UNLOK · Human Potential
Sample diagnostic · Illustrative data
AI Human Readiness
Diagnostic
Expose the leadership blind spots putting AI value at risk. See what employees actually experience, where adoption breaks, and what to fix first.
Workforce reality−Leadership prediction=Reality Gap
Confidential sample · 01
01 · AI Reality Gap
Where leadership's reality diverges.
Use this view to see which leadership assumptions are putting AI adoption and value at risk.
Leadership predictionWorkforce realityMaterial gap: −0.75 or lower
| Dimension | What it measures | Leadership | Workforce | Gap |
|---|
| AI Direction | Purpose, role line-of-sight, boundaries | 4.3 | 2.8 | −1.5 |
| AI Enablement | Access, support, real-task practice | 4.0 | 2.4 | −1.6 |
| AI Workflow | Opportunity, integration, human/AI roles | 3.6 | 2.9 | −0.7 |
| AI Trust | Intent, safety, job-impact confidence | 4.2 | 2.0 | −2.2 |
| AI Agency | Voice, autonomy, ownership | 3.8 | 2.6 | −1.2 |
| AI Mastery | Skill, evaluation, development | 3.7 | 2.8 | −0.9 |
The central risk is not resistance to AI. It is support and trust. People are using AI under the table because they do not trust that it will be received favorably. They also see it as a serious risk to their job security.
Blind spot
Employees worry AI could replace their jobs, making them less likely to use it openly or fully.
Aligned weakness
Leaders and employees agree: AI is not yet part of regular work.
Hidden strength
More people use AI than leaders think. This group of willing users is ideal for early cohort training.
AI Reality Gap · 03
02 · AI Adoption Map
What is actually happening with AI.
Behavioral facts are reported separately from the six conditions. They describe the current uses and practices among your workforce.
47%use AI at least weekly
18%use AI daily
38%of weekly users primarily use an approved tool
68%want to use more AI in their work
52%know what uses are permitted
41%say their manager knows about their use
14%had hands-on, task-specific practice
21%do not use AI for work today
Leadership prediction vs actual
22%
Predicted weekly
47%
Actual weekly
34%
Predicted approved
18%
Actual approved*
*18% of total workforce = 38% of weekly users.
The workforce has created a strong foundation for AI adoption. Clearer guidance and shared practices can move AI use onto approved tools, reduce avoidable risk, and help teams save time on real work.
Evidence: Employees whose managers actively support AI use are about 8.7× more likely to say AI has transformed their work. Gallup, State of the Global Workplace 2026.
AI Adoption Map · 04
03 · AI Opportunity Map
Where AI can create value—without hollowing out the work.
Average workweek allocation
Core / high-value 69%Admin 17%Search + rework 14%
31% is potentially redesignable, not automatically removable. Each use case requires risk, quality, and human-value review.
First pilot: Operations weekly reporting
Estimated 420 hours/month · high repetition · structured inputs · human approval retained
Recurring workHours/mo.Why this roleAI role
Compile weekly operating reports420Structured and repeatableAI Assist
Re-key customer and order data280Rules-based data entryAutomate
Search policies and prior proposals215Retrieval-heavyAI Assist
Draft routine follow-up emails170Repeatable draftingAI Assist
Coach performance and resolve conflict—Relationship and judgmentProtect Human
Make exceptions for strategic customers—Consequential judgmentProtect Human
Automate
Machine owns reliable, low-judgment movement of information.
AI Assist
Human owns the outcome; AI removes search, synthesis, or drafting load.
Protect Human
Relationships, consequential judgment, accountability, creativity, and care stay human-led.
AI Opportunity Map · 05
04 · Organizational Heatmap
Where adoption is most likely to break.
Workforce scores by function. Red indicates the lowest readiness conditions and the highest need for local intervention.
Function
Direction
Enablement
Workflow
Trust
Agency
Mastery
Sales
2.7
2.2
3.1
1.9
2.5
3.0
Operations
2.3
2.0
2.4
1.8
2.2
2.6
Finance
3.6
3.2
3.5
3.0
3.4
3.6
Marketing
3.8
3.7
3.9
3.2
3.8
3.9
People / HR
3.1
2.8
2.7
2.6
3.0
3.1
■ 1.0–2.4 critical■ 2.5–2.9 constrained■ 3.0–3.3 emerging■ 3.4–5.0 strength
Operations is the priority system.It combines the clearest workload opportunity with the lowest overall readiness. Begin with trust and permission before deploying the reporting pilot.
Sales needs a different intervention
Sales teams see where AI could help, but many still lack the support and confidence to use it. Start with trusted peers, examples that protect customer information, and clear backing from managers.
Learn from your marketing team.
Marketing is further ahead across all six conditions. Identify the manager behaviors, team practices, and examples driving that progress, then adapt what works for other functions.
Organizational Heatmap · 06
05 · AI Cascade
Managers reveal two different gaps.
