Best AI Skills Assessment Platforms for Hiring (2026)

More HR teams now want to know how well people work with AI, whether they are hiring new people or developing the teams they already have. A growing set of platforms can show it, but they measure different things in different ways. Some put people in a simulation with a live AI assistant. Some use scenario-based questions. Others use AI video interviews or adaptive, conversational questions.

This page compares ten platforms with a dedicated AI skills assessment: Bryq, TestGorilla, CodeSignal, Canditech, Maki, Workera, HackerRank, SHL, Harver and iMocha. It is written for HR and talent acquisition teams deciding how to assess AI skills, in candidates or in current employees.

A note on how this page was written. Bryq makes one of the platforms on this list. Every platform, including ours, is described from its own published pages as of October 2026. Each description links to its source.

How we compared the platforms

We compared each platform on seven questions. Together they decide whether an assessment shows how someone actually works with AI, and how useful the result is in a hiring decision.

1. What does it observe? The strongest signal comes from decisions and work done with AI in realistic tasks, whether through a simulation, scenario-based questions or a structured conversation. What someone says they know about AI shows much less.

2. What does it measure? A named set of skills, each scored on its own, tells you where a person is strong and where they need support. A single number hides that.

3. Does it fit the role? Some AI skills matter in every job. Others belong to one role, such as briefing AI agents in product management. Look for general coverage, and for role-specific versions where AI shapes the core work.

4. Is it tool-agnostic? AI tools change every few months. An assessment should measure skills that carry across tools, not familiarity with one product.

5. Who is it for, and how long does it take? Some platforms are built for hiring, some for developing current employees, and some for both. Length matters most early in the hiring process.

6. Does it sit in a full candidate profile? An AI skills score on its own is one more number to weigh. Next to cognitive ability and personality, scored against the same role, it becomes part of one picture of the candidate.

7. How was it validated? Ask who built and reviewed the assessment, and what research it rests on. For AI skills, the strongest foundation is peer-reviewed research and published work by subject-matter experts on how AI is used in each role. Look for an assessment built on that evidence, ideally reviewed by I/O psychologists who check that the scoring is reliable and fair.

The ten platforms at a glance

1. What does it observe?

• Bryq: a simulation with a live AI assistant, and scenario-based questions

• TestGorilla: scenario-based tasks and AI video interviews

• CodeSignal: AI chat, AI-assisted coding and scenario-based tasks

• Canditech: job simulations with embedded AI tools

• Maki: situational judgement tests and structured behavioral questions

• Workera: adaptive, conversational skill verification

• HackerRank: AI assistant conversations and IDE activity during coding and project questions

• SHL: SHL's Global Skills Assessment

• Harver: AI PREVAIL assessment module

• iMocha: scenario-based multiple-choice questions and technical evaluations

2. What does it measure?

• Bryq: named AI skills, each scored on its own

• TestGorilla: a five-pillar AI Fluency Framework

• CodeSignal: from AI literacy to model development and fine-tuning

• Canditech: AI skills across technical and non-technical roles

• Maki: four dimensions of AI proficiency

• Workera: AI, generative AI and responsible AI, on a 300-point scale

• HackerRank: context quality, critical thinking and collaboration, graded A to C

• SHL: AI literacy, analytical ability, continuous learning and AI promotion, each scored separately

• Harver: AI technical aptitude and behavioral readiness

• iMocha: prompt engineering basics, including prompt structure and avoiding hallucination

3. Does it fit the role?

• Bryq: product managers, account managers, sales development, managers leading AI adoption (AI Change Leadership) and more

• TestGorilla: AI fluency questions in more than 70 role-specific AI video interviews

• CodeSignal: role-based, from AI literacy to agentic AI engineering

• Canditech: tests generated from a job description

• Maki: -

• Workera: role-specific assessment packs

• HackerRank: -

• SHL: AI Leadership Profile for leaders

• Harver: -

• iMocha: combines several skills in one test

4. Is it tool-agnostic?

• Bryq: yes, across any AI tool

• TestGorilla: scores which tool a candidate chooses

• CodeSignal: choice of AI model

• Canditech: optional ChatGPT integration

• Maki: yes, measures agility across tools

• Workera: not tied to one tool

• HackerRank: built-in AI assistant

• SHL: behavioral skills, not tied to a tool

• Harver: not published

• iMocha: not published

5. Who is it for, and how long does it take?

• Bryq: hiring and current employees; about 10 to 15 minutes

• TestGorilla: hiring; length not published

• CodeSignal: hiring and upskilling; 20 to 30 minutes for AI literacy, 60 to 90 for advanced roles

