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Analytics & Artificial Intelligence for Strategic Management Training Course

The Analytics & Artificial Intelligence for Strategic Management Training Course is an advanced executive-focused programme designed to equip managers and strategic decision-makers with the knowledge and practical…

DA · Data Analytics & Business IntelligenceAll LevelsClassroomEnglish , Arabic
Duration
5 Days
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Sectors:Data, Analytics & Digital TransformationCategories:Data Analytics & Business Intelligence

Course Overview

The Analytics & Artificial Intelligence for Strategic Management Training Course is an advanced executive-focused programme designed to equip managers and strategic decision-makers with the knowledge and practical capabilities required to use analytics and artificial intelligence to strengthen strategic planning, decision-making, organizational performance, and long-term value creation. The course explores how organizations can move from traditional strategy development toward data-driven and AI-enabled strategic management, using business intelligence, advanced analytics, predictive insights, scenario analysis, and artificial intelligence to identify opportunities, anticipate risks, improve resource allocation, and enhance competitive positioning. Participants will examine how analytics and AI can support the full strategic management cycle, including environmental analysis, market intelligence, strategic objective setting, performance management, forecasting, strategic risk assessment, innovation, and execution. Particular attention is given to interpreting analytical and AI-generated insights while maintaining sound executive judgment. Through practical exercises, case studies, and strategic workshops, participants will develop frameworks for identifying high-value analytics and AI opportunities, evaluating strategic use cases, translating data into actionable intelligence, and building AI-enabled strategic roadmaps aligned with organizational priorities.

Learning Objectives

  • By the end of the course, participants will be able to:
  • Understand the strategic role of analytics and artificial intelligence in modern management.
  • Assess how data and AI can influence strategic planning and organizational performance.
  • Apply analytical approaches to identify strategic opportunities and emerging risks.
  • Evaluate markets, competitors, customers, and business environments using data-driven insights.
  • Develop data-driven strategic objectives, priorities, and performance measures.
  • Apply predictive analytics and forecasting techniques to support strategic planning.
  • Use AI-enabled insights to improve executive decision-making.
  • Evaluate AI and analytics use cases based on strategic value, feasibility, and business impact.
  • Integrate analytics and AI into strategy execution and performance management.
  • Apply scenario analysis to evaluate strategic alternatives and future possibilities.
  • Strengthen resource allocation and investment decisions through analytical evidence.
  • Identify risks, limitations, bias, and uncertainty in analytical and AI-generated outputs.
  • Establish appropriate governance and accountability for AI-enabled strategic management.
  • Develop strategies for building data-driven and AI-enabled organizational capabilities.
  • Create an actionable roadmap for integrating analytics and AI into strategic management.

Who Should Attend

This course is designed for CEOs, executive directors, senior managers, strategy leaders, business unit heads, department managers, and decision-makers who are responsible for strategic planning, organizational performance, transformation, growth, and business development. It is particularly relevant to professionals working in strategy, corporate planning, business intelligence, data analytics, digital transformation, artificial intelligence, innovation, finance, operations, risk management, marketing, business development, and performance management. The programme is suitable for government and public-sector organizations, banks and financial institutions, oil and gas companies, energy organizations, engineering and industrial companies, telecommunications, healthcare, logistics, and large corporations seeking to strengthen strategic management through analytics and artificial intelligence.

Learning Outcomes

  • By the end of the course, participants will be able to:
  • Explain how analytics and AI contribute to strategic management and organizational value creation.
  • Assess organizational readiness for data-driven and AI-enabled strategy.
  • Analyze market, customer, competitor, and operational data to generate strategic insights.
  • Identify high-value strategic opportunities using analytics and AI.
  • Develop data-driven strategic objectives and performance indicators.
  • Apply forecasting and predictive analytics to support strategic planning.
  • Evaluate strategic scenarios using data, analytical models, and AI-supported insights.
  • Improve executive decision-making through structured analytical evidence.
  • Prioritize analytics and AI initiatives according to strategic value and organizational feasibility.
  • Integrate AI and analytics into strategy execution and performance monitoring.
  • Identify potential bias, uncertainty, limitations, and risks in AI-generated insights.
  • Establish principles for responsible and governed use of AI in strategic decisions.
  • Connect analytics and AI investments with measurable business outcomes.
  • Develop an AI-enabled strategic management framework.
  • Prepare an actionable analytics and AI roadmap aligned with organizational strategy.

Course Outline

Course Outline

Day 1

Strategic Management in the Age of Analytics & AI

  • Evolution from traditional strategic management to data-driven strategy.
  • The strategic value of organizational data and intelligence.
  • Understanding analytics, artificial intelligence, and their strategic applications.
  • The relationship between strategy, data, analytics, and AI.
  • Data-driven strategic thinking and executive decision-making.
  • Assessing organizational data and AI maturity.
  • Identifying strategic challenges that can be addressed through analytics and AI.
  • Building a culture of evidence-based strategic management.
  • Practical Application: Assessing organizational readiness for analytics- and AI-enabled strategic management.
Day 2

Analytics for Strategic Intelligence & Competitive Advantage

  • Using analytics for environmental and market analysis.
  • Data-driven customer and stakeholder intelligence.
  • Competitor analysis and competitive positioning.
  • Identifying market trends and emerging opportunities.
  • Business performance and profitability analytics.
  • Identifying strategic growth opportunities.
  • Forecasting demand, market movements, and business performance.
  • Using data to improve strategic resource allocation.
  • Translating analytical findings into strategic recommendations.
  • Practical Application: Developing a data-driven strategic intelligence analysis for a selected organization.
Day 3

Artificial Intelligence for Strategic Decision-Making

  • Strategic applications of artificial intelligence.
  • AI-supported executive decision-making.
  • Predictive analytics and AI-based forecasting.
  • Scenario modelling and strategic simulation.
  • Identifying patterns and relationships through AI.
  • AI-supported opportunity and risk identification.
  • Generative AI applications for strategic analysis and management.
  • Evaluating the reliability and relevance of AI-generated insights.
  • Human judgment, critical thinking, and AI-supported decisions.
  • Practical Application: Using an AI-enabled analytical framework to evaluate strategic alternatives.
Day 4

AI-Enabled Strategy Execution, Performance & Risk

  • Integrating analytics and AI into strategy execution.
  • AI-powered performance monitoring and strategic dashboards.
  • Linking strategic objectives with data-driven KPIs.
  • Predictive performance management and early-warning indicators.
  • AI and strategic risk identification.
  • Scenario planning and strategic resilience.
  • AI governance, accountability, and responsible decision-making.
  • Managing data quality, privacy, security, and analytical risks.
  • Measuring the business value and return on AI and analytics investments.
  • Practical Application: Designing an AI-enabled strategic performance and risk management framework.
Day 5

Building the AI-Enabled Strategic Management Framework

  • Designing an integrated analytics and AI strategic management model.
  • Prioritizing high-value analytics and AI initiatives.
  • Developing strategic AI and analytics business cases.
  • Aligning technology investments with organizational priorities.
  • Building organizational capabilities, talent, and leadership readiness.
  • Establishing governance and performance measurement mechanisms.
  • Developing implementation priorities and strategic milestones.
  • Managing organizational change and adoption.
  • Scaling successful analytics and AI initiatives across the organization.
  • Final Workshop: Developing an integrated Analytics & Artificial Intelligence Strategic Management Roadmap covering strategic priorities, use cases, value opportunities, KPIs, governance, capabilities, implementation phases, and performance measures.

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