Reference handout · ST1512 v2.1 · Level 4

The AI & Automation Practitioner standard, in full.

Every knowledge, skill and behaviour in the Skills England Level 4 standard (ST1512), the 15 occupational duties, and how TESS teaches each across 12 modules. Built for employers writing the business case, line managers supporting an apprentice, and learners preparing for End Point Assessment. Print it, share it, bring it to a call.

See the apprenticeship → Jump to the KSBs ↓
Level 4
Standard
18 months
To gateway
£18,000
Max funding
29 / 29 / 6
K / S / B
No coding
Low / no-code
Ofqual
EQA provider

The AI & Automation Practitioner (ST1512) is a Level 4 apprenticeship standard, approved by Skills England for delivery from December 2025 and updated to v2.1 in May 2026. It trains people, with no coding required, to spot inefficient processes, build AI and automation solutions with low-code and no-code tools, and do it safely, ethically and with proper governance. The whole standard is defined by 64 statements: 29 knowledge areas (K1 to K29), 29 skills (S1 to S29) and 6 behaviours (B1 to B6), organised around 15 occupational duties. Here is the complete picture.

Plain English first: a practitioner finds the repetitive work that slows a business down, then designs, builds, tests and documents an automation or AI workflow that fixes it, keeping a human in the loop and the governance tight. The End Point Assessment is built on a real automation they have shipped for their employer, plus a one-hour professional conversation, graded Pass or Distinction. No 10,000-word essays. (More on that in how the apprenticeship is actually assessed.)
The standard in full

Knowledge, Skills & Behaviours

The 64 statements every apprentice is measured against, exactly as set out in the Skills England standard.

