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Master in AI Powered Data-Driven Management

Name: Master in AI Powered Data-Driven Management
Rating: 4.5 (22 reviews)

Build a data-driven organization using AI through practical frameworks, case studies and implementation.

Created byArun Singhal B-Tech MBA With 45+ Exp with Unilever, J&J, Danone, etc.

Last updated 7/2026

English

English [Auto],

What you'll learn

Build a data-driven organization using Artificial Intelligence to improve management excellence.
Create a strong data-driven culture that enables better management and business performance.
Transform business data into actionable insights for planning, execution, and continuous improvement.
Apply descriptive, diagnostic, predictive, and prescriptive analytics to support effective management
Build AI-powered dashboards and executive reporting systems for better organizational visibility.
Use AI to automate management processes and improve operational efficiency.
Apply AI for market intelligence, risk sensing, scenario planning, and strategic management.
Improve organizational performance through AI-enabled planning, performance management, and continuous feedback.
Lead AI adoption across teams and implement responsible AI governance and change management.
Develop a practical roadmap to successfully implement AI for Data-Driven Management Excellence.

Course content

12 sections • 35 lectures • 6h 18m total length

Introduction7:22
Introduction to the course and faculty
Introduction Case Study17:03
A case study of using AI to build Excellence in Data Driven Management

How can AI help build Excellence in Data Driven Management-Overview11:22
At the end of this lecture, you will learn the following
•How can AI help build Excellence in Data Driven Management
Overview I
Overview II- Case Study 16:50
At the end of this lecture, you will learn the following
•Case Study of AI helping build Excellence in Data Driven Management
Overview II
Overview III- Case Study 25:43
At the end of this lecture, you will learn the following
•Case Study of AI helping build Excellence in Data Driven Management
Overview III
Overview IV- Case Study 37:07
At the end of this lecture, you will learn the following
•Case Study of AI helping build Excellence in Data Driven Management
Overview IV

Build a Data Culture10:02
At the end of this lecture, you will learn the following
a. Build a Data Culture:
•Educate leaders and teams to rely on data over intuition.
Promote transparency and accessibility of data across departments
Setting the Foundation for Data-Driven AI Integration I
Establish a Robust Data Infrastructure10:52
At the end of this lecture, you will learn the following
b. Establish a Robust Data Infrastructure:
•Use modern data lakes/warehouses (e.g., Snowflake, BigQuery).
•Ensure data quality, governance, and security are in place.
Setting the Foundation for Data-Driven AI Integration II
Leverage the Right AI Tools12:38
At the end of this lecture, you will learn the following
c. Leverage the Right AI Tools :
•AutoML platforms (e.g., Google AutoML, DataRobot) for non-tech teams.
•Low-code/no-code AI tools (e.g., Power Platform, Tableau GPT)
Setting the Foundation for Data-Driven AI Integration III
Setting the Foundation for Data-Driven AI Integration Case Study10:54
A case study of Excellence in setting the Foundation for Data-Driven AI Integration

Descriptive Analytics (What happened?)10:17
At the end of this lecture, you will learn the following
Descriptive Analytics (What happened?)
•Use AI-enhanced BI tools (e.g., Power BI + Copilot, Tableau Pulse) to automate dashboards and detect patterns.
Using AI to Extract Insights from Data I
Diagnostic Analytics (Why did it happen?)12:06
At the end of this lecture, you will learn the following
Diagnostic Analytics (Why did it happen?)
•Apply ML models to uncover hidden correlations and root causes.
•Use NLP tools to analyze customer feedback, complaints, or survey data.
Using AI to Extract Insights from Data II
Predictive Analytics (What will happen?)10:49
At the end of this lecture, you will learn the following
Predictive Analytics (What will happen?)
•Predict demand, churn, risk, or revenue using ML algorithms.
Automate forecasts with time-series models and AI regressors
Using AI to Extract Insights from Data III
Prescriptive Analytics (What should we do?)14:41
At the end of this lecture, you will learn the following
Prescriptive Analytics (What should we do?)
•Use reinforcement learning or optimization models for decision support.
•Run simulations and scenario modeling (e.g., with Monte Carlo + AI).
Using AI to Extract Insights from Data IV
Using AI to Extract Insights from Data Case Study10:59
A case study of using AI to Extract Insights from Data Analytics

