"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. Clive gave us some best practice ideas and tips to take away. Fast paced but the instructor never lost any of the delegates"
Brian Leek, Data Analyst, May 2022
Redesigning Workflows Around AI
• Apply process mapping techniques to document a current-state workflow
• Identify tasks that are high-effort, repetitive, and AI-automatable
• Distinguish tasks AI should handle from those requiring human judgement
• Design a future-state workflow with clear AI and human responsibilities
• Prototype a redesigned process using no-code or low-code tools
• Estimate time and cost savings from proposed AI interventions
• Identify risks and failure modes in the redesigned process
• Define success metrics and how they will be measured
• Present a redesign proposal to stakeholders with a business case
No-Code AI Automation
Understand the landscape of no-code automation tools and when to use each
• Connect Power Automate or Make to an AI API using HTTP connectors
• Build a trigger-based automation that processes incoming data with AI
• Use AI to classify, summarise, or extract data from emails or documents
• Route outputs to the right system: SharePoint, Teams, email, or CRM
• Handle errors and edge cases without writing code
• Test automations safely using staging environments and test data
• Monitor automation runs and diagnose failures from logs
• Manage automation credentials and connections securely
Writing AI System Specifications
Translate a business problem into a clear AI system requirement
• Define the scope: what the AI will and will not do
• Write effective system prompts and document prompt design decisions
• Specify input and output formats a development team can build to
• Define acceptance criteria and evaluation standards for AI outputs
• Document data requirements: sources, formats, and access permissions
• Identify integration points with existing systems and APIs
• Specify error handling and fallback behaviour in plain language
Why This Works for Government & Blue Chip Clients
The critical differentiator for large organisations is not generic AI knowledge — it is the ability to integrate AI into what they already have. These courses are built around that premise:
• Labs use participants' actual technology environment where possible, not sandboxed demos
• Government-specific constraints (data sovereignty, security classification, procurement rules) are built into relevant modules
• Financial services, healthcare, and public sector examples throughout — not generic case studies
• Everything produced in a lab can be taken away and used in production
"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. Clive gave us some best practice ideas and tips to take away. Fast paced but the instructor never lost any of the delegates"
Brian Leek, Data Analyst, May 2022
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Produce a complete, buildable AI system spec from a business requirement, ready for a dev team.
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Produce a complete, buildable AI system spec from a business requirement, ready for a dev team.
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