{"product_id":"mastering-the-next-generation-of-ai-prompt-engineering-for-internal-audit","title":"Mastering the Next Generation of AI Prompt Engineering for Internal Audit","description":"\u003cp\u003e\u003cem\u003eFrom Advanced Prompting to Agentic AI, Deep Research and AI-Powered Audit Workflows\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003ePrerequisite\/ Requirement:\u003c\/strong\u003e Completion of Parts 1 and 2 of the Audit Training courses, or passing our individual ARC front-up assessment test before the start of the training course\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSuggested training duration:\u003c\/strong\u003e Three half‑day sessions (total 1.5 days)\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003eArtificial Intelligence is evolving rapidly, and so is the way Internal Auditors need to work with it. The latest generation of AI models like ChatGPT capabilities is moving far beyond simple question-and-answer interactions. Advanced reasoning, large-context analysis, Deep Research, persistent Projects, connected data sources and increasingly agentic workflows are fundamentally changing what auditors can delegate to AI. As a result, professional Prompt Engineering is evolving from writing instructions into the systematic design of AI-supported audit tasks.\u003cbr\u003eFor Internal Audit professionals, this means that Prompt Engineering is becoming a strategic capability. The question is no longer simply how to formulate a good prompt. The real challenge is to understand how to structure a complex audit task, select the appropriate reasoning level, provide the right context, define evidence requirements, control the workflow and determine where human judgment must remain in the loop.\u003cbr\u003eThis advanced training provides an overview of the latest developments in teamwork with AI and translates them into practical Prompt Engineering techniques for Internal Audit. Participants will learn how to move from traditional prompting toward advanced approaches such as reasoning-effort prompting, plan-first prompting, context engineering, evidence-pack prompting, trusted-source research, prompt chaining, self-review and AI quality gates.\u003cbr\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eLearning Objectives\u003c\/strong\u003e\u003cbr\u003eBy the end of the training, participants will be able to:\u003cbr\u003e\u003c\/p\u003e\n\u003col\u003e\n\u003cli\u003eDistinguish between traditional prompting, advanced Prompt Engineering and AI workflow design.\u003c\/li\u003e\n\u003cli\u003eSelect an appropriate reasoning level for different audit tasks.\u003c\/li\u003e\n\u003cli\u003eDesign prompts using advanced techniques such as plan-first prompting, context engineering and prompt chaining.\u003c\/li\u003e\n\u003cli\u003eUnderstand the latest developments in ChatGPT and their relevance for Internal Audit.\u003c\/li\u003e\n\u003cli\u003eStructure large evidence packages and complex audit contexts for AI-supported analysis.\u003c\/li\u003e\n\u003cli\u003eDesign Deep Research prompts using source hierarchies, trusted sources and explicit research criteria.\u003c\/li\u003e\n\u003cli\u003eApply outcome-based prompting to complex multi-step audit tasks.\u003c\/li\u003e\n\u003c\/ol\u003e\n\u003cp\u003e\u003cstrong\u003eAudit Training Agenda \u003c\/strong\u003e\u003c\/p\u003e\n\u003col\u003e\u003c\/ol\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cb\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e1. Introduction – The New AI Reality for Internal Audit\u003c\/span\u003e\u003c\/b\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cul style=\"margin-top: 0cm;\" type=\"disc\"\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l1 level1 lfo1; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eFrom GenAi, e.g. ChatGPT as a tool to AI as a working environment\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l1 level1 lfo1; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003eWhy Prompt Engineering is evolving\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l1 level1 lfo1; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eFrom individual productivity to AI-enabled audit workflows\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l1 level1 lfo1; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eThe changing role of the auditor in an increasingly agentic environment\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cb\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e2. AI Challenge – Test Your AI Knowledge\u003c\/span\u003e\u003c\/b\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eA dynamic and competitive Game to activate existing knowledge, identify learning gaps and introduce key concepts in an engaging way.\u003c\/span\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eCategory 1 – AI Foundations \u0026amp; Key Terminology\u003c\/li\u003e\n\u003cli\u003eCategory 2 – LLMs \u0026amp; Their Tells\u003c\/li\u003e\n\u003cli\u003eCategory 3 – The Prompting Frameworks\u003c\/li\u003e\n\u003cli\u003eCategory 4 – Advanced Prompting Techniques \u0026amp; Logic\u003c\/li\u003e\n\u003cli\u003eCategory 5 – Agentic AI \u0026amp; External Data Integration\u003cbr\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cb\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e3. Advanced Reasoning – Prompting the “Thinking” Process\u003c\/span\u003e\u003c\/b\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cul style=\"margin-top: 0cm;\" type=\"disc\"\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l7 level1 lfo2; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003eChoosing the appropriate reasoning effort\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l7 level1 lfo2; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eMatching reasoning intensity to audit complexity\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l7 level1 lfo2; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003ePlan-first prompting\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l7 level1 lfo2; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eFrom “give me an answer” to “develop, challenge and