The AI Strategic Alignment Workshop: 2-Day Format and Outcomes

Your executive team is excited about AI. Your CTO wants to start building immediately. Your CFO wants detailed ROI projections. Your Chief Legal Officer is concerned about regulatory risk. Your Chief Marketing Officer has 10 AI ideas. Your Chief Operations Officer is worried about employee displacement.

Everyone has opinions. Nobody agrees on priorities. Every meeting ends with "let's discuss this more next month."

Sound familiar?

Here's the uncomfortable truth: Most AI initiatives fail not because of technology challenges, but because of organizational misalignment. Different stakeholders have different priorities, different risk tolerances, different definitions of success, and different timelines. Without alignment, your AI strategy becomes a collection of conflicting individual agendas—not a coherent organizational capability.

According to McKinsey research, organizations that invest in strategic alignment before launching AI initiatives are 2.7x more likely to successfully deploy AI at scale. But here's what's interesting: they don't achieve alignment through endless meetings and PowerPoint decks. They use intensive, facilitated workshops that force difficult conversations, surface hidden assumptions, and drive to concrete decisions in 2 days instead of 6 months.

A well-designed AI Strategic Alignment Workshop compresses months of debate into 2 days of structured conversation that produces: shared understanding of AI opportunity, aligned priorities, clear decision rights, agreed-upon governance model, and 90-day action plan with committed owners.

Let me show you the exact 2-day workshop format that I've used with organizations to achieve executive alignment and launch successful AI programs.

Most organizations try to develop AI strategy through:

• Monthly executive committee meetings (slow, shallow discussion)
• Email chains and document reviews (no real conversation)
• Sequential one-on-one stakeholder interviews (miss the dynamics between stakeholders)
• Large group presentations (broadcast, not dialogue)

These approaches fail for AI because:

Reason 1: AI Requires Cross-Functional Decisions

Challenge: AI impacts every function—technology, operations, legal, compliance, ethics, HR, customers
Traditional approach failure: Functional leaders optimize for their own area, miss cross-functional trade-offs
Workshop advantage: All stakeholders in room together, surface and resolve trade-offs in real-time

Reason 2: AI Involves Uncertain Value and Risk

Challenge: Can't precisely predict AI ROI or risk upfront, requires judgment under uncertainty
Traditional approach failure: Analysis paralysis, endless debate about unprovable projections
Workshop advantage: Structured frameworks for making decisions despite uncertainty

Reason 3: AI Requires Shared Mental Models

Challenge: Different stakeholders have very different understanding of what AI is and isn't
Traditional approach failure: Talking past each other using same words with different meanings
Workshop advantage: Build shared vocabulary and mental models through exercises and discussion

Reason 4: AI Creates Organizational Anxieties

Challenge: AI triggers fears about job loss, changing power dynamics, loss of control
Traditional approach failure: Unstated fears sabotage explicit strategy
Workshop advantage: Safe space to surface and address anxieties directly

Reason 5: AI Demands Fast Decisions

Challenge: AI landscape changes rapidly, need to move fast
Traditional approach failure: Slow consensus-building, opportunities missed
Workshop advantage: Time-boxed process forces decisions, creates momentum

The 2-Day AI Strategic Alignment Workshop Blueprint

Pre-Workshop Preparation (2-3 Weeks Before)

Participant Selection (12-18 people):

• CEO or division president (executive sponsor)
• CFO or finance leader
• CIO/CTO or technology leader
• COO or operations leader
• Chief Legal Officer or general counsel
• CHRO or HR leader
• Chief Marketing Officer
• Chief Data/Analytics Officer (if exists)
• Chief Risk Officer or compliance leader
• 2-3 senior business unit leaders
• 1-2 technical AI experts (advisors, not decision-makers)

Pre-Work Assignments (2 hours per participant):

