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Artificial Intelligence in Business
CoursesArtificial Intelligence and Its Applications in Business
Professional Training Program

Artificial Intelligence in Business

A practical AI business program covering AI value creation, automation, predictive analytics, personalization, and competitive advantage, AI use-case identification across marketing, sales, customer service, operations, HR, finance, and risk, AI use-case development, business objectives, data requirements, technical feasibility, and economic feasibility, ROI, payback period, NPV, IRR, cost estimation, and benefit estimation for AI projects, AI-as-a-service platforms, cloud AI services, open-source alternatives, and infrastructure choices, with case studies, templates, tool demonstrations, hands-on exercises, and applied outputs for workplace

Certificate Included
Expert-Led Training
Practical Learning
Enrollment Support
days
3 Days
Language
English / Arabic
Online Payment Available
2026-10-11

Pay Online & Book Your Seat

Total Tuition
396 SAR
VAT included

This course has a priced upcoming session. Choose your seat type, select an available payment method, and complete booking through a protected checkout.

Accepted Payment Methods
madaVisaMastercardAmerican ExpressSTC Pay
Course Summary
Total Tuition
396 SAR
VAT included
madaVisaMastercardAmerican ExpressSTC Pay
Start Date
2026-10-11
Session hours
6:00–10:00 PM (Riyadh time)
Delivery
Online
Certificate
Attendance Certificate
days
3 Days
Ask on WhatsApp

By continuing you agree to the Refund Policy

Course Details

Overview

The Artificial Intelligence in Business course is a practical artificial intelligence and business applications program designed to build applied capability in AI value creation, automation, predictive analytics, personalization, and competitive advantage, AI use-case identification across marketing, sales, customer service, operations, HR, finance, and risk, AI use-case development, business objectives, data requirements, technical feasibility, and economic feasibility, ROI, payback period, NPV, IRR, cost estimation, and benefit estimation for AI projects. It helps participants understand how AI can improve productivity, decision-making, customer value, operational efficiency, risk control, and innovation.

The program covers AI value creation, automation, predictive analytics, personalization, and competitive advantage, AI use-case identification across marketing, sales, customer service, operations, HR, finance, and risk, AI use-case development, business objectives, data requirements, technical feasibility, and economic feasibility, ROI, payback period, NPV, IRR, cost estimation, and benefit estimation for AI projects, along with AI-as-a-service platforms, cloud AI services, open-source alternatives, and infrastructure choices, AI risk management, ethics, PDPL compliance, model explainability, and governance, AI adoption roadmaps, pilot projects, scaling plans, and organizational change management. Participants work with realistic business cases, AI tools, templates, demonstrations, scenario analysis, and applied exercises that can be adapted to their organization.

The course is designed for approximately 4 training day(s), with emphasis on practical execution, responsible AI use, data-driven thinking, governance awareness, and measurable workplace outputs.

Objectives

Program Objectives

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

  1. Understand AI value creation, automation, predictive analytics, personalization, and competitive advantage in realistic business scenarios related to Artificial Intelligence in Business.
  2. Apply AI use-case identification across marketing, sales, customer service, operations, HR, finance, and risk in realistic business scenarios related to Artificial Intelligence in Business.
  3. Analyze AI use-case development, business objectives, data requirements, technical feasibility, and economic feasibility in realistic business scenarios related to Artificial Intelligence in Business.
  4. Evaluate ROI, payback period, NPV, IRR, cost estimation, and benefit estimation for AI projects in realistic business scenarios related to Artificial Intelligence in Business.
  5. Develop AI-as-a-service platforms, cloud AI services, open-source alternatives, and infrastructure choices in realistic business scenarios related to Artificial Intelligence in Business.
  6. Produce a practical work output such as an AI use-case brief, prompt library, analytical model, dashboard, governance checklist, implementation roadmap, or business-ready AI workflow according to the course topic.
Target Audience

Target Audience

This training program is designed for the following target audiences:

  1. Business leaders, managers, supervisors, specialists, analysts, consultants, and professionals who need to understand or apply AI in their work.
  2. Entrepreneurs, new graduates, product owners, operational teams, and non-technical professionals seeking practical AI literacy.
  3. Organizations seeking practical, responsible, and measurable AI adoption across business functions.
Competencies

Core Competencies

Apply AI value creation, automation, predictive analytics, personalization, and competitive advantage

Ability to apply AI value creation, automation, predictive analytics, personalization, and competitive advantage within Artificial Intelligence in Business, using appropriate data, tools, templates, governance controls, practical analysis, and business-oriented recommendations.

