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The AI Readiness & Work Transformation Assessment evaluates an individual's ability to adopt AI, identify practical applications, solve workplace problems and redesign workflows for improved productivity. Through scenario-based and performance-oriented questions, it measures six essential AI competencies, helping organizations identify AI-ready talent, assess workforce capabilities, and plan role-specific AI development.
The PMaps AI Readiness & Work Transformation Test evaluates an individual's willingness and ability to adopt AI, recognize opportunities for its application and transform existing workflows to improve productivity. Moving beyond theoretical AI knowledge, the assessment uses workplace scenarios and practical tasks to measure AI adoption mindset, opportunity recognition, practical application, problem-solving, workflow redesign, and responsible AI judgment.
The assessment follows a three-level approach:
This structured approach helps organizations identify AI-ready talent, uncover workforce skill gaps, and make informed decisions about AI adoption, upskilling, and work transformation.
Measures willingness to embrace AI-enabled working methods, experiment with new tools, and adapt existing practices. It evaluates curiosity, openness to change, learning readiness, and comfort with AI-assisted work.
Assesses the ability to identify where AI can add value and recognize its limitations. Individuals must distinguish between tasks suitable for automation, AI augmentation, and activities that require human judgment.
Evaluates how effectively individuals use AI to achieve workplace objectives. It measures prompt formulation, context setting, output specification, iterative refinement, and the ability to identify gaps in AI-generated responses.
Measures the ability to apply AI to workplace challenges, break down complex problems, compare alternative solutions, and validate outputs. It also evaluates when independent human reasoning or intervention is necessary.
Assesses how effectively individuals identify repetitive activities, redesign existing workflows, allocate responsibilities between humans and AI, and recognize productivity improvement opportunities.
Evaluates the ability to use AI while maintaining accuracy, confidentiality, fairness, and accountability. It measures output verification, privacy awareness, bias recognition, responsible data handling, and appropriate human oversight.
Identify AI-Ready Talent
Evaluate employees and candidates based on their willingness and ability to apply AI, helping organizations understand workforce readiness beyond technical knowledge.
Discover Workforce AI Skill Gaps
Identify development needs across AI adoption, practical application, problem-solving, and responsible AI usage to support targeted training initiatives.
Measure Practical AI Capabilities
Use workplace scenarios and performance-oriented questions to evaluate how individuals apply AI to real business tasks rather than recall AI terminology.
Identify Workflow Transformation Potential
Assess whether individuals can recognize manual work, recommend AI-enabled process changes, and redesign workflows to support productivity improvements.
Support Role-Specific AI Development
Connect a common AI competency framework with functional scenarios across HR, sales, finance, operations, marketing, and customer service.
Strengthen Responsible AI Adoption
Evaluate whether individuals recognize AI limitations, protect confidential information, verify outputs, and maintain human accountability.
Make AI Upskilling More Targeted
Use competency-level insights to distinguish employees who need foundational awareness, guided application practice, or more advanced workflow transformation development.
Globally Validated
Language Agnostic
Advanced Analytics
Reliable & Validated
Seamless Integration
Real-time Reporting
Proctoring
PMaps combines behavioral evaluation, practical AI application, and workplace transformation scenarios in a structured assessment framework. Its six competencies help organizations distinguish between employees who are open to AI, those who can apply it effectively, and those capable of identifying opportunities to redesign existing work.
The assessment also connects AI readiness with role-specific responsibilities, making the insights useful for workforce development and talent decisions. Competency-level reporting helps HR and business leaders identify individual strengths, development opportunities, and areas requiring additional support for responsible AI adoption.
The test categories—including logical thinking, quantitative assessment, qualitative analysis, and verbal reasoning—were very effective in identifying candidates who best fit our requirements. The structured division of the test criteria was particularly helpful in streamlining our selection process
We found it well within our budget, which saved us a lot of time during the hiring process. The assessment was highly relevant and accurately matched our hiring needs—extremely effective and efficient overall.
The quality of our hiring metrics has significantly improved. Our goal was to find individuals who can understand and respond effectively to client communication, and this assessment has helped us achieve that. The test results have been excellent, making this transition highly valuable for us.
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Set Test Difficulty
Choose from beginner, intermediate, or advanced questions within our extensive skill libraries to challenge candidates at appropriate levels.