validate the approach”\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cb\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e4. Context Engineering – The New Core of Prompt Engineering\u003c\/span\u003e\u003c\/b\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cul style=\"margin-top: 0cm;\" type=\"disc\"\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l6 level1 lfo3; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eFrom clever prompts to high-quality context\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l6 level1 lfo3; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003eWorking with large evidence packages\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l6 level1 lfo3; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e256K-token context and what it means for auditors\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cb\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e5. Projects, Memory and Persistent Audit Context\u003c\/span\u003e\u003c\/b\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cul style=\"margin-top: 0cm;\" type=\"disc\"\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l2 level1 lfo4; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eBuilding a persistent audit knowledge environment\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l2 level1 lfo4; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003eSource once, reuse many times\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l2 level1 lfo4; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eMaintaining methodology, prior analyses and reusable knowledge\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cb\u003e\u003cspan lang=\"DE\"\u003e6. Deep Research for Internal Audit\u003c\/span\u003e\u003c\/b\u003e\u003cspan lang=\"DE\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cul style=\"margin-top: 0cm;\" type=\"disc\"\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l9 level1 lfo5; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eDesigning a research strategy instead of simply asking a question\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l9 level1 lfo5; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003eTrusted-source prompting\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l9 level1 lfo5; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003eRegulatory and supervisory research\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cb\u003e\u003cspan lang=\"DE\"\u003e7. From Prompting to Workflow Engineering\u003c\/span\u003e\u003c\/b\u003e\u003cspan lang=\"DE\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cul style=\"margin-top: 0cm;\" type=\"disc\"\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l3 level1 lfo6; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003eOutcome-based prompting\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l3 level1 lfo6; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eDefining goals, constraints, deliverables and acceptance criteria\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l3 level1 lfo6; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003ePrompt chaining versus the “Mega-Prompt”\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cb\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e8. From AI Assistant to AI Audit Workforce\u003c\/span\u003e\u003c\/b\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cul style=\"margin-top: 0cm;\" type=\"disc\"\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l4 level1 lfo7; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003eAI Agent prompting\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l4 level1 lfo7; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eSpecialised audit agents along the audit value chain\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cb\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e9. Multi-Agent Prompting \u0026amp; the Future Audit Workflow\u003c\/span\u003e\u003c\/b\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cul style=\"margin-top: 0cm;\" type=\"disc\"\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l8 level1 lfo8; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003eAI workforce orchestration\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l8 level1 lfo8; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eCombining research, analysis and QA agents\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l8 level1 lfo8; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eThe future role of the auditor as AI Engagement Manager\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cb\u003e\u003cspan lang=\"DE\"\u003e10. From Training to Implementation\u003c\/span\u003e\u003c\/b\u003e\u003cspan lang=\"DE\"\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cul style=\"margin-top: 0cm;\" type=\"disc\"\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l0 level1 lfo9; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eWhich techniques can be implemented immediately?\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l0 level1 lfo9; tab-stops: list 36.0pt;\"\u003e\u003cspan style=\"mso-ansi-language: EN-GB;\"\u003eWhich audit processes are best suited for advanced prompting?\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l0 level1 lfo9; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003eQuick wins versus strategic AI initiatives\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l0 level1 lfo9; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003ePersonal action plan\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"mso-list: l0 level1 lfo9; tab-stops: list 36.0pt;\"\u003e\u003cspan lang=\"DE\"\u003eKey takeaways\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"ARC Institute","offers":[{"title":"Default Title","offer_id":54719029772625,"sku":null,"price":890.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1058\/4807\/8673\/files\/MasteringtheNextGenerationofAIPromptEngineeringforInternalAudit.png?v=1787920314","url":"https:\/\/arc-institute.com\/products\/mastering-the-next-generation-of-ai-prompt-engineering-for-internal-audit","provider":"ARC Institute","version":"1.0","type":"link"}