Real-time Dashboards with Intelligent Alerts10:09
At the end of this lecture, you will learn the following
Real-time Dashboards with Intelligent Alerts:
•Use AI to flag anomalies or trigger alerts based on thresholds or patterns.
Operationalizing AI for Decision-Making I
Intelligent Decision Engines12:01
At the end of this lecture, you will learn the following
Intelligent Decision Engines:
•Set up AI models to recommend next best actions (NBAs) for sales, marketing, supply chain, etc.
Operationalizing AI for Decision-Making II
Executive Summarization via NLG10:26
At the end of this lecture, you will learn the following
Executive Summarization via NLG:
•Use Natural Language Generation (e.g., AWS Quicksight Narratives, Narrato AI) to auto-generate summaries for stakeholders.
Operationalizing AI for Decision-Making III

RPA + AI (Intelligent Automation)10:43
At the end of this lecture, you will learn the following
RPA + AI (Intelligent Automation):
•Automate data entry, reporting, reconciliation using tools like UiPath, Power Automate + AI Builder.
Automating Processes Using AI I
AI in Workflow Management11:23
At the end of this lecture, you will learn the following
AI in Workflow Management:
•Use AI to assign tasks, predict delays, and optimize resource allocation.
Automating Processes Using AI II
AI-Driven Knowledge Management12:42
At the end of this lecture, you will learn the following
AI-Driven Knowledge Management:
•Use vector databases + LLMs to build internal search/chatbots for SOPs, reports, policies.
Automating Processes Using AI III

Market and Competitor Intelligence11:12
At the end of this lecture, you will learn the following
Market and Competitor Intelligence:
•Use AI to scan news, filings, and social media for signals.
•Tools: AlphaSense, Crayon, Feedly AI.
Using AI to Support Strategic Management I
Risk Sensing and Mitigation14:11
At the end of this lecture, you will learn the following
Risk Sensing and Mitigation:
•Use AI to detect fraud, compliance breaches, and external threats in real time.
Using AI to Support Strategic Management II
Scenario Planning12:30
At the end of this lecture, you will learn the following
Scenario Planning:
•Use Generative AI to simulate strategic scenarios for M&A, pricing, expansion, etc.
Using AI to Support Strategic Management III

Personalized KPIs and Dashboards12:07
At the end of this lecture, you will learn the following
Personalized KPIs and Dashboards:
•AI tailors insights to each role/manager using behavior and context.
Embedding AI in Performance Management I
Dynamic Goal Setting10:15
At the end of this lecture, you will learn the following
Dynamic Goal Setting:
•Use AI to recommend goals based on trends, company priorities, and historical data.
Embedding AI in Performance Management II
Continuous Feedback Loops12:38
At the end of this lecture, you will learn the following
Continuous Feedback Loops:
•AI tools (like Viva Insights or Lattice + AI) analyze performance feedback and guide improvements.
Embedding AI in Performance Management III

Train Leaders and Managers12:31
At the end of this lecture, you will learn the following
Train Leaders and Managers:
•Run programs on AI literacy, ethics, and data-driven leadership.
Building AI Fluency Across the Organization I
Cross-Functional Collaboration10:12
At the end of this lecture, you will learn the following
Cross-Functional Collaboration:
Pair domain experts with data scientists to co-develop AI solutions
Building AI Fluency Across the Organization II
Promote Citizen Data Scientists11:55
At the end of this lecture, you will learn the following
Promote Citizen Data Scientists:
•Empower analysts and business users with tools like Excel + AI, Power BI + Copilot, etc.
Building AI Fluency Across the Organization III

Implement clear policies for AI usage9:48
At the end of this lecture, you will learn the following
•Implement clear policies for AI usage.
Governance, Ethics & Change Management I
Ensure fairness, transparency, and explainability in AI decisions10:21
At the end of this lecture, you will learn the following
•Ensure fairness, transparency, and explainability in AI decisions.
Governance, Ethics & Change Management II
Manage resistance through transparency and education10:49
At the end of this lecture, you will learn the following
•Manage resistance through transparency and education
Governance, Ethics & Change Management III

Requirements

5 hours learning time

Description

Is Your Organization Truly Data-Driven?

