehensive background information and thoughtful prompts, similar to how we prepare human participants.

As facilitators, it’s crucial to equip AI with context—why we’re gathering, the tools and exercises we plan to use, and the key questions we aim to explore. This preparation allows the AI to generate responses that are more aligned with our goals and more useful to our group. For instance, if we are conducting a workshop on strategic planning, providing AI with information about the company’s vision, mission, and current challenges can lead to more relevant and insightful contributions.

Moreover, considering AI as a participant helps us think differently about its role in our workshops. Should it act as an extra person, or should every attendee have an AI copilot? These structural elements can significantly influence how effectively we harness AI’s potential during collaborative sessions. What are some ways you prepare your AI tools to be more effective collaborators? Let’s discuss.

Training Teams to Work with AI

Effective AI collaboration requires training our team members to engage with these tools meaningfully. It’s not just about using AI for tasks but understanding the difference between a transactional and a collaborative relationship with AI.

A transactional relationship focuses on simple command-response interactions, while a collaborative approach involves a deeper engagement, where AI contributions are integrated into the team’s workflow. Facilitators can guide this process by setting up scenarios where team members interact with AI in ways that build their capacity for richer engagements. For example, role-playing exercises where AI takes on different perspectives can help team members see its value beyond basic tasks.

Training our teams in this manner helps them see AI as a partner that enhances their work. Over time, this fosters a more innovative and adaptive team environment, where AI is leveraged to its full potential. This training can include workshops, hands-on practice sessions, and continuous learning opportunities to keep up with evolving AI capabilities. How have you trained your teams to work with AI? What challenges and successes have you encountered?

Enhancing Facilitation with AI

One of the most exciting aspects of integrating AI into facilitation is its ability to enhance the adaptive quality of the process. By being open to AI-generated inputs, facilitators can pivot and adapt their strategies in real-time, adding a layer of dynamism to workshops.

AI introduces a level of unpredictability that can be incredibly valuable. For example, AI might suggest an idea or perspective that wasn’t initially considered, prompting facilitators and participants to explore new avenues. This is akin to rolling dice in a game, where the outcome is not entirely predictable but can lead to interesting and productive developments.

Furthermore, AI can help facilitators manage the flow of discussions by providing real-time feedback and suggestions. This dynamic interaction can make workshops more engaging and creatively stimulating, ultimately leading to better outcomes. Integrating AI in this way can make workshops more engaging and creatively stimulating, ultimately leading to better outcomes. Have you experienced the adaptive nature of facilitation with AI? Share your stories!

Practical Applications: SOCOM Innovation Foundry

At a recent Innovation Foundry with US SOCOM, we had the opportunity to incorporate AI to elevate group outcomes. Teams used AI to generate descriptions, refine their ideas, and even challenge their concepts to strengthen them. This iterative process of using AI as a critical evaluator helped them identify weaknesses and enhance their proposals.

Additionally, AI tools like Midjourney were utilized to create compelling visuals for presentations. This not only improved the quality of their final products but also provided a unique perspective that might not have been considered otherwise.

Such practical applications highlight the potential of AI to help push the group beyond the first good idea, inspire higher quality and effectiveness of our work, making it an invaluable asset in both the ideation and execution phases.

For example, one team used AI to simulate potential market responses to their product idea, which led to significant refinements and a more robust final proposal. Another team leveraged AI to create detailed visual prototypes, making their presentations more persuasive and impactful. Have you used AI to refine your group process? How did it help? Let’s hear your experiences.

The Future of AI in Facilitation

As we look to the future, the integration of AI in facilitation is poised to become even more integral. Advances in AI technology will likely introduce more sophisticated tools and capabilities, further enhancing the ways in which we can collaborate and innovate. Staying abreast of these developments and continuously refining our approach will be key to maximizing the benefits of AI in facilitation.

Exploring new AI tools and keeping up with the latest trends can provide facilitators with a competitive edge. Embracing a mindset of continuous improvement and innovation will ensure that we are always leveraging AI to its fullest potential. The future promises exciting possibilities, from more intuitive AI interfaces to tools that can better understand and predict group dynamics.

Investing in training and development for both facilitators and team members will be crucial. As AI evolves, so too must our skills and strategies for integrating it effectively into our processes. The potential for AI to revolutionize facilitation is vast, and by staying proactive, we can continue to lead the way in collaborative innovation.

Conclusion

The integration of AI into facilitation is more than just a technological advancement; it represents a paradigm shift in how we approach collaboration and innovation. By treating AI as a team member, preparing it with relevant context, training our teams to engage with it meaningfully, and embracing its adaptive qualities, we can unlock new levels of creativity and productivity. Practical applications, like those seen with the SOCOM Innovation Foundry, demonstrate the tangible benefits of this approach.

