• Dânia Meira

AI Guild Accreditation: The competency standard

Updated: Jun 23

Accreditation is the AI Guild action and process of recognizing a data professional as qualified to perform her or his profession to the highest quality standard.

Requirements for accreditation

Accreditation is available to all industry practitioners, e.g. employed, freelance, or entrepreneur. To be eligible for accreditation, the candidate must meet the following requirements:

  • Four or more years of professional experience.

  • Evidence for all elements of the competency standard.

The competency standard

AI competency standard by the AI Guild
Perform your profession to the highest quality standards

Accreditation means recognizing a practitioner as qualified to perform at the highest standards for technical competence, ethical behavior, business impact, and benefits to society.


The competency standard covers the following areas:


  1. Data proficiency

  2. Advancing AI Adoption

  3. Professional contribution

  4. Personal capacity


Data proficiency

  • Skills: Be competent across the product lifecycle. Demonstrate the breadth of skills as a professional (e.g., data and software tools from data generation to model deployment).

  • Expertise: Hold deep domain expertise. Demonstrate repeated and improved work with a set of methods in a particular domain that makes you an expert (e.g., Computer Vision engineer in mobility, Data Scientist in fraud detection).

  • Portfolio: Have a track record to senior level and beyond. Prove that you co-built a deployed product or solution as an expert over a more extended period.


Advancing AI adoption

  • Value: Solution(s) implemented that create value for the customer or client. Communicate how the solution improved or changed the life of the customer or client, including any metrics.

  • Impact: Solutions deployed have a business impact. Measurable impact on the bottom line, e.g., revenue, savings, efficiency.

  • Innovation: Solve a problem or start something new. Problem-solving with algorithms, data, and related tools, e.g., improving an existing solution, automating a process, exploration of new topics/challenges.

  • Quality: Provide evidence of reproducibility, transparency, appropriateness of your solution, and its safety. For example, code quality (efficiency, the accuracy of tools); model quality (the plausibility of assumptions); protection from bias or the resolution thereof; safety standards and regulations met.

Professional contribution

  • Development: Investment in your continuous professional development. Track record of your professional development, e.g., training, certification, teaching, mentorship, coaching.

  • Communication: Communicate on the product, work, and profession clearly with technical and non-technical audiences. The capacity to communicate with business stakeholders, external stakeholders, and the public (e.g., public media, teaching, business meetings, company board).

  • Knowledge sharing: Share your insights and experience. Track record of your contribution to the field by coding, video, writing, speaking, or similar.

Personal capacity

  • Ethics: Demonstrate commitment in behavior and algorithms to privacy, fairness, and diversity. Instances where (your) ethical behavior is relevant in teamwork, research, product development, or deployment.

  • Decision-making: Show the independence of your professional judgment, and take responsibility. Instances where (your) decision-making is relevant in teamwork, research, product development, or deployment.

  • Team, including leadership: Be someone that people want to work with again. Track record of your behavior and teamwork as a senior, lead, principal, manager, and so on.

Submitting your evidence for accreditation

The accreditation validates your expertise. You prepare for the accreditation through your professional experience, contribution, and development.


For accreditation by the AI Guild, we ask you to submit three pieces of evidence. The evidence will be assessed by the AI Guild and reviewed by experts (your peers). After an independent review of your submission by two experts, we invite you for a 2-hour interview.


The pieces of evidence you are requested to submit are as follows.

  1. An up-to-date CV shows your skills’ breadth and depth with a supporting portfolio (data proficiency).

  2. A narrative as audio, video, or text file, naming and describing at least two use cases (product or solution) to which you contributed significantly (advancing AI adoption and personal capacity, typically based on the portfolio).

  3. A chronological list of your professional contributions.

If you have questions, please set an appointment with the AI Guild online.

Start your accreditation

90 days from submission to accreditation. Get recognized as a practitioner qualified to perform at the highest standards for technical competence, ethical behavior, business impact, and benefits to society. Submit anytime for accreditation by using this form.


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Competency standard for accreditation by
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