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AI Assessment gives you a verified baseline of how your people actually work with AI — by team, function and role — and what to build first.

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Evolve LevelMeasure applied AI skills and identify gaps by role.
Evolve CoachHelp people work better with AI coaching in the tools they already use.
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From pilots to real AI adoption

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You invested in AI. Is it working?

Ten minutes to a clear answer.

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Know where your people really stand with AI — before you train them

Evolve Level assesses how each person works with AI through realistic scenarios adapted to their role and domain. It evaluates both the outcome and the process, then identifies skill gaps and learning priorities.

Team overviewAI for Non-Technical Professionals

Export Report
Average Score
0%
Completed Assessments
0/24
0%
Assessments In Progress
0employees
Assessments Not Started
0employees
Skill Gaps
Optimizing Text with AI9%
AI Cyber Hygiene14%
Evaluating AI Outputs31%
Top Skills
Prompt Engineering84%
Structuring & Synthesizing Information71%
Research with AI Tools68%

  1. Compare verified results by person, role, team, and function before setting training budgets, assigning people to AI initiatives, or making other workforce decisions where AI skills matter.

  2. Break results down by role, domain, and skill. Evolve Level recommends a targeted development path for each person, reducing broad training and time spent on skills they already have.

  3. Assessments can reflect real cases and use the tools and models relevant to each role and domain. Scoring considers the actions and decisions behind the result, not only the final answer.

  4. Reassess the same skills after training to determine what improved, which gaps remain, and where further development is needed.

Your workspace

During this workflow, your screen will split into two panels: this chat stays on the left, and your workspace opens on the right.

Left panel: Our conversation. Here I will share instructions, and you will submit your answers. If something feels unclear, you can also ask me questions about data clarification, technical support, or process help.

Right panel: The workspace. That’s where you will complete your work with:

  • IDE space where you’ll run and edit code.
  • LLM chat where you can brainstorm ideas.

Open the Workspace

Click Workspace on the right edge to slide the panel out. Your files appear there whenever a phase requires coding.

Ask Dot anything

Decision-ready baseline

Identify who needs training and who is already proficient

Compare verified results by person, role, team, and function before setting training budgets, assigning people to AI initiatives, or making other workforce decisions where AI skills matter.

Your workspace

During this workflow, your screen will split into two panels: this chat stays on the left, and your workspace opens on the right.

Left panel: Our conversation. Here I will share instructions, and you will submit your answers. If something feels unclear, you can also ask me questions about data clarification, technical support, or process help.

Right panel: The workspace. That’s where you will complete your work with:

  • IDE space where you’ll run and edit code.
  • LLM chat where you can brainstorm ideas.

Open the Workspace

Click Workspace on the right edge to slide the panel out. Your files appear there whenever a phase requires coding.

Ask Dot anything

Focused development

Train only the skills that are missing

Break results down by role, domain, and skill. Evolve Level recommends a targeted development path for each person, reducing broad training and time spent on skills they already have.

Expertise Overview

Prompt Engineering

Evaluating AI Outputs

Research with AI Tools

Optimizing Text with AI

Structuring & Synthesizing Information

AI Cyber Hygiene

Advanced skills6
Emerging skills12

Relevant evidence

Measure capability in the right context

Assessments can reflect real cases and use the tools and models relevant to each role and domain. Scoring considers the actions and decisions behind the result, not only the final answer.

Assessments In Progress
4employees
Completed Assessments
18/2475%
Average Score
88%
AI for Non-Technical

Proof of progress

Verify whether training improved AI skills

Reassess the same skills after training to determine what improved, which gaps remain, and where further development is needed.

Used a broad prompt without specifying keywords, date ranges, or methodology, pulling back irrelevant results

Essential expertise 5 skills
Prompt Engineering for Research20%
Identifying AI Hallucinations40%
Data Privacy with AI Tools50%
2 more skills

You conducted a thorough bias audit before deployment, identifying and mitigating disparate impacts across demographic groups

How it works?

From assessment to
a targeted development plan

Completed skill card for Prompt Engineering for Research with a Level me up button

Stage: Assess

01 Complete real AI tasks

Each person completes role-based scenarios in an isolated workspace, with selected AI tools and no access to real data.

Skill scores grouped into essential and important expertise

Stage: Measure

02 Evaluate process and result

Evolve Level scores the final output and the decisions behind it: how the person frames the task and uses the model.

Recommended growth areas card highlighting Machine Learning Basics

Stage: Prioritize

03 Build the skills baseline

Results are organized by person, role, team and skill, showing who needs development and where to focus first.

Level gauge from Emerging to Advanced with the needle at Proficient

Stage: Develop

04 Generate a development path

Each person gets a development path for their gaps. After training, Level reassesses them and updates the path.

What your organization gets

Make AI training decisions with verified skills data

Evolve Level identifies who needs development, which skills to prioritize, and which employees are ready to support AI initiatives. Leaders can use that evidence to avoid broad training, allocate budget more precisely, and verify progress after development.

How Evolve Level produces
reliable, comparable results

Psychometricians and subject-matter experts define the criteria for every AI skill, informed by relevant research and field data. Evolve Level applies those criteria consistently to everyone assessed on that skill.

Supporting expertise

AI Ethics & Responsibility

Understanding ethical principles and responsible practices for developing and deploying AI systems. This skill is essential when designing AI products, establishing governance frameworks, or evaluating algorithmic impact.

Skill gap40%

Assessments recreate real working situations without accessing production systems, company codebases, or proprietary data.

IDE spaceLLM chat

Your workspace

During this workflow, your screen will split into two panels: this chat stays on the left, and your workspace opens on the right.

  • IDE space where you’ll run and edit code.
  • LLM chat where you can brainstorm ideas.

People demonstrate their capability by completing real tasks. Results are based on what they do and the decisions they make, not how they rate their own knowledge.

What went well

You conducted a thorough bias audit before deployment, identifying and mitigating disparate impacts across demographic groups

What could be improved

Deployed a model without testing for bias across different user demographics, leading to unfair outcomes for underrepresented groups

L&D and HR teams can adjust the thresholds used to prioritize development according to their organization’s standards and goals.

LevelProficient

Frequently asked questions

An AI skills assessment measures how well employees can apply AI in their work, not just what they know about it. It can evaluate prompting, critical judgment, output validation, workflow integration, and knowing when not to rely on AI.

An AI skills assessment focuses on people’s ability to work with AI. An AI maturity assessment examines the broader organization, including strategy, data, infrastructure, governance, and operating models. Evolve Level provides a verified baseline for the people dimension of AI maturity but does not replace a complete maturity assessment.

Companies can define the AI skills required for each role and evaluate employees through realistic work scenarios. Results can then be scored by domain and skill and aggregated across teams, functions, and roles. Evolve Level applies this approach to create a verified workforce capability baseline.

Self-assessments measure perceived confidence, while quizzes primarily test knowledge and recall. Evolve Level uses realistic scenarios to show how someone applies AI, evaluates its output, and makes decisions while completing a task.

Yes. Evolve Level adapts assessment scenarios and scoring criteria to the skills required by each role. Assessments can take place in an LLM chat, simulated IDE, or task-based workspace, depending on the capability being measured.

Evolve Level shows each person’s strengths and skill gaps by role, domain, and individual skill. These results roll up into comparable views across teams and functions and generate personalized recommendations for what each person should develop next.

Assessments take place in synthetic, isolated workspaces that recreate relevant tasks without accessing production systems, company codebases, or proprietary data.

Get a verified view of
your workforce’s AI skills

Evolve Level shows who needs training, which skills to prioritize, who is already proficient, and whether capability improves after development.