AI Quality Improvement Apprentice

PROJECTING SUCCESS LTD

Recruiting nationally

Closes in 20 days (Wednesday 30 September 2026 at 11:59pm)

Posted on 10 September 2026

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Contents

Summary

An AI-first development role for someone who is genuinely passionate about emerging technology and wants to apply it to real business challenges.

You will work within the Quality Team while also helping Projecting Success identify practical opportunities to use AI and automation to work smarter and grow.

Wage

£22,000 a year

Minimum wage rates (opens in new tab)

Formal review after 12 months

Training course
Artificial intelligence (AI) and automation practitioner (level 4)
Hours
Our standard working week is Monday to Friday, 9am to 5.30pm

40 hours a week

Start date

Thursday 29 October 2026

Duration

1 year 3 months

Positions available

1

Work

Most of your apprenticeship is spent working. You’ll learn on the job by getting hands-on experience.

What you'll do at work

Quality assurance, data & management information:

  • Maintain quality dashboards, reports and management information to support decision-making.
  • Use AI/automation to analyse quality findings, identify trends and highlight risks, good practice and improvements.
  • Analyse learner data other quality indicators to inform improvements.
  • Produce clear reports and visualisations to help managers monitor quality, learner outcomes and inspection readiness.
  • Create and maintain quality trackers, action plans, self-assessment documents and improvement records.
  • Maintain accurate, timely quality information with effective version control and audit trails.

Inspection, audit & compliance readiness:

  • Prepare for inspections, audits and funding reviews by collating and maintaining evidence.
  • Maintain accessible evidence libraries and inspection-readiness records.
  • Use digital tools and automation to track actions, evidence, deadlines and follow-ups.
  • Identify record gaps or inconsistencies for review by the relevant lead.
  • Produce management information and evidence packs for internal and external quality activity.

AI-assisted quality assurance & assessment:

  • Develop AI-assisted tools to review learner files, assessment decisions and compliance requirements.
  • Test and evaluate AI solutions that improve quality assurance consistency, accuracy and efficiency.
  • Develop AI marking and feedback tools that support assessors while retaining professional judgement, human oversight and quality standards.
  • Develop tools that review written feedback, flag evidence gaps and improve assessment feedback consistency and quality.
  • Develop and test AI-assisted moderation and standardisation tools to improve assessment consistency.
  • Contribute to systems that flag possible inappropriate or unethical AI use for human review; indicators must not be treated as conclusive evidence.
  • Document testing outcomes, limitations, risks and recommended controls for AI-assisted quality tools.

Digital systems & automation:

  • Develop digital systems that improve quality monitoring, reporting, record-keeping and access to management information.
  • Work with quality and curriculum colleagues to identify administrative processes suitable for automation.
  • Map processes and support the design, testing and implementation of controlled automated workflows.
  • Ensure digital quality systems maintain accurate data, audit trails and access controls.
  • Identify opportunities to connect information and reduce duplication across quality and curriculum processes.

Curriculum, teaching & learning innovation:

  • Research emerging AI technologies that could support teaching, learning, assessment, curriculum and quality improvement.
  • Work with curriculum colleagues, tutors and assessors to identify where AI or automation could address practical challenges.
  • Support controlled pilots and gather evidence on effectiveness, risks and limitations.
  • Develop guidance, examples and resources for responsible, effective AI use in teaching, learning and assessment.
  • Share relevant AI developments, learning and good practice.

 

Responsible AI & information handling:

  • Use AI and data in line with Projecting Success policies, data protection, information security and AI governance.
  • Maintain confidentiality.
  • Build human review into AI processes affecting learners, assessment, quality or compliance.
  • Raise concerns about AI bias, inaccuracy, data protection risks or over-reliance on automated outputs.

Where you'll work

Projecting Success are a remote based organisation so this role will be home based with occasional travel requirements in support of our hackathon events - these are communicated well in advance and accommodation/travel are provided if needed.

Training

Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.

Training provider

PROJECTING SUCCESS LTD

Training course

Artificial intelligence (AI) and automation practitioner (level 4)

Understanding apprenticeship levels (opens in new tab)