1. AI Opportunity Brainstorm: Each participant identifies 3-5 AI use cases for their area (template provided)
2. AI Concerns Document: Each participant lists their top 3 concerns about AI (risks, challenges, fears)
3. AI Learning: Complete 30-minute "AI for Executives" online course (ensures baseline knowledge)
4. Competitor/Industry Research: Review provided briefing on AI adoption in your industry

Facilitator Preparation:

• Review pre-work submissions
• Identify themes, conflicts, and gaps
• Prepare workshop materials (templates, frameworks, case studies)
• Set up workshop room (flip charts, sticky notes, breakout spaces)

Day 1: Understanding and Opportunity

8:00-8:30 AM: Opening and Context Setting

Facilitator Activities:

• Welcome and workshop objectives
• Ground rules (confidentiality, participation, decision-making authority)
• Current state: "Why we're here" presentation (5 minutes)
• Success definition: "What good looks like by end of Day 2"

Outcome: Aligned expectations, psychological safety established

8:30-10:00 AM: AI 101 and Shared Mental Models

Exercise 1: AI Myth-Busting (30 min)

• Present 10 common AI myths
• Participants vote True/False on each
• Facilitator reveals answers and discusses implications
• Goal: Clear misconceptions, build shared understanding

Examples:

• "AI will automate 50% of jobs in 5 years" (False - automation is gradual, augments more than replaces)
• "AI needs perfect data to work" (False - can start with imperfect data, improve over time)
• "AI projects require 2-year development timelines" (False - can deliver value in 6-12 months with right approach)

Exercise 2: AI Capability Mapping (45 min)

• Present 5 AI capability categories (prediction, personalization, automation, generation, optimization)
• For each category: explain what it does, show 2-3 industry examples
• Breakout groups: Identify 2-3 potential applications in your organization for each category
• Report back: Each group shares top ideas

Outcome: Shared vocabulary, expanded thinking about AI possibilities

10:00-10:15 AM: Break

10:15 AM-12:00 PM: Opportunity Identification and Prioritization

Exercise 3: Use Case Gallery Walk (45 min)

• All pre-work use case ideas posted on walls (30-50 ideas from participants)
• Participants walk around, read all ideas
• Each participant gets 5 votes (dot stickers) to vote for top opportunities
• Identify top 10-12 most-voted ideas for deeper analysis

Exercise 4: Use Case Deep Dive (60 min)

• Breakout groups (3-4 people each)
• Each group assigned 2-3 top-voted use cases
• Template for analysis:
  • Business value: What problem does it solve? What's the impact? ($, %, customer/employee benefit)
  • Technical feasibility: Do we have data? Is the AI capability proven? What's the complexity?
  • Organizational readiness: Who's impacted? What changes are required? What's the resistance?
  • Time to value: POC (3 months)? Pilot (6-9 months)? Production (12+ months)?
  • Risk level: Low, medium, high, critical?
• Report back: 5 minutes per group

Outcome: Top 10-12 use cases analyzed across multiple dimensions

12:00-1:00 PM: Lunch (Working Lunch with AI Case Study)

Activity:

• Watch 15-minute video case study of successful AI implementation in similar industry
• Facilitated discussion: "What can we learn? What would we do differently?"

1:00-2:30 PM: AI Maturity Assessment

Exercise 5: AI Maturity Self-Assessment (45 min)

• Present AI Maturity Model (5 levels across 6 dimensions):

  • Strategy: Ad-hoc → Defined → Aligned → Optimized → Leading
  • Data: Siloed → Accessible → Governed → Strategic Asset → Monetized
  • Technology: None → Experimenting → Platform → Scaled → Advanced
  • Talent: None → Nascent → Growing → Mature → Center of Excellence
  • Governance: None → Basic → Framework → Integrated → Proactive
  • Culture: Resistant → Curious → Adopting → AI-First → Innovation Engine

• Participants individually score organization on each dimension (1-5)

• Facilitator aggregates scores and shows results

• Discussion: Where are we? Where do we need to be? What are the gaps?

Exercise 6: Capability Gap Analysis (45 min)

• Breakout groups by dimension (Strategy, Data, Technology, Talent, Governance, Culture)
• Each group:
  • Documents current state (pain points, examples of gaps)
  • Defines target state (what "good" looks like for us)
  • Identifies top 3 actions to close gap
• Report back: 5 minutes per group

Outcome: Clear understanding of current AI maturity, priority capability gaps

2:30-2:45 PM: Break

2:45-4:30 PM: Risk and Governance Discussion

Exercise 7: AI Risk Identification (45 min)

• Review pre-work: Participants' stated concerns about AI
• Facilitator categorizes concerns into themes (typically: bias/ethics, privacy/security, regulatory compliance, job displacement, cost/ROI, vendor dependence, technical failure)
• Breakout groups by risk theme
• Each group:
  • Elaborates the risk: What could go wrong? What's the impact?
  • Assesses likelihood: Low, medium, high?
  • Proposes mitigation: How do we address this?
• Report back: 5 minutes per group

Exercise 8: Governance Model Design (60 min)

• Present 3 governance model options (centralized, federated, hybrid)
• Discuss pros/cons for your organization
• Group decision: Which model fits our culture and needs?
• Design key governance elements:
  • Decision rights: Who approves AI projects? At what threshold?
  • Risk management: How do we assess and manage AI risk?
  • Standards: What standards apply to all AI projects? (data, security, ethics, etc.)
  • Review process: How often? Who's involved?
  • Escalation: When and how to escalate AI issues?

Outcome: Agreed governance model, decision rights, and risk mitigation strategies

4:30-5:00 PM: Day 1 Synthesis and Homework

Facilitator Activities:

• Recap Day 1: What we learned, what we decided
• Preview Day 2: What we'll accomplish
• Overnight homework:
  • Review Day 1 outputs (facilitator will synthesize and send by 7 PM)
  • Reflect on: "What are our top 3 AI priorities for next 12 months?"
  • Come prepared to make decisions on Day 2

Day 2: Prioritization and Action Planning

8:00-8:15 AM: Day 1 Recap and Day 2 Preview

Facilitator Activities:

• Quick recap of Day 1 decisions
• Day 2 agenda and objectives
• Reminder: We will leave today with decisions and action plan

8:15-10:00 AM: Strategic Prioritization

Exercise 9: Portfolio Design (60 min)

• Present Portfolio Framework (Horizon 1: Quick Wins, Horizon 2: Strategic Bets, Horizon 3: Moonshots)
• Review 10-12 analyzed use cases from Day 1
• Group activity: Classify each use case into H1/H2/H3
• Discuss portfolio balance:
  • Do we have enough quick wins to build credibility?
  • Are our strategic bets aligned with business strategy?
  • Are our moonshots ambitious enough or too risky?
  • What's our budget allocation across horizons?

Exercise 10: Use Case Prioritization (45 min)

• Facilitated discussion using decision criteria:
  • Business value (high/medium/low)
  • Strategic importance (high/medium/low)
  • Technical feasibility (high/medium/low)
  • Organizational readiness (high/medium/low)
  • Time to value (fast/medium/slow)
• Participants debate and score top 10-12 use cases
• Facilitator captures scores and creates priority ranking
• Decision point: Select top 3-5 use cases to launch in next 90 days

Outcome: Prioritized portfolio of AI initiatives with clear rationale

10:00-10:15 AM: Break

10:15 AM-12:00 PM: Budget and Resourcing

Exercise 11: AI Investment Planning (60 min)

• Present typical AI investment categories:
  • Platform & Infrastructure: Cloud, ML platform, data infrastructure
  • Talent: Hiring, training, consulting
  • Projects: Use case development and deployment
  • Governance: Tools, processes, risk management
• Facilitated discussion:
  • What's our total AI investment envelope for Year 1?
  • How should we allocate across categories?
  • What's funded from central budget vs. business unit budgets?
  • What's the approval process for investments?
• Decision point: Agree on Year 1 AI budget and allocation

Exercise 12: Talent and Organization (45 min)

• Discuss organizational model options:
  • Centralized AI team (CoE)?
  • Federated (business unit teams)?
  • Hybrid?
• For selected model:
  • What roles do we need? (Data scientists, ML engineers, product managers, etc.)
  • How many people? (typical ratios: 1 data scientist per 500-1000 employees)
  • Build, buy, or partner? (hire, train existing staff, consultants, vendors?)
  • Who leads AI program? (identify candidate or agree to recruit)
• Decision point: Agree on organizational model and initial team structure

Outcome: Defined AI budget, resource allocation, and organizational approach

12:00-1:00 PM: Lunch (Working Lunch with AI Vendor Overview)

Activity:

• 15-minute presentation from pre-selected AI platform vendor (optional)
• Q&A with vendor
• Discussion: Build vs. buy considerations for our context

1:00-3:00 PM: 90-Day Action Plan Development

Exercise 13: Roadmap Creation (90 min)

• Breakout groups by workstream:

  • Use Case Delivery: How do we launch top 3-5 use cases?
  • Platform & Infrastructure: What do we need to stand up?
  • Talent & Organization: How do we build the team?
  • Governance & Risk: How do we implement governance?
  • Change & Enablement: How do we prepare the organization?

• Each group creates 90-day roadmap:

  • Weeks 1-4: What gets done? Who owns it? What's the deliverable?
  • Weeks 5-8: What gets done? Who owns it? What's the deliverable?
  • Weeks 9-12: What gets done? Who owns it? What's the deliverable?
  • Key milestones: What are the critical checkpoints?
  • Dependencies: What blocks progress? What needs to happen first?
  • Risks: What could derail us? How do we mitigate?

• Report back: 10 minutes per group

Exercise 14: Integration and Dependencies (30 min)

• Facilitator creates master 90-day Gantt chart on wall
• Identify dependencies across workstreams
• Surface conflicts and resolve scheduling
• Identify critical path (what has to happen when)
• Decision point: Approve integrated 90-day action plan

Outcome: Detailed, integrated 90-day action plan with owners and milestones

3:00-3:15 PM: Break

3:15-4:30 PM: Commitment and Governance

Exercise 15: Ownership and Accountability (45 min)

• Review all decisions from 2 days

• For each major decision/action:

  • Who's the owner (single point of accountability)?
  • Who's the sponsor (executive backing)?
  • What's the success criterion (how do we know it's done)?
  • When is it due (specific date)?
  • What support is needed (budget, people, approvals)?

• Create RACI matrix for top 10 actions:

  • Responsible (does the work)
  • Accountable (owns the outcome)
  • Consulted (provides input)
  • Informed (kept in loop)

• Decision point: Each owner publicly commits to their deliverables

Exercise 16: Governance and Communication (30 min)

• Establish ongoing governance:
  • Monthly AI Steering Committee: Who attends? What do we review? How do we make decisions?
  • Quarterly Portfolio Review: Assess progress, adjust strategy, reallocate resources
  • Communication cadence: How do we keep organization informed?
• Create communication plan:
  • Week 1: Announce AI strategy and priorities to organization
  • Week 4: Town hall on AI vision and what it means for employees
  • Monthly: AI progress updates to leadership and organization
• Decision point: Approve governance model and communication plan

Outcome: Clear ownership, accountability, and governance structure

4:30-5:00 PM: Workshop Close and Next Steps

Facilitator Activities:

• Recap all decisions made over 2 days
• Review 90-day action plan and owners
• Celebrate alignment achieved
• Distribute workshop output document (facilitator will finalize within 3 days)
• Next meeting: Schedule first monthly AI Steering Committee meeting (within 3 weeks)
• Final words from executive sponsor

Immediate Post-Workshop Actions (Facilitator):

