Pideya Learning Academy

AI for Strategic Decision-Making and KPIs

Upcoming Schedules

  • Schedule

Date Venue Duration Fee (USD)
24 Feb - 28 Feb 2025 Live Online 5 Day 3250
10 Mar - 14 Mar 2025 Live Online 5 Day 3250
21 Apr - 25 Apr 2025 Live Online 5 Day 3250
09 Jun - 13 Jun 2025 Live Online 5 Day 3250
11 Aug - 15 Aug 2025 Live Online 5 Day 3250
15 Sep - 19 Sep 2025 Live Online 5 Day 3250
13 Oct - 17 Oct 2025 Live Online 5 Day 3250
24 Nov - 28 Nov 2025 Live Online 5 Day 3250

Course Overview

In an era defined by data saturation and rapid technological disruption, traditional methods of strategic planning are no longer sufficient to ensure business resilience and growth. Organizations are increasingly shifting away from reactive strategies toward predictive and prescriptive models powered by Artificial Intelligence (AI). The training program “AI for Strategic Decision-Making and KPIs” by Pideya Learning Academy is designed to equip modern leaders, analysts, and planners with a forward-thinking mindset and actionable tools to enhance decision-making processes through AI technologies.
Modern enterprises face escalating pressure to make faster, smarter, and more agile decisions. According to a 2024 McKinsey report, over 56% of companies globally have integrated AI into at least one function, with strategic decision-making ranking among the top three use cases. Furthermore, Gartner predicts that by 2026, over 75% of enterprises will deploy AI-driven decision intelligence platforms, fundamentally reshaping how organizations define success metrics and assess performance. These trends reflect a paradigm shift across industries—from finance and manufacturing to healthcare, energy, and the public sector—where AI is no longer a niche innovation but a strategic necessity.
The “AI for Strategic Decision-Making and KPIs” training by Pideya Learning Academy bridges this transition by offering a comprehensive guide to applying AI for both strategic foresight and performance management. Participants will learn how to align organizational objectives with AI-enabled analytics, using algorithms to detect patterns, predict future outcomes, and optimize key performance indicators (KPIs). As AI systems become more intuitive and self-improving, decision-makers can leverage these capabilities to support dynamic strategy execution and agile business planning.
A standout feature of this course is the emphasis on AI-powered dashboards and scorecards, which allow organizations to move beyond static reports and embrace live, data-driven insights. Participants will gain exposure to the architecture of intelligent reporting tools that consolidate vast datasets into intuitive visual summaries for executive consumption. Additionally, the training covers simulation techniques using AI—enabling scenario modeling that accounts for risk, uncertainty, and competing objectives in real-time strategic planning.
Ethical AI adoption is another cornerstone of this program. As AI becomes embedded in core decision-making frameworks, concerns around fairness, transparency, and accountability must be proactively addressed. The course therefore includes a dedicated focus on AI governance models, ethical integration strategies, and methods to ensure explainability of AI-generated outputs.
Throughout the course, participants will benefit from real-world insights, data-centric examples, and expert-led sessions that bring theory to life. Whether revising outdated KPIs, building new strategic frameworks, or seeking alignment across departments, this program provides a robust foundation for transforming AI from a technical tool into a true business partner.
Participants will walk away with:
A solid understanding of how AI enables strategic planning and leadership decision-making
Practical approaches to using machine learning for tracking and improving KPIs
Knowledge of designing AI-powered scorecards, dashboards, and simulation tools
Skills to build governance frameworks for ethical and transparent AI use
Strategies for translating AI-generated insights into organizational impact
Enhanced capacity to align AI tools with cross-functional performance goals
This course by Pideya Learning Academy is a game-changer for professionals looking to future-proof their decision-making capabilities and embed AI into the heart of their performance management culture. As global markets become more volatile and data more abundant, leaders trained in AI-driven strategy will be better positioned to lead with confidence, speed, and foresight.