Combine Skills in One Test
Integrate multiple skill sets into one efficient test to evaluate candidates' competencies across the board comprehensively.
Add Custom Questions
Easily insert your specialized questions, be they coding problems, multiple-choice questions, or case studies, to tailor the test to your company’s profile.
Create Custom Assessments
Collaborate with our experts to develop bespoke assessments that effectively pinpoint the best candidates for your team.
Benchmark or Customize
Select from established industry benchmarks or work with us to create customized criteria that meet your unique organizational needs.
Enable Proctoring
Utilize our advanced proctoring feature to maintain test integrity, ensuring a fair and secure assessment environment.
AI adoption requires more than access to technology. Employees must understand where AI can support their work, how to use it effectively, and when human judgment remains essential. Without these capabilities, organizations may invest in AI tools without knowing whether their workforce can apply them productively.
The PMaps AI Readiness & Work Transformation Assessment addresses this challenge by evaluating six interconnected competencies covering willingness, understanding, application, problem-solving, work redesign, and responsible AI judgment.
Knowing what generative AI means does not necessarily indicate an ability to apply it at work. An employee may understand AI terminology but struggle to identify appropriate use cases or construct effective instructions.
The assessment therefore uses scenarios and practical tasks that examine how people evaluate AI opportunities, structure prompts, and assess generated responses.
Employees encounter repetitive, information-heavy, and decision-support tasks across many functions. Recognizing which activities can be automated, augmented, or retained under human control is an important part of AI readiness.
For example, a recruiter may identify resume summaries and interview scheduling as opportunities for AI assistance while retaining human review in candidate evaluation and selection.
AI capability also depends on selecting appropriate approaches for workplace challenges. Individuals must interpret problems, consider alternatives, validate generated information, and recognize exceptions requiring human intervention.
Scenario-based evaluation helps distinguish between merely using an AI chatbot and applying AI deliberately to accomplish a business objective.
The assessment places particular emphasis on workflow redesign. Instead of asking whether individuals can use AI tools, it evaluates whether they can analyze existing processes and recommend more effective human-AI workflows.
For instance, an employee may be presented with a time-consuming reporting process and asked to identify manual steps, propose an AI-assisted approach, define human review points, and suggest how productivity improvement could be measured.
AI-generated outputs can be incomplete, inaccurate, biased, or unsuitable for sensitive situations. Effective AI adoption therefore requires verification, confidentiality awareness, and accountability.
The assessment evaluates whether individuals recognize these risks and make appropriate decisions about information handling, human oversight, and escalation.
A common AI competency framework allows organizations to assess employees consistently, while role-specific scenarios make the evaluation relevant to daily responsibilities.
For example, customer service employees may work through query-classification situations, finance professionals may evaluate reporting scenarios, and managers may examine AI-assisted decision support.
This approach connects individual AI capability with practical workplace requirements and helps organizations plan more focused development initiatives.
Learn more about PMaps through commonly asked questions:
An AI Readiness Assessment evaluates an individual's willingness and ability to adopt, understand, and apply artificial intelligence in workplace activities. It helps organizations assess practical AI capabilities, identify development needs, and understand potential for AI-enabled work transformation.
The assessment measures six competencies: AI Adoption Mindset, AI Understanding & Opportunity Recognition, Practical AI Application, AI Problem-Solving & Decision-Making, AI Work Transformation Ability, and Responsible AI Judgment.
The proposed PMaps assessment takes approximately 28 minutes and includes situational judgment questions, scenario-based multiple-choice questions, and practical performance-oriented tasks.
Yes. A common competency framework can be combined with role-specific workplace scenarios. For example, recruitment scenarios may involve candidate summaries, while finance scenarios may focus on reporting, reconciliation support, and variance analysis.
AI literacy generally concerns understanding AI concepts, capabilities, and limitations. AI work transformation ability goes further by assessing whether an individual can identify opportunities to redesign tasks, allocate responsibilities between humans and AI, and recommend ways to improve existing workflows.
Organizations can use competency-level results to identify strengths, prioritize AI upskilling, understand workflow transformation potential, and inform employee development plans. Results should be interpreted alongside job requirements, practical performance, and other relevant evidence.
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