• Day 1 (within 24 hours): Send thank-you and high-level summary
• Day 3 (within 72 hours): Deliver comprehensive workshop output document:
  • Executive summary (2 pages)
  • All exercise outputs (use cases, prioritization, maturity assessment, etc.)
  • 90-day action plan with Gantt chart
  • RACI matrix
  • Governance model
  • Communication plan
• Week 2: One-on-one check-ins with key action owners
• Week 4: First monthly steering committee meeting

Workshop Output Document Structure

The facilitator produces a comprehensive output document that serves as the AI strategy playbook:

Section 1: Executive Summary (2 pages)

• Workshop participants and dates
• Key decisions made
• Top 3-5 AI priorities
• 90-day action plan overview
• Budget commitment
• Success metrics

Section 2: AI Opportunity Analysis (10 pages)

• Full list of identified use cases (30-50 ideas)
• Deep analysis of top 10-12 use cases
• Prioritization framework and scores
• Selected portfolio (H1/H2/H3 classification)
• Rationale for priorities

Section 3: AI Maturity Assessment (5 pages)

• Current maturity scores across 6 dimensions
• Maturity heatmap visualization
• Gap analysis and target state
• Capability-building roadmap

Section 4: Risk and Governance (8 pages)

• Identified risks and mitigation strategies
• Governance model (centralized/federated/hybrid)
• Decision rights and approval thresholds
• Standards and policies
• Review and escalation processes

Section 5: Budget and Resources (5 pages)

• Year 1 AI budget and allocation
• Investment by category (platform, talent, projects, governance)
• Funding model (central vs. business unit)
• Approval process

Section 6: Organization and Talent (5 pages)

• Organizational model (CoE structure, federated teams)
• Roles and responsibilities
• Hiring plan
• Training and enablement approach

Section 7: 90-Day Action Plan (10 pages)

• Integrated Gantt chart
• Detailed actions by workstream with owners, timelines, deliverables
• Key milestones and checkpoints
• Dependencies and risks
• RACI matrix for top actions

Section 8: Governance and Communication (5 pages)

• Ongoing governance structure (steering committee, portfolio reviews)
• Meeting cadence and agendas
• Communication plan and timeline
• Success metrics and tracking

Real-World Workshop Success Story

Let me share a recent workshop I facilitated for a regional bank ($5B assets, 2,000 employees).

Context:

• CEO wanted "AI strategy" but executive team had no alignment
• CTO wanted to start building immediately
• CFO wanted business cases first
• Chief Risk Officer concerned about regulatory issues
• Business unit leaders had conflicting priorities
• Six months of meetings produced no decisions

Pre-Workshop State:

• 3 AI pilots running (no coordination, different vendors)
• No shared understanding of AI opportunity
• No governance or standards
• Decision paralysis

Workshop Execution:

Day 1 Outcomes:

• Identified 37 AI use case ideas (from all participants)
• Prioritized to top 12 for deep analysis
• AI Maturity Assessment: Scored 2.1/5 average (early stage)
• Identified 5 major capability gaps: data access, ML platform, talent, governance, change management
• Risk discussion surfaced 8 major concerns: regulatory compliance #1, followed by data privacy, bias/fairness, vendor lock-in
• Agreed on hybrid governance model (central platform + federated execution)

Day 2 Outcomes:

• Selected 4 use cases for Year 1:

  1. Fraud detection enhancement (H1: Quick Win) - 9-month timeline, $2M value
  2. Customer churn prediction (H1: Quick Win) - 6-month timeline, $1.5M value
  3. Loan underwriting automation (H2: Strategic) - 12-month timeline, $5M value, regulatory complexity
  4. Personalized financial advice (H2: Strategic) - 18-month timeline, competitive differentiator

• Budget approved: $6M Year 1 (60% H1, 30% H2, 10% infrastructure and governance)

• Organizational model: Hybrid AI CoE

  • Central team: 12 people (platform, governance, consulting)
  • Federated: 2 business unit AI teams (retail banking, commercial banking)
  • CAIO role approved (internal promotion from analytics leader)

