AI Clarity Workshops
A facilitated on-site engagement for leadership teams to evaluate AI readiness, explore realistic use cases, assess the ROI of high-impact initiatives, and develop a roadmap rooted in phased delivery, from pilot to scale, to minimize risk.
Why This Workshop Exists
The five places mid-market AI efforts
get stuck before they start.
We know AI matters. We're not sure where to start.
Most teams that stall aren’t short on interest, they’re short on a starting point that isn’t “buy a tool and see what happens.” Readiness research backs this up: organizations with a clearly defined AI strategy see meaningfully better outcomes than those without one, and starting from a tool instead of a target outcome is one of the most common reasons AI pilots never reach production.
We can't tell if it's AI, or automation with a new label.
This confusion runs in both directions. Internally, leadership teams often use “AI” and “automation” interchangeably when deciding where either one applies. Externally, the market hasn’t helped, vendors routinely market basic rules-based automation as AI-powered, a pattern significant enough that regulators now pursue it as a form of securities or consumer fraud. If a team can’t draw that line internally, evaluating a vendor’s claims is close to impossible.
We're not sure our data is ready.
This instinct is usually correct, and it’s worth surfacing before a contract gets signed rather than after. Recent mid-market data readiness research found only a small minority of organizations report their data is genuinely AI-ready, and data quality consistently ranks among the top barriers cited by mid-market IT leaders trying to scale past a pilot.
Knowledge gap.
This is broader than “has the team used ChatGPT, Claude, Gemini or CoPilot.” Studies of professional workforces consistently find a meaningful share of employees have received contradictory guidance, or no formal guidance at all from leadership on how, or whether, to use AI in their work. That’s a leadership communication gap as much as a skills gap, and a generic training video doesn’t close it.
Alignment gap.
One we’d add from the research, not your list: surveys of executives and individual contributors at the same companies routinely show a wide gap in how each group perceives the organization’s AI progress and intent, leadership tends to overestimate both adoption and enthusiasm relative to what frontline staff actually report. Left unaddressed, that gap quietly
undercuts adoption regardless of how sound the strategy is.
A Pre-Assessment Survey That Shapes the Agenda
Every participant completes a short, confidential readiness survey before workshop day. It covers current AI literacy by role, tools already in informal or “shadow” use, the blockers people actually believe are holding adoption back, and what each person hopes the organization gets out of AI. Responses are aggregated and anonymized — the goal is an honest baseline, not a performance review.
The results shape the entire day. We don’t run a canned curriculum: where your team already has working knowledge, we move past it; where the survey shows a real gap or a sharp disagreement between functions, that’s where the day spends its time.
TIME TO COMPLETE
~10 MIN
Per participant, sent ahead of the session
REPORTING
Aggregated and anonymized, individual responses are never attributed in the room.
USED FOR
Creating Phase 1 and 2 of the workshop agenda, so we're not reteaching what the participants already know.
Workshop Tailored to
your organization's AI journey
01
Review of Survey Results
We open by presenting the aggregated, anonymized readiness survey results back to the room where understanding is aligned, where it diverges sharply between functions, and what that gap means for adoption risk. No one is singled out; the goal is a shared, judgment-free starting point before any strategy discussion begins.
02
Training and Knowledge Session
A focused, vendor-neutral primer on what current AI systems can and cannot reliably do — the real difference between generative AI, predictive ML, and agentic systems — plus the cost and risk factors that vendor demos tend to leave out. Calibrated to the survey results, so we’re not re-teaching what the room already knows or skipping fundamentals a previous pitch assumed everyone had.
03
AI Vision
Facilitated session to define what AI should mean for this organization specifically. Ties AI ambition to business outcomes leadership can defend in a board meeting. Produces a written, one-page vision statement.
04
Use Case Analysis
Structured brainstorming across participants’ day-to-day functions, surfaces both obvious use cases and opportunities buried in manual, repetitive work. Each use case opportunity is captured with process detail, data involved, current cost or time, and owner.
05
Evaluation Matrix
Every use case scored against a consistent, technology-neutral matrix. Scoring criteria: business impact, technical feasibility, data readiness, implementation cost, risk and governance exposure. Produces a ranked shortlist, not a flat list of ideas.
06
Next Steps
Identifies one to three use cases to pursue first. Clarifies what each needs to move forward, data, budget, an executive sponsor
Honest read on whether the organization is ready to build, needs deeper readiness work, or a full AI Advisory roadmap
Built for Leaders & Cross-Functional Teams
CEO / Founders
You’ve set the AI direction. Six months later the team is still debating where to start. This session gets your leadership team aligned and moving.
IT Leaders
You’re fielding vendor proposals and internal requests with no neutral framework to evaluate them. The workshop gives you a structured way to assess options and set clear priorities.
Finance Teams
You’re being asked to approve AI investments without a clear ROI framework. This session gives you the tools to evaluate proposals, stress-test assumptions, and set guardrails before budget is committed.
Operations
Your team is buried in manual work and asking for AI tools. You need a practical way to assess what’s worth pursuing, what isn’t, and how to sequence it without disrupting what’s already working.