Course Objectives

After completing this Pideya Learning Academy training, the participants will learn to:
Interpret the evolving role of AI in strategic planning and performance analytics
Develop AI-enabled KPI frameworks aligned with organizational objectives
Build and evaluate machine learning models for performance forecasting
Integrate predictive analytics into corporate decision-making processes
Design AI-powered dashboards and scorecards for executive reporting
Simulate multiple strategic scenarios using AI-based tools
Address ethical, legal, and governance considerations in AI adoption
Translate AI insights into effective, cross-functional business strategies

Personal Benefits

Participants will gain:
Advanced knowledge of AI-driven decision-making frameworks
Skills to transform raw data into strategic insights
Capability to design and monitor AI-informed KPIs
Proficiency in using AI to simulate complex business outcomes
Competitive edge in strategic roles across industries

Organisational Benefits

Organizations attending this course will benefit by:
Accelerating AI adoption in strategy formulation and performance measurement
Enhancing organizational agility and responsiveness to market changes
Enabling evidence-based planning across business units
Improving KPI accuracy, traceability, and alignment with corporate goals
Fostering a culture of data-driven decision-making at all levels

Who Should Attend

This course is ideal for:
Strategic Planning Officers and Decision-Makers
Business Analysts and Performance Managers
Data Scientists and AI Professionals
Corporate Executives and Business Leaders
IT Managers involved in digital transformation
Risk and Compliance Professionals
Public Sector Strategy and Policy Officers
Course

Course Outline

Module 1: Foundations of AI in Strategic Decision-Making
Strategic decision theory and the AI advantage Overview of AI tools and technologies From data to decision: The AI pipeline Case studies of AI-driven strategy Human vs machine decision paradigms Bias, transparency, and interpretability in AI outputs
Module 2: KPI Systems and AI Alignment
Introduction to KPI frameworks Linking KPIs to corporate goals AI’s role in selecting measurable indicators Dynamic KPI systems using ML models Real-time monitoring with AI dashboards Threshold setting, alerts, and anomaly detection
Module 3: Predictive Analytics for Strategic Foresight
Time-series forecasting models Regression and classification in business strategy Demand, risk, and resource forecasting AI-driven scenario simulation Linking predictive analytics to strategic goals Business impact assessment of forecasts
Module 4: Machine Learning for Performance Optimization
Supervised and unsupervised learning use cases Feature selection and model tuning for KPI data Training and validation in strategic applications Interpreting model accuracy and insights AutoML and low-code platforms Ethical deployment in performance systems
Module 5: AI-Enhanced Decision Intelligence Platforms
Introduction to decision intelligence architecture AI decision engines and optimization algorithms Feedback loops and continuous learning Integration with ERP and BI systems Visual storytelling in decision dashboards Use cases in finance, operations, and HR
Module 6: Strategic Scenario Modeling and Simulations
Defining strategic options and trade-offs Monte Carlo simulations for risk-adjusted plans Sensitivity and impact analysis AI in crisis management and uncertainty planning Evaluating cost-benefit outcomes Strategy mapping using AI-based tools
Module 7: Data Governance and Ethics in AI Strategy
Governance structures for AI integration Data quality, lineage, and stewardship Ethical principles in algorithmic decision-making Regulatory compliance and auditability Explainable AI (XAI) and trust-building AI accountability and stakeholder transparency
Module 8: Communicating AI-Driven Insights to Leadership
Structuring insights for executive stakeholders Data storytelling and visual analytics Scorecards and narrative performance reviews Influencing board-level decisions with AI metrics Overcoming resistance to AI integration Cross-departmental alignment and buy-in
Module 9: Building AI Strategy Implementation Roadmaps
Phases of AI integration in strategic planning AI capability maturity assessment Infrastructure and talent considerations Budgeting and ROI justification Change management and internal communication Monitoring progress and performance milestones

Have Any Question?

We’re here to help! Reach out to us for any inquiries about our courses, training programs, or enrollment details. Our team is ready to assist you every step of the way.