• Canditech: hiring; length not published

• Maki: hiring graduates, knowledge workers and managers; length not published

• Workera: developing current employees; length not published

• HackerRank: hiring for technical roles; length not published

• SHL: hiring and current employees; length not published

• Harver: hiring and current employees; length not published

• iMocha: hiring and existing teams; length not published

6. Does it sit in a full candidate profile?

• Bryq: one integrated profile with cognitive ability and personality, scored against the role

• TestGorilla: up to five tests per assessment, including cognitive ability and personality

• CodeSignal: -

• Canditech: cognitive ability, personality and AI skills on one platform

• Maki: score sits in the candidate profile next to other results

• Workera: -

• HackerRank: -

• SHL: alongside SHL's cognitive ability and behavioral assessments

• Harver: alongside Harver's cognitive ability, personality and behavioral fit assessments

• iMocha: cognitive ability tests; no personality tests

7. How was it validated?

• Bryq: subject-matter experts, peer-reviewed research frameworks, reviewed by I/O psychologists

• TestGorilla: a science team of I/O psychologists, psychometricians and data scientists

• CodeSignal: validated by I-O psychologists

• Canditech: built by industry experts, reviewed by a PhD-level psychometrics team

• Maki: framework validated by Maki's science team

• Workera: an assessment science team, with ongoing validity monitoring

• HackerRank: language-model scoring against standard rubrics

• SHL: SHL's science team, from its Superworker skills research

• Harver: in-house I/O psychology team, aligned with global AI literacy frameworks

• iMocha: not published

Other platforms we checked. Criteria, Testlify and HireVue are widely used assessment and interviewing platforms. As of October 2026, none of them publishes a dedicated assessment of candidates' AI skills on its website, so they are not in the comparison above.

Why AI fluency belongs in the full candidate profile

AI fluency is one signal among several. It shows how someone works with AI, but not how they learn, solve problems or work with others. A candidate can be fluent with AI and still be the wrong fit for the role.

That is why it matters where an AI skills result sits. On its own, it is one more score to weigh against interviews and other tests, often on a different scale. Inside a full candidate profile, next to cognitive ability and personality and scored against the same role, it becomes part of one picture of the person.

Bryq is built this way. It measures cognitive ability, personality traits, soft and hard skills, including AI fluency, in one integrated candidate profile. Its assessments are validated by I/O psychologists, and its AI Fluency Assessment is built on six peer-reviewed research frameworks.

The platforms in detail

Bryq

Bryq is a talent assessment platform that measures cognitive ability, personality traits soft and hard skills, including AI fluency, in one candidate profile. It assesses AI fluency in two ways:

• AI simulation (about 15 minutes): people complete a work task with a live AI assistant. Bryq scores five skills from 0 to 100 (AI task strategy, prompting and interaction, critical evaluation, ethical and responsible use, and workflow integration) and places the result at one of three levels per role: Aware, Functional or Advanced.

• Scenario questions: multiple-choice questions set in realistic work moments ask what people would do next, with a separate score for each skill.

Both assessments are tool-agnostic and included in every Bryq plan.

Bryq integrates with your ATS in under a week.

Best fit: teams that want AI fluency in the same profile as cognitive ability, personality, soft and hard skills, for candidates and current employees.

Worth knowing: Bryq also offers role-specific AI fluency assessments for product managers, account managers, sales development, managers leading AI adoption (AI Change Leadership) and more.

TestGorilla

TestGorilla's AI fluency assessments are built on its five-pillar AI Fluency Framework, launched in March 2026. Its page names applied use, learning agility, systems thinking and responsible use among the pillars. Candidates complete scenario-based tasks, and TestGorilla says its scoring captures "which tool they chose, what they verified". AI video interviews measure all five pillars in one sitting, and more than 70 existing AI video interviews include one or two AI fluency questions.