KnowledgeK1 to K29
K1The role of organisational leadership in responsible AI adoption, including setting values, policy and strategy. The business case for ethical AI adoption, including reputational risk, staff morale and long-term sustainability.
K2Legal and regulatory frameworks including employment rights, equality, responsible automation, data protection and GDPR. Ethical principles and professional standards such as fairness, transparency and accountability.
K3The potential social and economic impacts of AI and automation on different roles, particularly for non-technical staff, including change management principles.
K4Approaches for identifying and implementing incremental change, including piloting and evaluating solutions against organisational constraints such as budget, time and resources.
K5Methods to identify opportunities to enhance productivity, such as improving processes, reducing waste, increasing satisfaction or optimising outcomes.
K6The importance of designing AI and automation systems that augment rather than replace human work, where feasible.
K7The capabilities, benefits and risks of automation, AI and digital tools, including responsible use, ethical considerations and the potential impact on the workforce.
K8The capabilities, risks and implications of on-premise, cloud-based and third-party solutions.
K9AI and automation concepts, models and limitations. The impact adoption may have on workplace culture and wellbeing.
K10Sources of error and algorithmic bias, including how they are affected by choice of dataset and methodology, and the impact on user and organisation. Fairness metrics and mitigation approaches.
K11User requirements when designing and implementing AI and automation solutions, including accessibility considerations.
K12Product development lifecycle including UX principles such as user-centred design, data-informed design and experimental testing.
K13How to assess the viability of solutions: testing and evaluating, using test data and results, feasibility (time, cost, data quality, process maturity) and user testing.
K14Principles and application of testing methodologies in practice.
K15Principles of human oversight and human-AI collaboration to achieve shared outcomes.
K16Feedback and evaluation loops to improve systems, processes, productivity and performance, including human-in-the-loop safeguards.
K17Principles for designing sustainable solutions to support organisational strategies and objectives.
K18Governance principles to ensure accountability and compliance, including identifying system vulnerabilities and mitigating threats to assets, data and cyber security.
K19Engagement and training approaches for non-technical staff to understand their roles, responsibilities and concerns when AI automation is proposed, including best-practice delivery methods.
K20Methods to develop resources such as manuals, short explainers, chat-based guidance, interactive wikis and training materials.
K21Strategies for inclusive communication with stakeholders from diverse and non-technical backgrounds.
K22Collaborative working principles to explore AI and automation solutions and implement prototypes, pilots or proofs of concept.
K23Mitigation strategies for post-deployment issues such as overreliance and automation bias.
K24Principles to support project and change management delivery.
K25Approaches to maintaining up-to-date knowledge of existing, evolving and emerging technologies and sector trends (peer learning, online forums, AI tool release notes).
K26The benefits of wellbeing and safe working practices.
K27Methods for assuring compliance in AI and automation projects: documenting model decision-making, structured risk assessments, aligning with recognised AI assurance and governance frameworks. The importance of auditability, transparency and accountability.
K28Algorithmic impact assessment and workforce equality monitoring, including identifying, assessing and mitigating disproportionate impacts on different workforce groups. Organisational responsibilities under equality and employment law.
K29Long-term monitoring of AI and automation solutions, including detecting and mitigating model drift, emerging bias, degraded performance and security vulnerabilities.
SkillsS1 to S29
S1Review, establish, follow and amend policies and procedures on data and information security.
S2Follow ethical, responsible and safe working practices, respecting confidentiality and sensitive organisational matters.
S3Analyse whether automation is viable, including assessing risks such as data quality, process maturity and unintended consequences such as impact on job roles.
S4Engage with non-technical staff to understand roles, responsibilities and concerns when automation is proposed, adapting approach to support workforce needs.
S5Support the introduction, adaptation and implementation of change. Contribute to constructive dialogue between leaders and employees about adoption.
S6Review and complete workflow and process mapping to identify problems or inefficiencies and recommend solutions, including pilots, incremental changes and scaling.
S7Use automation design tools to configure, adapt and implement AI or automation solutions, such as conversational agents, text-processing AI, workflow automation platforms and cloud SaaS or PaaS.
S8Create and refine prompts for AI tools, using iterative testing to achieve accurate, useful outputs.
S9Apply analytical and computational techniques using tools and datasets to design, evaluate and optimise automation solutions.
S10Integrate AI and automation technologies to collect, process and manage data effectively for intelligent, efficient system operation.
S11Design, integrate and test digital workflows and AI automation tools using APIs, connectors or low/no-code integration methods.
S12Iterate solutions based on testing and feedback to ensure reliability, security, accessibility and alignment with organisational needs.
S13Identify opportunities to deliver automation. Support leaders in integrating ethical, empathetic approaches to decision-making.
S14Identify and evaluate opportunities for increased productivity, e.g. low/no-code tools, streamlining processes and use of AI platforms.
S15Make evidence-based suggestions to support governance and outcomes, e.g. cost-benefit analysis.
S16Report on productivity and efficiency savings and on opportunities for automation, including where automation does not improve experience or process.
S17Contribute to sustainable and efficient AI and automation solutions.
S18Support delivery of training to technical and non-technical audiences, adapting content and format and responding to feedback and context.
S19Contribute to creating and adapting resources such as user guides, training materials and process documents.
S20Work collaboratively to deploy AI and automation strategies, supporting the impact of automation, e.g. retraining, redeployment or upskilling of affected staff.
S21Undertake data analysis, preparation and conversion to support automation solutions.
S22Present and communicate information, translating technical concepts into accessible materials for clear stakeholder dialogue.
S23Work with others to achieve agreed outcomes. Provide evidence-based analysis to leaders on the likely human impacts of automation.
S24Use project management principles, techniques and tools to develop clear, balanced communications articulating both opportunities and risks.
S25Keep up to date with existing, evolving and emerging technologies and trends, including methods to evaluate vendor and supplier solutions.
S26Apply ethical and human-centred design principles when scoping, developing and deploying solutions, underpinned by robust governance.
S27Apply technical understanding to align business needs with technical capabilities, supporting scalable, efficient, strategically aligned solutions.
S28Undertake assurance activities to evidence responsible AI and automation: clear documentation of design and decisions, contributing to risk assessments, applying assurance frameworks.
S29Apply algorithmic impact assessment and workforce equality monitoring, gathering and analysing workforce data, identifying equality risks and recommending fair, inclusive adoption.
BehavioursB1 to B6
B1Demonstrates empathy by actively considering the perspectives and concerns of staff impacted by AI-driven change. Acts responsibly, balancing efficiency goals with fairness to employees.
B2Maintains professionalism and upholds confidentiality when discussing sensitive workforce impacts, showing respect for individual contributions.
B3Demonstrates confidence in sharing concerns or alternative perspectives, even under pressure to deliver efficiencies.
B4Balances respect for leadership decisions with advocacy for employees.
B5Supports leaders to consider the impact of AI automation adoption, not just immediate organisational gains.
B6Shows curiosity and initiative, experimenting with AI and automation while ensuring exploration is safe, ethical and mindful of potential impacts.
The 15 duties