What you'll learn

Course contents
  • Review, establish, follow and or amend policies and procedures on data and information security.
  • Follow ethical, responsible and safe working practices respecting confidentiality and sensitive organisational matters.
  • Undertake analysis to identify if automation is viable. Including assessing risks such as data quality, process maturity and unintended consequences of AI automation projects, such as the impact on job roles.
  • Engage with non-technical staff to understand their roles, responsibilities, and concerns when automation solutions are proposed and implemented. Adapt approach to support workforce needs when implementing solutions that impacts the workforce.
  • Support with the introduction, adaption, and implementation of change. Contribute to constructive dialogue between leaders and employees about the adoption of AI and automation solutions.
  • Review and complete workflow and process mapping to identify problems or inefficiencies and recommend solutions including pilots, incremental changes and scaling opportunities.
  • Use automation design tools to suit the organisational context to configure, adapt and implement AI or automation solutions, such as conversational agents, text processing AI, workflow automation platforms and cloud based SaaS or PaaS.
  • Create and refine prompts for AI tools, using iterative testing to achieve accurate and useful outputs.
  • Apply analytical and computational techniques using tools and datasets to design, evaluate, and optimise automation solutions.
  • Integrate AI and automation technologies to collect, process, and manage data effectively, enabling intelligent and efficient system operation.
  • Design, integrate, and test digital workflows and AI automation tools using APIs, connectors, or low-or no-code integration methods.
  • Iterate solutions based on testing and feedback to ensure reliability, security, accessibility, and alignment with organisational needs.
  • Identify opportunities to deliver automation. Support leaders in integrating ethical, empathetic approaches when decision-making.
  • Support in the identification and evaluation of opportunities for increased productivity. For example, use of low-or no-code tools, streamlining processes and use of AI platforms.
  • Make evidence based suggestions to support governance, outcomes and facilitate improvement for example cost benefit analysis.
  • Report on productivity and efficiency savings and the opportunities for automation and where applicable when automation does not improve experience or processes.
  • Contribute to sustainable and efficient AI and automation solutions.
  • Support with the delivery of training to technical and non-technical user groups or audiences adapting content and format responding to feedback and organisational context.
  • Contribute to the creation and or adaption of resources such as user guides, training materials, process documents to meet user requirements.
  • Work collaboratively to deploy AI and automation strategies. Support where required to deal with the impact of automation for example retraining, redeployment, or upskilling of affected staff.
  • Undertake data analysis, preparation, and conversion to support automation solutions.
  • Present and communicate information including the translation of technical concepts into accessible materials to support clear dialogue with stakeholders.
  • Work with others to achieve agreed outcomes or outputs. Provide evidence-based analysis and insight to leaders on the likely human impacts of automation projects.
  • Use project management principles, techniques and tools to support the development of clear, balanced communications and briefings, articulating both opportunities and risks.
  • Keep up to date with existing, evolving, emerging technologies and sector trends in AI, automation and technology including methods to evaluate vendor and supplier solutions.
  • Apply ethical and human-centred design principles when scoping, developing, and deploying automation and AI solutions, underpinned by robust governance.
  • Apply technical understanding to help align business needs with technical capabilities, supporting the development of solutions that are scalable, efficient, and aligned with the organisation’s strategic objectives.
  • Undertake assurance activities to evidence responsible AI and automation, including maintaining clear documentation of design and decision-making, contributing to risk assessments, and applying assurance frameworks to support compliance with organisational, regulatory, and ethical standards.
  • Apply algorithmic impact assessment and workforce equality monitoring techniques when scoping, implementing, and reviewing AI and automation projects. Gather and analyse relevant workforce data, identify potential equality risks, and contribute evidence-based recommendations to support fair and inclusive adoption.
  • Review, establish, follow and or amend policies and procedures on data and information security.
  • Follow ethical, responsible and safe working practices respecting confidentiality and sensitive organisational matters.
  • Undertake analysis to identify if automation is viable. Including assessing risks such as data quality, process maturity and unintended consequences of AI automation projects, such as the impact on job roles.
  • Engage with non-technical staff to understand their roles, responsibilities, and concerns when automation solutions are proposed and implemented. Adapt approach to support workforce needs when implementing solutions that impacts the workforce.
  • Support with the introduction, adaption, and implementation of change. Contribute to constructive dialogue between leaders and employees about the adoption of AI and automation solutions.
  • Review and complete workflow and process mapping to identify problems or inefficiencies and recommend solutions including pilots, incremental changes and scaling opportunities.
  • Use automation design tools to suit the organisational context to configure, adapt and implement AI or automation solutions, such as conversational agents, text processing AI, workflow automation platforms and cloud based SaaS or PaaS.
  • Create and refine prompts for AI tools, using iterative testing to achieve accurate and useful outputs.
  • Apply analytical and computational techniques using tools and datasets to design, evaluate, and optimise automation solutions.
  • Integrate AI and automation technologies to collect, process, and manage data effectively, enabling intelligent and efficient system operation.
  • Design, integrate, and test digital workflows and AI automation tools using APIs, connectors, or low-or no-code integration methods.
  • Iterate solutions based on testing and feedback to ensure reliability, security, accessibility, and alignment with organisational needs.
  • Identify opportunities to deliver automation. Support leaders in integrating ethical, empathetic approaches when decision-making.
  • Support in the identification and evaluation of opportunities for increased productivity. For example, use of low-or no-code tools, streamlining processes and use of AI platforms.
  • Make evidence based suggestions to support governance, outcomes and facilitate improvement for example cost benefit analysis.
  • Report on productivity and efficiency savings and the opportunities for automation and where applicable when automation does not improve experience or processes.
  • Contribute to sustainable and efficient AI and automation solutions.
  • Support with the delivery of training to technical and non-technical user groups or audiences adapting content and format responding to feedback and organisational context.
  • Contribute to the creation and or adaption of resources such as user guides, training materials, process documents to meet user requirements.
  • Work collaboratively to deploy AI and automation strategies. Support where required to deal with the impact of automation for example retraining, redeployment, or upskilling of affected staff.
  • Undertake data analysis, preparation, and conversion to support automation solutions.
  • Present and communicate information including the translation of technical concepts into accessible materials to support clear dialogue with stakeholders.
  • Work with others to achieve agreed outcomes or outputs. Provide evidence-based analysis and insight to leaders on the likely human impacts of automation projects.
  • Use project management principles, techniques and tools to support the development of clear, balanced communications and briefings, articulating both opportunities and risks.
  • Keep up to date with existing, evolving, emerging technologies and sector trends in AI, automation and technology including methods to evaluate vendor and supplier solutions.
  • Apply ethical and human-centred design principles when scoping, developing, and deploying automation and AI solutions, underpinned by robust governance.
  • Apply technical understanding to help align business needs with technical capabilities, supporting the development of solutions that are scalable, efficient, and aligned with the organisation’s strategic objectives.
  • Undertake assurance activities to evidence responsible AI and automation, including maintaining clear documentation of design and decision-making, contributing to risk assessments, and applying assurance frameworks to support compliance with organisational, regulatory, and ethical standards.
  • Apply algorithmic impact assessment and workforce equality monitoring techniques when scoping, implementing, and reviewing AI and automation projects. Gather and analyse relevant workforce data, identify potential equality risks, and contribute evidence-based recommendations to support fair and inclusive adoption.

