| Date | Venue | Fees | |
|---|---|---|---|
| 03 - 07 Aug 2026 | London - UK | $ 5,950 | |
| 16 - 20 Nov 2026 | Amsterdam - The Netherlands | $ 5,950 | |
| 15 - 19 Mar 2027 | London - UK | $ 5,950 | |
| 02 - 06 Aug 2027 | London - UK | $ 5,950 | |
| 15 - 19 Nov 2027 | Amsterdam - The Netherlands | $ 5,950 |
Introduction
This GLOMACS Artificial Intelligence Enabled Strategic Decision-Making training course enables leaders to improve the quality, speed, and auditability of strategic decisions using Artificial Intelligence. Participants learn Decision Intelligence methods to frame decisions, surface assumptions, test evidence, and document trade-offs in a way that is transparent and defensible.
The training course strengthens scenario planning, forecasting, and risk analysis so leaders can make better choices under uncertainty. Alongside this, delegates build practical proficiency with Large Language Models such as OpenAI ChatGPT, Microsoft Copilot, and Google Gemini as decision-support tools—learning where they add value and where they can mislead. The training course closes with a forward-looking view of how Generative AI and Agentic AI will reshape decision workflows, and what governance, controls, and human-review steps are required to scale safely.
This Artificial Intelligence Enabled Strategic Decision Making training course will highlight:
- Decision Intelligence foundations for executive choices
- Large Language Models (LLM) decision support: structure, critique, validation
- Evidence packs, KPIs, and analytical reasoning
- Scenario planning, forecasting, and risk adjustment
- Governance, audit trails, and safe agentic trajectory
Objectives
At the end of this Artificial Intelligence Enabled Strategic Decision Making training course, you will learn to:
- Frame strategic decisions using Decision Intelligence
- Apply LLMs for structured decision support
- Evaluate evidence quality and uncertainty
- Build scenarios, forecasts, risk adjustments
- Establish governance and auditable decision trails
Training Methodology
The Artificial Intelligence Enabled Strategic Decision Making training course blends concise instruction with structured discussion and facilitated workshops. Participants apply Decision Intelligence frameworks to real decisions, using guided exercises to build evidence packs, evaluation rubrics, scenarios, and governance artefacts. Practical LLM labs develop repeatable prompt patterns for framing, critique, and synthesis, with peer review to strengthen clarity, assumptions, and auditability.
Organisational Impact
Organisations will improve decision speed, consistency, and defensibility while managing AI-related risk.
- Faster, more consistent strategic decisions
- Improved transparency, auditability, compliance
- Better risk-adjusted choices and resilience
- Stronger evidence packs and KPI discipline
- Reduced bias and decision blind spots
- Safe scaling of GenAI and agentic workflows
Personal Impact
Participants will gain practical tools and confidence to make and document high-quality decisions with AI support.
- Practical templates to structure decisions
- Confidence using LLMs responsibly at work
- Stronger analytical reasoning and judgement
- Ability to run scenarios and pre-mortems
- Clear documentation for executive scrutiny
- Enhanced leadership credibility and growth
Who should Attend?
This Artificial Intelligence Enabled Strategic Decision Making training course suits leaders who sponsor or make strategic decisions under uncertainty. It benefits those accountable for performance, risk, and governance.
This GLOMACS Artificial Intelligence Enabled Strategic Decision Making training course is suitable to a wide range of professionals but will greatly benefit:
- Strategy, transformation, and business planning professionals
- Operational leaders driving performance and delivery
- Finance, investment, and commercial decision-makers
- Risk, compliance, audit, and assurance professionals
- Digital, data, analytics, and technology leaders
Decision Intelligence Foundations and Large Language Model Decision Support
- Programme and portfolio management professionals
- Decision quality: speed, consistency, transparency
- Decision framing, assumptions, and trade-offs
- Evidence requests and decision trail design
- LLMs as decision support: strengths and limits
- Validation practices: uncertainty and challenge prompts
- Generative AI to Agentic AI in decision workflows
Data, Evidence, and Analytical Reasoning for Strategic Decisions
- Evidence quality: bias, completeness, timeliness
- KPIs, leading indicators, signal vs noise
- AI-enabled analysis and insight generation
- Evidence pack design for strategic decisions
- Option evaluation rubrics: criteria and weighting
- Separating facts, assumptions, and judgement
Scenario Planning, Forecasting, and Risk-Adjusted Choices
- Scenario drivers, uncertainties, and stress testing
- Forecasting ranges, error, and confidence
- Risk framing: probability, impact, tail risks
- Testing options across base, upside, downside cases
- Pre-mortems to surface failure modes
- Mitigation planning and risk-adjusted recommendations
Bias, Ethics, and Governance in AI-Augmented Decisions
- Common decision biases and debiasing methods
- How AI can amplify or reduce bias
- Ethical, privacy, and compliance considerations
- Governance for AI-assisted decision-making
- Audit trails: sources, prompts, outputs, judgement
- Human review steps and escalation thresholds
Agentic AI for Decision Workflows and Executive Capstone
- Agentic AI: monitoring, proposing, acting within limits
- Control design: permissions, monitoring, kill switches
- Exception handling and incident response
- Operationalizing at scale: measurement and improvement
- Pilot design for GenAI decision support with controls
- Agentic decision workflow trajectory planning
- Upon successful completion of this training course, GLOMACS Certificate will be awarded to the delegates. Continuing Professional Education credits (CPE): In accordance with the standards of the National Registry of CPE Sponsors, one CPE credit is granted per 50 minutes of attendance
.webp?v=1782980860)