What a practitioner actually does

The occupational duties the KSBs serve, in plain English.

DutyIn practice
1 & 3Identify opportunities for automation to drive improvement and cost savings, and evaluate the AI and automation tools and platforms available.
2Provide input into solutions that go beyond low/no-code, collaborating with technical teams when needed.
4 & 5Facilitate design and solution workshops, then simplify processes and design workflows that exploit AI and automation.
6 & 7Configure and adapt low/no-code tools, and apply AI solutions such as chatbots, summarisation and SaaS/PaaS automation to add value.
8Develop, document and test integrated digital workflows, producing technical and end-user materials.
9 & 10Keep stakeholders informed, and provide training and user guides for the tools adopted.
11 & 12Support change management and adoption, then monitor and refine automations using end-user feedback.
13Measure and report on productivity, efficiency and value savings.
14Ensure compliance and support digital ethics, security and privacy: governance, auditing, explainability and documented decision-making.
15Keep up to date with AI automation trends, opportunities and risks to inform current and future practice.
How TESS teaches it

The standard, mapped to 12 modules

The KSBs are the official Skills England standard. The mapping below is how TESS sequences delivery across the programme, taught through Claude, Claude Projects and no-code automation tools. Build is front-loaded: a live automation by month 3, a working AI agent on your data by month 4.

ModulePrimary KSBs covered
M00 · Onboarding & AI DiagnosticK5, K25 · S6 · B6
M01 · AI FoundationsK6, K7, K9, K15 · S8
M02 · Process DiscoveryK4, K5, K12 · S3, S6, S14
M03 · Workflow AutomationK11, K13, K14 · S7, S9, S11
M04 · Agentic AIK8, K22 · S7, S10, S11, S12
M05 · AI Integration & AssuranceK13, K18, K27 · S11, S12, S28
M06 · Data Decisions & Data LawK2, K8, K10 · S1, S21
M07 · Designing Responsible AIK1, K6, K10, K26, K28 · S2, S26, S29 · B1, B2, B4, B5
M08 · Pilot, Test & AssureK13, K14, K16, K23, K29 · S12, S28 · B3
M09 · Leading AI AdoptionK3, K19, K20, K21, K24 · S4, S5, S18, S19, S20, S22, S23 · B1, B3, B4
M10 · AI Strategy, Scaling & ValueK1, K17, K18 · S13, S15, S16, S17, S24, S27 · B5
M11 · Applied AI Mastery (Capstone)Synthesis across all KSBs, plus the End Point Assessment project
A note on the mapping: the knowledge, skills and behaviours are Skills England’s official standard and are fixed. The module breakdown is TESS’s delivery approach and is indicative; many KSBs are revisited and assessed across more than one module, and the capstone consolidates the lot through a real workplace project.
See how it’s taught through Claude →

Thinking about putting someone through the standard?

Tell us the role and the repetitive work in their week. We’ll show you what their automation and AI agent could look like, map it to these KSBs, and sort the funding (100% for SMEs, or drawn from the levy). 25-minute Teams call, response within one working day.

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Source: Skills England occupational standard, Artificial intelligence (AI) and automation practitioner (ST1512), version 2.1, updated 22 May 2026. KSB text is reproduced from the standard under the Open Government Licence; module mapping is TESS Group’s delivery approach. Related reading: the full L4 employer guide, how it is assessed, and the Claude Apprenticeship.