Training schedule

Training will take place at work, via a combination of live sessions taught by our team of subject matter experts, self study & guided exercises and working closely with your allocated Tutor who will support you through the apprenticeship journey.

 

More training information

Projecting Success was established in 2014 to provide specialist data in project management apprenticeships and transform the world of project delivery.

Working with government departments, the wider civil service as well as companies large and small across multiple sectors, Projecting Success has supported many people on their apprentice journey.

We understand the importance of high-quality learning and ensure our tutors are amongst the best the industry has to offer.

The course offerings are carefully selected to provide the apprentice, line manager and the wider organisation with the knowledge to evolve into a forward thinking, more efficient operation.

Requirements

Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.

Skills

  • Communication skills
  • IT skills
  • Attention to detail
  • Organisation skills
  • Creative
  • Initiative
  • Passion for AI & automation

Other requirements

  • Meet the eligibility requirements for a funded apprenticeship in England.
  • Passing right to work checks including a Disclosure and Barring Service (DBS) check.

About this employer

Projecting Success was established in 2014 to provide specialist data in project management apprenticeships and transform the world of project delivery.

Working with government departments, the wider civil service as well as companies large and small across multiple sectors, Projecting Success has supported many people on their apprentice journey. We understand the importance of high-quality learning and ensure our tutors are amongst the best the industry has to offer. The course offerings are carefully selected to provide the apprentice, line manager and the wider organisation with the knowledge to evolve into a forward thinking, more efficient operation.

Projecting Success works with clients to ensure the space and opportunity is created to allow our learners to utilise their learning to the full and optimise their benefit to the wider organisation. Only through the effective embedding of new knowledge will businesses realise the true return on investment offered through our apprenticeships. We have seen this work in practice where learners have returned to their workplaces and quickly introduced new workflows and working practices.

By introducing new methodology, our apprentices have expedited project delivery times and saved thousands of man hours which have been refocused on other important tasks. Talk to us to see how we can support your businesses’ evolution.

https://projectingsuccess.co.uk/ (opens in new tab)

Company benefits

  • 34 annual leave days, inclusive of English bank holidays and Christmas shutdown.
  • Additional day of leave for each full year employed at Projecting Success (up to maximum of 40 days).
  • 2 volunteering days per year.
  • Bonus scheme.
  • Referral bonus.
  • Ongoing training and development.
  • Access to retail discount websites.
  • Free railcard.
  • Free eye tests.
  • Flexible hours.
  • Matched pension contribution.

After this apprenticeship

Your earnings can increase over time with an apprenticeship. Find out about potential future pay (opens in new tab).

We're a growing business in a rapidly developing sector - roles change and are introduced on a regular basis so development opportunities are not restricted to a particular pathway.

Monthly 121 meetings with you line manager, and an annual appraisal, will help steer your development through identifying strengths and areas for development.

Ask a question

The contact for this apprenticeship is:

PROJECTING SUCCESS LTD

The reference code for this apprenticeship is VAC2000052756.

Apply now

Closes in 20 days (Wednesday 30 September 2026 at 11:59pm)