Equip your people, at every level, to get the most from AI.

What it covers

• Sessions shaped entirely around the executive's function, priorities, and decisions
• Hands-on work with the AI tools most relevant to that leader's role
• Building the executive's own AI workflow, from inbox to board prep
• A confidential setting to ask anything, at the leader's own pace

What it covers

• The current state of AI in your sector, with named comparables
• The strategic and reputational questions a board should be asking management
• Governance structures and the controls a board should expect to see
• Live discussion calibrated to your organisation's stage and exposure

What it covers

• A diagnostic of where your organisation sits on AI maturity
• Scenarios for the next 18 months and what each means for strategy
• Strategic priorities, investment trade-offs, and capability gaps
• Joint drafting of a leadership statement on the path forward

What it covers

• Pre-workshop diagnostic and stakeholder interviews
• Shaping of the top three to five strategic AI bets
• Owner allocation, milestones, and resource confirmation in the room
• Risk and dependency mapping with accountable owners

What it covers

• What generative AI actually is, in plain terms, with no hand-waving on either side
• The current state of AI across enterprise functions, with real deployments and what they have delivered
• Where AI works well today, where it does not, and where the line moves over the next twelve months
• Risk, governance, and the decisions a leadership team has to own before the technology arrives

What it covers

• What AI is and is not, demonstrated live with real tools
• How AI is reshaping common knowledge work: research, drafting, analysis, summarisation
• The do's and don'ts of using AI at work, including data privacy and information handling
• A guided first interaction with a generative AI assistant

What it covers

• Models, tokens, training, and fine-tuning, and what those words mean for the buyer
• Why hallucinations happen and what controls reduce them
• Retrieval, agents, and the rest of the current vocabulary, in plain language
• Hands-on time with several different AI tools

What it covers

• Emerging AI governance frameworks and global benchmarks, EU AI Act and NIST AI RMF
• Model risk for generative systems, and where it differs from classical model risk
• Data lineage, auditability, and explainability for AI in an enterprise setting
• Building an AI governance committee and the policies it should own

What it covers

• The anatomy of a working prompt, with deliberate practice on each component
• Patterns that compound: chain-of-thought, few-shot, structured output, role anchoring
• Building prompt libraries for repeatable workflows across your function
• Where prompting hits its ceiling and what comes next

What it covers

• Research and synthesis with AI: briefs, scans, comparisons
• Drafting at speed: emails, memos, summaries, board notes
• Data work without code: structured analysis and pattern-finding
• Building a personal AI workflow you actually keep using

What it covers

• Report drafting, reconciliation support, and anomaly detection with AI
• Document-heavy finance workflows: invoices, statements, filings
• Forecasting and variance analysis with AI assistance
• Where to keep a human in the loop, and why

What it covers

• Operational data summarisation and exception handling
• Supplier and supply-chain risk surfacing with AI
• Demand and inventory insight from historical data
• Practical automation of repeatable operational work

What it covers

• Content production at speed with brand and voice integrity preserved
• Account research and pre-meeting briefs in minutes
• Proposal and sales-enablement acceleration
• Measuring and improving AI-generated outputs over time

What it covers

• Fairness, transparency, accountability, and privacy as concrete design choices
• Bias detection and mitigation in real data and real models
• Human-in-the-loop design: when, where, and how much
• Operationalising AI principles inside an established enterprise

What it covers

• Designing AI into the close, reporting, and planning cycles
• Document intelligence across the finance document estate
• Forecasting models and their governance
• Building the finance function's own AI roadmap

What it covers

• Supplier intelligence and risk monitoring at scale
• Demand sensing and inventory optimisation with AI
• Contract and document analysis across procurement
• Prioritising AI use cases across the supply chain

What it covers

• Operational data analysis and exception management
• Predictive insight from equipment and process data
• Quality and inspection support with AI
• Sequencing AI adoption across operations

What it covers

• How document intelligence reads, classifies, and extracts at scale
• Turning paper-bound processes into structured, searchable workflows
• The efficiency and sustainability case for digitisation
• Identifying the highest-value document workflows to tackle first

What it covers

• Where AI is changing customer experience across sectors
• Conversational AI, sentiment, and intelligent routing in practice
• Working alongside an AI assistant in customer-facing workflows
• What the front line should automate, escalate, and supervise

What it covers

• Building functional AI agents on accessible no-code platforms
• Connecting agents to the everyday tools your team already uses
• Designing safe, useful automations with the right human checkpoints
• Knowing what to build yourself and when to call in a technical team

What it covers

• Spotting the automation opportunities hiding in your daily work
• Building no-code automations across common business tools
• Adding AI judgement steps that simple automation cannot handle
• Measuring the time you get back

What it covers

• Building custom assistants trained on your own content
• Grounding assistants in your documents, policies, and procedures
• Sharing assistants safely across a team
• Maintaining and improving them over time

What it covers

• Deeper hands-on fluency across the AI tools your organisation uses
• Leading AI adoption and good practice within a team
• Identifying and shaping practical use cases on the ground
• Acting as the bridge between business teams and AgentiQ's specialists