• 90-day action plan:

  • Week 1-4: Hire CAIO, stand up cloud environment, launch fraud detection project
  • Week 5-8: Hire 4 ML engineers, deploy ML platform, launch churn prediction project
  • Week 9-12: Launch AI literacy training (500 employees), complete fraud detection POC, establish governance board

• Governance established:

  • Monthly AI Steering Committee (executive team + CAIO)
  • Quarterly portfolio reviews
  • Risk review for high-risk use cases (loan underwriting)
  • Communication plan: All-hands on Week 2, monthly updates

Post-Workshop Results (12 Months Later):

• All 4 use cases delivered on time:

  • Fraud detection: $2.3M annual value (exceeded target)
  • Churn prediction: $1.8M annual value (exceeded target)
  • Loan underwriting: Live in pilot, 40% faster decisions, regulatory approval obtained
  • Personalized advice: POC complete, pilot launching

• Business value: $8.5M delivered in Year 1 (1.4x ROI on $6M investment)

• Capability built:

  • 18-person AI CoE operational
  • ML platform deployed (AWS SageMaker)
  • 600 employees completed AI literacy training
  • Governance model operating smoothly

• Organizational transformation:

  • From 0 alignment → Full executive commitment
  • From ad-hoc pilots → Disciplined portfolio management
  • From 6 months of indecision → 90 days to first production deployment
  • From siloed efforts → Coordinated AI program

What Made It Work:

1. Time-boxed decisions: No leaving room without commitments
2. All stakeholders present: Surface and resolve conflicts in real-time
3. Structured exercises: Frameworks prevent endless debate
4. Facilitator neutrality: External facilitator (me) could push for decisions without politics
5. Executive sponsorship: CEO personally participated both days, made it clear decisions would stick
6. Follow-through: Detailed output document + ongoing governance ensured execution

Workshop Facilitation Best Practices

Practice 1: Pre-Workshop Stakeholder Alignment

Before the workshop:

• Interview executive sponsor: Understand their goals, concerns, constraints
• Interview 3-5 key stakeholders: Understand political dynamics, potential conflicts
• Identify likely points of disagreement
• Pre-socialize controversial decisions (don't surprise people in workshop)

Practice 2: Enforce Time Discipline

Time management:

• Start exactly on time (sets tone)
• End exercises when scheduled (no over-runs)
• Use timers visible to participants
• Have co-facilitator manage time while lead facilitates
• Cut off debates that aren't productive ("Let's take this offline" or "Let's vote")

Practice 3: Balance Air Time

Participation management:

• Draw out quiet participants ("Sarah, what's your perspective?")
• Politely cut off dominators ("Thanks John, let's hear from others")
• Use breakout groups to give everyone voice
• Use anonymous voting/surveys for controversial topics
• Have "parking lot" for off-topic but important discussions

Practice 4: Make Decisions Visible

Decision capture:

• Write decisions on flip charts as they're made
• Have someone photograph all flip charts (backup documentation)
• Read back decisions periodically ("Here's what we've decided so far...")
• Get explicit agreement ("Is everyone comfortable with this decision?")
• Document dissenters (if any) and their concerns

Practice 5: Manage Energy and Engagement

Energy management:

• Mix presentation, discussion, exercises, breakouts (variety)
• Take breaks exactly when scheduled (people need them)
• Use energizers after lunch (quick physical activity, icebreakers)
• Watch for disengagement (laptops open, side conversations) and address
• Celebrate progress ("We've made 5 major decisions in 3 hours—great work!")