As we continue to explore and refine our methods, the potential for AI to enhance our collaborative efforts remains vast and exciting. The future of facilitation with AI is bright, and by embracing these tools, we can drive innovation and achieve outstanding outcomes in our workshops and collaborative endeavors.

FAQ

Q: How can I start integrating AI into my facilitation processes? A: Begin by viewing AI as a team member rather than just a tool. Provide it with context and thoughtful prompts, and involve it in brainstorming sessions and idea refinement. Training your team to interact with AI meaningfully is also crucial.

Q: What are some AI tools that can be used in facilitation? A: Tools like ChatGPT and Claude can be used for generating ideas and providing feedback, while visual tools like Midjourney can help create compelling visuals for presentations. Additionally, tools like DALL-E can generate unique visual concepts that can inspire creative thinking.

Q: How do I prepare AI for collaboration? A: Equip AI with comprehensive background information about your goals, the context of your gathering, and the tools and exercises you plan to use. This helps the AI generate responses that are aligned with your objectives. Providing continuous feedback to the AI can also help refine its outputs over time.

Q: What challenges might I face when integrating AI into facilitation? A: Some challenges include ensuring team members understand how to engage with AI collaboratively rather than transactionally, and adapting to the unpredictability of AI-generated inputs. Training and practice can help overcome these challenges, as well as fostering a culture of open-mindedness and experimentation.

Q: Can AI replace human facilitators? A: AI is not a replacement for human facilitators but rather a valuable collaborator. It can enhance the facilitation process by providing diverse insights and creative stimuli, but human intuition and leadership remain essential. The human element of empathy, intuition, and nuanced understanding of group dynamics is irreplaceable and works best in tandem with AI

The post Facilitation & AI Teaming appeared first on Voltage Control.

I’m happy to share that Voltage Control and KUNGFU.AI will be hosting an AI Readiness Workshop as part of the CTO Summit this year. The workshop will take place on April 10, 2019, the day after the Summit. The AI Readiness Workshop is designed to help innovators and technology leaders focus in on how to apply artificial intelligence across the business.

About the Workshop

• An instructor-led event with activities to connect the dots between data, technology, and practical AI use cases.
• Includes a presentation by expert Ron Green on the state of AI.
• Working with peers, you’ll see how to align on a business objective, assess the state of your data, identify practical use cases, and define a starting point.
• By the end of the workshop, you will walk away with a framework and strategy document that guides internal conversations on how to apply this technology.

Who Should Attend?

• CTO/CIO/CPO/CDO/VP-level digital and technology leaders
• But, bring a few team members, as the activities are collaborative.

(Reach out to me at info@voltagecontrol.co if you can’t attend the CTO Summit and want to buy tickets to the workshop.)

By the end of this event, you will walk away with:

• Understanding key tenants of the successful AI strategies
• A strategic framework for identifying AI opportunities relevant to your business
• Methods for aligning and inspiring your team to do more with data

AI Readiness Workshop Agenda | April 10, 2019

9:30 AM: Doors Open
10:00 AM: Welcome & Intros
10:30 AM: Presentation from AI Expert Ron Green, CTO KUNGFU.AI
11:30 AM: Break
11:45 AM: AI Readiness Canvas: Explore Your Challenges
12:15 AM: AI Readiness Canvas: Articulating Your Goals
12:45 PM: Lunch
3:45 PM: AI Readiness Canvas: Data Worksheets
4:00 PM: Closing & Network

About Ron Green

Ron Green, CTO at KUNGFU.AI will kick things off with a lecture on the state of AI, explore the history of its application, and share some common themes on how it is being applied in business today.

Ron is a serial tech entrepreneur, CTO, and expert in machine learning. He’s built several successful companies in telecom, biotech, e-commerce, social media, and healthcare. He was most recently CEO and founder of Thrive Technologies (acquired by CLOUD), a mobile healthcare startup. Prior to Thrive, Ron ran software development at Ziften Technologies, Powered (acquired by Dachis Group), and Visible Genetics (acquired by Bayer). Ron holds an MSc with Distinction in Evolutionary and Adaptive Systems from the University of Sussex, and a degree in Computer Science from the University of Texas

Venue

• We will be located in the Mobility X room inside Capital Factory.
• Capital Factory is located in the Omni Hotel: 701 Brazos St, Austin, TX 78701
• Mobility X is located on the 1st floor of the Omni building. It is on the northwest corner, inside the Voltron co-working space. There will be signs and staff that can help you to the room.

Parking

The Omni has paid valet parking. There is also street parking nearby as well as lots on 8th st. and Trinity as well as 8th and Neches.

Sponsors

About the Sponsors

KUNGFU.AI helps companies start and accelerate AI programs by providing strategy and development services.

The post From AI Thinking to AI Doing: A Strategy Workshop appeared first on Voltage Control.