Best fit: teams already using TestGorilla's test library who want to add AI fluency to it.

Worth knowing: AI interviews are on the Plus plan. Paid plans are billed annually and credit-based.

CodeSignal

CodeSignal's agentic AI assessments put candidates and employees in realistic AI simulations, including AI chat, AI-assisted coding and scenario-based tasks. Coverage runs from foundational AI literacy to advanced skills such as model development and fine-tuning. Teams can choose which large language model powers an assessment, and CodeSignal says its assessments are validated by I-O psychologists. AI literacy assessments take 20 to 30 minutes; advanced technical ones take 60 to 90.

Best fit: organizations assessing AI skills from business roles through to engineering and AI research.

Worth knowing: the range leans technical, with separate assessments for AI-assisted coding and agentic AI engineering.

Canditech

Canditech assesses AI skills through job simulations with embedded AI tools, including ChatGPT, so candidates show how they use AI on a task. Its AI Assessment Builder generates job-specific tests from a job description, and AI auto-scoring grades open-text, code and video responses. Canditech lists more than 40 ATS integrations and anti-cheating features.

Best fit: teams that want custom, simulation-style AI tests across technical and non-technical roles.

Worth knowing: Canditech describes AI skills by role rather than through a named set of dimensions.

Maki

Maki's AI proficiency assessment, launched in April 2026, measures four dimensions: AI tool agility, human-tool interactivity, ethical use of AI, and data and algorithmic literacy. It uses situational judgement tests and structured behavioral questions, with conversational tasks planned. The AI proficiency score sits in the candidate's profile next to their other results.

Best fit: existing Maki customers, who get it at no extra cost inside Maki's screening and voice interview agents.

Worth knowing: Maki built it for graduates, knowledge workers and managers.

Workera

Workera measures AI skills across a workforce through adaptive, conversational skill verification. Its AI fluency framework covers AI, generative AI and responsible AI, and its assessments extend to advanced technical skills, scored on a 300-point scale. Role-specific assessment packs connect general AI fluency to the outcomes of each job.

Best fit: large organizations measuring and developing AI skills in current employees.

Worth knowing: Workera focuses on workforce development rather than pre-hire screening. Pearson has agreed to acquire Workera, with the deal expected to close in the second half of 2026.

HackerRank

HackerRank's AI Fluency Evaluation, part of its AI add-on, assesses how candidates use the built-in AI assistant during coding and project questions. It analyzes the conversation with the assistant and the candidate's IDE activity, then grades AI fluency from A to C across three dimensions: context quality, critical thinking and collaboration. Language models score the interactions against standard rubrics.

Best fit: engineering teams that already use HackerRank for coding assessments.

Worth knowing: it is available only with HackerRank's Advanced Evaluation and Proctor Mode, and it works on coding and project questions.

SHL

SHL's AI Readiness Profile measures four areas: AI literacy, analytical ability, continuous learning and AI promotion, each through two observable skills. It runs through SHL's Global Skills Assessment, and each skill is scored separately. A separate AI Leadership Profile covers leaders.

Best fit: large organizations measuring AI readiness across a workforce, or in hiring alongside SHL's other assessments.

Worth knowing: the profile focuses on the behavioral skills behind AI readiness rather than hands-on work with an AI tool.

Harver

Harver launched AI PREVAIL in April 2026 as an AI aptitude and adaptability assessment module. Harver says it spans AI technical aptitude and behavioral readiness, was built in line with global AI literacy frameworks, and was validated by its in-house I/O psychology team. It works for hiring and for assessing existing employees.

Best fit: Harver customers who want AI readiness next to its cognitive ability, personality and behavioral fit assessments.

Worth knowing: Harver does not publish the assessment's format or length.

iMocha

iMocha's GenAI Readiness: Prompt Engineering Basics test uses scenario-based multiple-choice questions and technical evaluations. It covers prompt structure, prompt chaining, and avoiding ambiguity and hallucination. It can be combined with other skills in a single test, for candidates or existing teams.

Best fit: teams hiring for AI and machine learning roles that depend on prompt engineering.

Worth knowing: iMocha aims the test at roles such as prompt engineer, machine learning engineer and AI product manager.