Managers answer twice: once about their own experience of executive leadership, and once to predict what employees will say. Employees then report their actual experience.
1 · Managers look upTheir answers reveal the gap between executive intent and what managers actually understand.
2 · Managers look downTheir predictions are compared with employee answers to reveal what managers cannot see in their teams.
AI condition1–5 scale
Executive → Manager gapExecutive view compared with manager experience
Manager → Workforce gapManager prediction compared with employee reality
Direction
4.3→3.6−0.7
3.6→2.8−0.8
Enablement
4.0→3.1−0.9
3.1→2.4−0.7
Workflow
3.6→3.2−0.4
3.2→2.9−0.3
Trust · largest gap
4.2→3.7−0.5
3.7→2.0−1.7
Agency
3.8→3.2−0.6
3.2→2.6−0.6
Mastery
3.7→3.1−0.6
3.1→2.8−0.3
The executive message reaches managers reasonably well. The larger failure happens between managers and employees, especially around trust and job security.
What this means
Managers understand more than employees do, but they overestimate how safe and clear AI feels to their teams.
What to do
Give managers clear answers about permitted use, role impact, and where to take questions they cannot answer.
AI Cascade · 07
06 · Human Gain Map
If AI works, what do people gain?
We asked employees where they would reinvest five hours saved by AI.
Five hours returned each week.The value comes from where those hours go next.
29%Customers & relationships1.45 hours / week
23%Strategic thinking1.15 hours / week
18%Problem-solving0.9 hours / week
16%Deep work & craft0.8 hours / week
14%Learning & coaching0.7 hours / week
73% believe AI could make their job better, not merely faster.That optimism depends on responsible implementation and visible reinvestment of saved time.
Work employees say should remain human-led
Performance conversationsCustomer trustConsequential decisionsCreative directionExceptions & ethicsCoaching
Reclaimed time must be assigned, protected, and measured.
Assign itDecide where saved time should go before the pilot begins.
Protect itGive managers permission to preserve that capacity.
Measure itTrack whether the time reaches customers, strategy, learning, or deeper work.
Human Gain Map · 08
07 · Discovery Plan
What the diagnostic tells you to do next.
The diagnostic turns leadership assumptions and workforce evidence into a practical, prioritized plan. The sequence below is illustrative—not a pre-set implementation proposal.
#
Finding
Recommended next move
Likely owner
Priority
1
Trust is the largest gap
Leadership 4.2 · Workforce 2.0
Clarify why AI is being introduced, what it means for jobs, and how managers should address employee concerns.
CEO / CHRO
First
2
Permission is unclear
52% know permitted uses
Define approved and prohibited uses, practical examples, and one route for questions or escalation.
CIO / Legal
High
3
Demand exceeds support
68% want more; 14% practiced
Identify the roles and teams where hands-on, task-specific support would unlock the most value.
L&D / Function leads
High
4
Operations has a clear opportunity
420 hours/month identified
Validate the reporting workflow, its quality requirements, and the human judgment that must remain in the loop.
COO / Ops lead
Explore
5
Evidence should guide investment
31% of work is redesignable
Sequence opportunities by readiness, value, risk, and human impact before committing to tools or implementation.
Leadership team
Decide
People insight
See where trust, clarity, support, and confidence are helping—or blocking—responsible AI use.
Adoption insight
See where AI is already being used, where it is hidden, and what would move use onto approved practices.
Business insight
See which workflows merit deeper validation and where investment is most likely to create measurable value.
The output is a decision plan: what is wrong, what matters most, who should own it, and what evidence to gather next.
Discovery Plan · 09
UNLOK · Human Potential
Optional execution support
How Laura and Thompson can help deliver the plan.
The diagnostic tells you what needs attention. If you want help acting on it, we bring the leadership, workflow, and delivery expertise the findings call for.
Laura · Leadership and trust
Turn intent into credible leadership action.
Align leaders, equip managers, and address employee concerns about AI and jobs.
- Executive alignment
- Manager communication tools
- Trust and role-impact conversations
Plan priorities01Establish trust02Make permission usable
Thompson · Workflows and practice
Turn opportunity into better work.
Translate the findings into practical workflow improvements and build skill with approved tools on real work.
- Validate the right use cases
- Redesign workflows and ways of working
- Train people on real tasks
- Set quality checks and human sign-off
Plan priorities03Build practical capability04Validate workflow value
Trusted network · Delivery capacity
Add the right expertise when ownership is the constraint.
Bring in dedicated ownership or specialized expertise when the plan requires it.
- Interim program leadership
- Functional or technical expertise
- Additional delivery capacity
Plan coverage1–5Matched to the priority and need
Support follows the evidenceScope, sequence, and team composition are set only after the diagnostic identifies the priorities. You can engage Laura and Thompson for the parts your organization needs—not a pre-set program.
Execution support is optional. The diagnostic and its decision plan stand on their own.
Optional Execution Support · 10