AI Agility (Developer) Assessment to evaluate generative AI readiness in software development
The Mercer AI Agility (Developer) Assessment is a structured assessment designed to evaluate developers’ ability to use generative AI tools in software development workflows. The assessment measures understanding of generative AI capabilities, prompt engineering techniques, and AI-assisted coding workflows used in development tasks. By focusing on development scenarios, the assessment evaluates how developers guide AI tools, validate generated outputs, and ensure alignment with engineering standards and system architecture. It enables organizations to identify developers who can integrate generative AI into development workflows while maintaining software quality and reliability.
About the Mercer AI Agility (Developer) Assessment
The Mercer AI Agility (Developer) Assessment evaluates developers’ readiness to use generative AI tools in software development workflows. As generative AI becomes integrated into coding, debugging, and documentation tasks, developers must understand how to apply these tools while ensuring that generated outputs align with established engineering standards.
This assessment measures the competencies required to use generative AI tools effectively during software development tasks. It evaluates how developers construct prompts, interpret model outputs, validate AI-generated code, and integrate these outputs into existing development pipelines while ensuring alignment with system architecture and development standards.
By providing objective insights into developers’ ability to use generative AI within development workflows, the assessment helps organizations identify professionals who can integrate these tools into software development while maintaining software quality and reliability.
What is inside this framework?
The AI Agility (Developer) Assessment evaluates developers across several competency areas that reflect the practical use of generative AI tools in software development workflows.
Business context and ROI awareness
This section measures developers’ ability to evaluate when generative AI should be used within development processes.
- Use case identification: Recognizing development scenarios where generative AI can improve productivity or output quality.
- Cost and token awareness: Designing AI-assisted workflows that remain efficient and scalable.
Advantages of the AI Agility (Developer) Assessment
The Mercer’s AI Agility (Developer) Assessment helps organizations introduce structure and consistency into evaluating developers’ readiness to work with generative AI tools. As AI-assisted development is becoming more common across software teams, organizations need reliable methods to determine whether developers can use these tools efficiently while maintaining engineering standards and code quality. This assessment provides an objective framework for identifying developers who can apply generative AI effectively in real development workflows.
- Standardized AI capability screening: Provides a consistent framework for evaluating developers’ ability to use generative AI tools across diverse candidate pools.
- Objective validation of AI-assisted development skills: Evaluates capabilities such as prompt engineering, code validation, and AI-assisted development workflows beyond self-reported experience.
- Improved hiring accuracy for AI-enabled development roles: Helps organizations identify developers who can apply generative AI within coding workflows while maintaining software quality and engineering discipline.
- More focused technical interviews: Allows interview stages to shift toward deeper technical discussions focusing on reasoning, design choices, and technical judgment.
- Supports scalable hiring and workforce development: Enables organizations to assess AI readiness consistently as engineering teams adopt AI-assisted development practices.
Use cases of the Mercer AI Agility (Developer) Assessment
Organizations can use the AI Agility (Developer) Assessment across multiple hiring and workforce development initiatives as generative AI tools become integrated into software engineering workflows.
- Hiring developers for AI-assisted software development roles: Identifies candidates who can use generative AI tools effectively within development workflows while maintaining engineering standards.
- Early technical screening: Helps recruiters evaluate candidates’ ability to use generative AI tools before progressing to deeper technical interviews.
- Developer training and upskilling initiatives: Highlights capability gaps in areas such as prompt engineering, AI-assisted coding, and output validation to support targeted training programs.
- Evaluating engineering team readiness for AI adoption: Enables technology leaders to assess how prepared development teams are to incorporate generative AI tools into development workflows.
- Supporting AI-driven workforce transformation: Provides structured insights that help organizations build AI-ready engineering teams as generative AI becomes part of modern development practices.
AI Agility (Developer) Assessment Competency Framework
Get a detailed look inside the test
AI Agility (Developer) Assessment competencies under scanner
Business Context & ROI
LLM Foundations & Concepts
Prompt Engineering & Interaction
Code Verification & Quality
Security Hygiene & Compliance
Competencies:
Helps developers understand where AI or GenAI is actually the right solution, so they apply it only when it adds clear value and avoid using it where traditional methods work better.
It ensures developers design solutions that use GenAI efficiently, so that the applications stay affordable to run and easy to scale as demand grows.
Competencies:
Necessary to ensure that developers pick the right GenAI tool for each business problem, saving time and money by avoiding misapplication.
Essential for tuning the model's behavior to meet specific application requirements and controlling the output generated from the tool
Essential to leverage proprietary knowledge and data, providing ground truth while minimizing factual errors (hallucinations)
Competencies:
Effectively managing and accessing past interactions using external memory is key to controlling costs and ensuring that long, complex conversations with GenAI stay clear and efficient, despite the GenAI’s limited ability to remember information in the short term.
Ensures outputs are relevant and adhere to current project. Essential for increasing code quality, minimizing hallucinations and reducing iterations.
Measuring prompting techniques and using iterative prompting helps software developers guide Gen AI to deliver accurate and efficient results for complex tasks.
Competencies:
Ensures GenAI-generated code follows good engineering practices and avoids common mistakes that cause maintenance issues or production failures.
It ensures that GenAI-generated code is accurate, reliable, and meets quality standards, by focusing on rigorous testing and validation.
1. This focuses on preventing the GenAI tools from generating misleading, biased, or harmful content (often called 'hallucinations'). 2. It ensures that any code suggested by the GenAI does not violate the organization's software licenses or introduce known security vulnerabilities.
This ensures that all GenAI-generated code fits into the existing standards and system design, ensuring seamless integration while also reducing costly rework.
Competencies:
Protects the application from being tricked into generating malicious code or leaking sensitive data via hostile user input.
Mandatory for compliance, ensuring proprietary or sensitive company data is never exposed to public LLM services.
This creates a clear, auditable record of every prompt, data input, and GenAI output. This is essential for compliance checks, forensic analysis after an incident, and guaranteeing accountability
Customize This AI Agility (Developer) Assessment
Flexible customization options to suit your needs
Choose easy, medium or hard questions from our skill libraries to assess candidates of different experience levels.
Add multiple skills in a single test to create an effective assessment. Assess multiple skills together.
Add, edit or bulk upload your own coding questions, MCQ, whiteboarding questions & more.
Get a tailored assessment created with the help of our subject matter experts to ensure effective screening.
The Mercer | Mettl AI Agility (Developer) Assessment Advantage
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Frequently Asked Questions (FAQs)
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The data obtained across industries and verticals of various types of organizations is updated in the Mercer Assessments database periodically. Utmost care is taken to ensure that the newly added data gets incorporated periodically while preparing the reports.