Every organization is generating more data than ever before.

Artificial Intelligence is advancing at an incredible pace.

Yet many organizations still struggle to turn data into better management, faster execution, and superior business performance.

Do any of these challenges sound familiar?

Managers still rely on intuition instead of data.
Valuable business data remains trapped in silos.
Dashboards report information but fail to drive action.
AI initiatives generate excitement but little measurable business value.
Teams struggle to embed AI into everyday management processes.
Leaders want to build a data-driven culture but don't know where to start.

If so, this course is designed for you.

Build a Data-Driven Organization Using AI

This course provides a practical framework to help organizations use Artificial Intelligence to achieve Data-Driven Management Excellence.

Rather than focusing only on AI tools or analytics techniques, you will learn how AI can strengthen every stage of the management process—from building a data-driven culture and integrating AI into management processes to improving organizational performance and driving continuous improvement.

Through practical frameworks, real-world case studies, and implementation guidance, you will learn how successful organizations use AI to transform management and create sustainable business value.

What You Will Learn

By the end of this course, you will be able to:

Build a strong data-driven culture across your organization.
Establish the right data foundation for AI-enabled management.
Transform business data into meaningful insights.
Apply descriptive, diagnostic, predictive, and prescriptive analytics.
Build intelligent dashboards and executive reporting systems.
Automate management workflows using AI.
Improve planning, performance management, and operational execution.
Use AI for market intelligence, risk sensing, and strategic planning.
Lead AI adoption across teams and business functions.
Implement practical AI governance and responsible AI practices.
Develop a practical roadmap for achieving Data-Driven Management Excellence.

Why This Course Is Different

Many courses teach Artificial Intelligence.

Many courses teach Data Analytics.

Many courses teach Management.

This course brings these disciplines together into one practical framework that shows how organizations can use AI to become truly data-driven.

The focus is not on learning AI tools for their own sake.

The focus is on helping organizations improve management, strengthen execution, increase organizational performance, and create measurable business value through effective use of AI and data.

Who Should Take This Course?

This course is ideal for:

Business Leaders
Senior Managers
Functional Managers
Digital Transformation Leaders
Business Consultants
Project Managers
Entrepreneurs
MBA Students
Professionals responsible for improving organizational performance using AI and data

No Prior AI Experience Required

The course explains AI concepts from a practical business and management perspective.

Whether you are beginning your AI journey or leading organizational transformation, you will gain practical knowledge, frameworks, and implementation strategies that can be applied immediately within your organization.

Start Building a Data-Driven Organization Today

Organizations that successfully combine AI, data, and effective management will be better positioned to improve performance, respond faster to change, and build sustainable competitive advantage.

If you want to transform your organization into a truly data-driven enterprise and use Artificial Intelligence to achieve Management Excellence, this course provides the practical framework, implementation guidance, and real-world insights to help you succeed.

Enroll today and start building the capabilities needed to lead your organization's AI-powered transformation

This Course is Part of a Structured Learning Path

Learning Path: ANALYTICS PATH (Starter → Builder → Advanced)

This course is your ADVANCED step.

Next Recommended Courses

After completing this course, continue your growth with:

Data Analytics (Starter)

Business Analytics (Builder)

Business Analysis (Builder)

Data Science (Builder)

Who this course is for:

Business Leaders
Managers and Executives
Strategy Professionals
Business Analysts
Data Analysts
Consultants
Entrepreneurs
Transformation Leaders
Operations Managers
Functional Leaders looking to leverage AI

Master in AI Powered Data-Driven Management

What you'll learn

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Course content

Introduction2 lectures • 24min

Overview4 lectures • 31min

Setting the Foundation for Data-Driven AI Integration4 lectures • 44min

Using AI to Extract Insights from Data5 lectures • 59min

Operationalizing AI for Decision-Making3 lectures • 33min

Automating Processes Using AI3 lectures • 35min

Using AI to Support Strategic Management3 lectures • 38min

Embedding AI in Performance Management3 lectures • 35min

Building AI Fluency Across the Organization3 lectures • 35min

Governance, Ethics & Change Management3 lectures • 31min

Requirements

Description

Who this course is for: