Introduction

Artificial intelligence is transforming how organisations interpret information, evaluate options, and make high-impact business decisions. As uncertainty increases and data volumes expand, leaders and managers must make faster, more accurate, and more defensible decisions while still protecting performance, accountability, and governance expectations. Traditional approaches often struggle to keep pace with real-time market shifts, operational complexity, and the demand for evidence-based judgement.

The Smart Decision Making with Artificial Intelligence (AI) training course provides a practical, business-focused approach to using AI tools, analytics, and decision-support systems to improve decision quality and measurable outcomes. Participants learn how AI augments managerial judgement, strengthens forecasting and planning, and improves performance management across strategic, operational, and financial decision contexts. The course also addresses governance and ethical considerations to ensure AI-driven insights are used responsibly and consistently.

Key focus areas include:

Key Learning Outcomes

At the end of this Smart Decision Making with Artificial Intelligence (AI) training course, participants will be able to:

Training Methodology

This Smart Decision Making with Artificial Intelligence (AI) training course combines executive-level explanation with practical scenario work, decision exercises, and applied case analysis. Participants practise interpreting AI-supported insights, pressure-testing assumptions, and documenting defensible decisions aligned with business priorities and governance expectations.

Smart Decision Making with Artificial Intelligence (AI)

Who Should Attend?

This Smart Decision Making with Artificial Intelligence (AI) training course is ideal for professionals seeking to:

  • Senior managers and executives
  • Strategy, planning, and business development professionals
  • Finance, operations, and performance management leaders
  • Business analysts and decision-makers
  • Digital transformation and innovation leaders
  • Project and programme managers
  • Professionals responsible for improving decision quality and business outcomes

Course Outline

Day 1

AI Foundations for Business Decision-Making

  • Introduction to Artificial Intelligence in business environments
  • Evolution of decision-making: from intuition to data-driven AI
  • Key AI concepts explained for non-technical professionals
  • Descriptive, predictive, and prescriptive analytics
  • AI-enabled decision-support systems
  • Identifying decision-making challenges AI can solve
Day 2

Data, Analytics, and AI-Driven Insights

  • The role of data in AI-powered decisions
  • Data quality, data governance, and data readiness
  • Turning raw data into meaningful business insights
  • AI-powered dashboards and business intelligence tools
  • Real-time analytics for faster decision-making
  • Using AI to reduce uncertainty and bias in decisions
Day 3

AI Applications for Business Performance Improvement

  • AI in strategic planning and competitive analysis
  • Improving operational efficiency with AI
  • AI-driven financial analysis and performance forecasting
  • Enhancing customer experience and customer decision journeys
  • AI for supply chain, procurement, and resource optimization
  • AI in risk management and scenario analysis
  • Measuring the impact of AI on business performance
Day 4

Predictive & Prescriptive AI for Smarter Decisions

  • Predictive analytics for forecasting business outcomes
  • Prescriptive analytics for optimization and decision recommendations
  • AI-based scenario modeling and “what-if” analysis
  • AI in budgeting, investment decisions, and cost optimization
  • Decision automation vs. decision augmentation
  • Integrating AI recommendations into managerial judgment
  • Managing risks and limitations of AI-driven decisions
Day 5

Implementing AI for Sustainable Decision Excellence

  • Building an AI-driven decision-making culture
  • Aligning AI initiatives with business strategy
  • Selecting and evaluating AI tools and vendors
  • Change management and workforce readiness for AI adoption
  • AI governance, ethics, and responsible decision-making
  • Measuring ROI and performance impact of AI initiatives
  • Developing an AI adoption roadmap for decision-making excellence

International Standards & Professional Alignment

Our training courses are aligned with internationally recognised professional standards and frameworks across leadership, strategy, finance, governance, risk, compliance, and audit. By integrating globally trusted models, we ensure learners develop practical, relevant, and industry-recognised capabilities.

Our trainings draw on leading international standards and professional frameworks, including ISO, ISACA, COSO, OECD, IIA, FATF, Basel, IFRS/ISSB, GRI, NIST, CPD, ILM and the OECD AI Principles. This alignment ensures consistency with global best practices across financial management, risk oversight, digital governance, sustainability, and strategic decision-making..

Designed in alignment with globally recognised professional bodies, our courses support continuous professional development, strengthen organisational capability, and provide clear pathways toward professional certifications valued worldwide.

Ready to Take the Next Step?

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FAQs

This training course focuses on using AI-enabled analytics and decision-support tools to strengthen judgement, improve forecasting, and enhance measurable business performance. 

Yes. This training course is designed for managers and professionals who need practical business application rather than technical AI development expertise. 

Yes. The training course addresses governance, accountability, and ethical considerations to support responsible use of AI in business decision-making. 

The training course strengthens the use of predictive and prescriptive analytics to improve forecasting, scenario planning, and decision confidence.

The training course shows how AI-enabled dashboards and performance tools can improve visibility, discipline, and follow-through across business priorities.

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