Practice 6: Handle Conflicts Constructively

Conflict resolution:

• Name the conflict explicitly ("I'm hearing two different perspectives here...")
• Explore underlying interests ("What's important to you about this?")
• Find common ground ("Where do you agree?")
• Use data/evidence to resolve factual disputes
• Escalate to executive sponsor if needed ("CEO, we need your call on this")
• Document disagreement and decision rationale

Practice 7: Create Psychological Safety

Safety building:

• Establish confidentiality ground rules
• Model vulnerability ("I don't know" is okay)
• Thank people for raising difficult topics
• Protect dissenters (don't punish disagreement)
• Use humor appropriately (lightens mood)
• Take breaks when tension is high

When NOT to Run This Workshop

This workshop format works well for most organizations, but there are situations where it's not appropriate:

Don't run this workshop if:

• ❌ Executive team fundamentally disagrees on business strategy (fix that first before AI strategy)
• ❌ Organization in crisis mode (AI strategy is not urgent, focus on survival)
• ❌ No executive sponsorship (workshop will produce decisions that won't stick)
• ❌ No budget authority in room (can't make real commitments)
• ❌ Major organizational change underway (merger, restructuring - wait until stable)
• ❌ Key stakeholders can't attend both full days (need continuity and commitment)

Alternative approaches:

• If executive team not ready: Do stakeholder interviews → executive briefing → revisit workshop later
• If budget uncertain: Do abbreviated 1-day workshop focused on opportunity and strategy, not detailed planning
• If organization too large/complex: Do division-level or business unit workshops first, then enterprise consolidation

Your Workshop Planning Checklist

8 Weeks Before:

• Secure executive sponsor commitment
• Identify and invite 12-18 participants (ensure decision-makers, not delegates)
• Book 2 consecutive days on calendars (protect against conflicts)
• Select facilitator (external recommended for neutrality)
• Book workshop venue (off-site preferred to avoid interruptions)

4 Weeks Before:

• Send pre-work assignments to participants
• Facilitator interviews executive sponsor and 3-5 key stakeholders
• Prepare workshop materials (slides, templates, handouts)
• Set up collaboration tools (shared documents, virtual whiteboard if hybrid)

2 Weeks Before:

• Reminder email with pre-work due date
• Confirm attendance (no last-minute drops)
• Review submitted pre-work, identify themes
• Finalize workshop agenda based on pre-work insights

1 Week Before:

• Collect all pre-work submissions
• Facilitator synthesizes pre-work (use case ideas, concerns, etc.)
• Final agenda and materials sent to participants
• Logistics confirmed (room setup, meals, AV equipment)

Day Before:

• Room setup (flip charts, sticky notes, breakout spaces)
• Test AV and collaboration tech
• Print materials for all participants
• Facilitator final prep and mental rehearsal

Workshop Days:

• Start exactly on time
• Capture all outputs (photos of flip charts, digital notes)
• End with clear next steps and commitments

Within 3 Days After:

• Deliver comprehensive workshop output document
• Thank-you email to participants
• Schedule first AI Steering Committee meeting

Within 2 Weeks After:

• One-on-one check-ins with key action owners
• Address any blockers or questions
• Track progress on 90-day commitments

Get Expert Facilitation for Your AI Alignment Workshop

Running an effective AI Strategic Alignment Workshop requires balancing facilitation expertise, AI knowledge, and organizational change experience. The facilitator must drive toward decisions while managing group dynamics, surface hidden conflicts while maintaining psychological safety, and compress months of debate into 2 days without feeling rushed.

I facilitate AI Strategic Alignment Workshops for organizations launching or accelerating their AI journey—workshops that produce genuine executive alignment, clear priorities, committed resources, and 90-day action plans that actually get executed.

→ Book a discovery call to discuss your AI Alignment Workshop where we'll discuss your organization's context, stakeholder dynamics, decision-making culture, and customize the workshop format to your specific needs.

Or download the AI Workshop Facilitator's Guide (PDF + templates) with detailed facilitation scripts, exercise instructions, templates for all activities, pre-work assignments, and output document structure.

The organizations that move fastest with AI don't skip alignment—they accelerate it through intensive, facilitated workshops that drive to decisions. Make sure your AI strategy starts with alignment, not hope.