Apply AI use-case identification across marketing, sales, customer service, operations, HR, finance, and risk

Ability to apply AI use-case identification across marketing, sales, customer service, operations, HR, finance, and risk within Artificial Intelligence in Business, using appropriate data, tools, templates, governance controls, practical analysis, and business-oriented recommendations.

Apply AI use-case development, business objectives, data requirements, technical feasibility, and economic feasibility

Ability to apply AI use-case development, business objectives, data requirements, technical feasibility, and economic feasibility within Artificial Intelligence in Business, using appropriate data, tools, templates, governance controls, practical analysis, and business-oriented recommendations.

Apply ROI, payback period, NPV, IRR, cost estimation, and benefit estimation for AI projects

Ability to apply ROI, payback period, NPV, IRR, cost estimation, and benefit estimation for AI projects within Artificial Intelligence in Business, using appropriate data, tools, templates, governance controls, practical analysis, and business-oriented recommendations.

Apply AI-as-a-service platforms, cloud AI services, open-source alternatives, and infrastructure choices

Ability to apply AI-as-a-service platforms, cloud AI services, open-source alternatives, and infrastructure choices within Artificial Intelligence in Business, using appropriate data, tools, templates, governance controls, practical analysis, and business-oriented recommendations.

Apply AI risk management, ethics, PDPL compliance, model explainability, and governance

Ability to apply AI risk management, ethics, PDPL compliance, model explainability, and governance within Artificial Intelligence in Business, using appropriate data, tools, templates, governance controls, practical analysis, and business-oriented recommendations.

Learning Journey

Program Outline

01

Day 1: Ai Value Creation, Automation, Predictive Analytics, Personalization, And Competitive Advantage

Ai Value Creation, Automation, Predictive Analytics, Personalization, And Competitive Advantage
This session develops practical competence in AI value creation, automation, predictive analytics, personalization, and competitive advantage as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai Use-Case Identification Across Marketing, Sales, Customer Service, Operations, Hr, Finance, And Risk
This session develops practical competence in AI use-case identification across marketing, sales, customer service, operations, HR, finance, and risk as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai Use-Case Development, Business Objectives, Data Requirements, Technical Feasibility, And Economic Feasibility
This session develops practical competence in AI use-case development, business objectives, data requirements, technical feasibility, and economic feasibility as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Roi, Payback Period, Npv, Irr, Cost Estimation, And Benefit Estimation For Ai Projects
This session develops practical competence in ROI, payback period, NPV, IRR, cost estimation, and benefit estimation for AI projects as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai-As-A-Service Platforms, Cloud Ai Services, Open-Source Alternatives, And Infrastructure Choices
This session develops practical competence in AI-as-a-service platforms, cloud AI services, open-source alternatives, and infrastructure choices as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
02

Day 2: Ai Use-Case Identification Across Marketing, Sales, Customer Service, Operations, Hr, Finance, And Risk

Ai Use-Case Identification Across Marketing, Sales, Customer Service, Operations, Hr, Finance, And Risk
This session develops practical competence in AI use-case identification across marketing, sales, customer service, operations, HR, finance, and risk as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai Use-Case Development, Business Objectives, Data Requirements, Technical Feasibility, And Economic Feasibility
This session develops practical competence in AI use-case development, business objectives, data requirements, technical feasibility, and economic feasibility as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Roi, Payback Period, Npv, Irr, Cost Estimation, And Benefit Estimation For Ai Projects
This session develops practical competence in ROI, payback period, NPV, IRR, cost estimation, and benefit estimation for AI projects as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai-As-A-Service Platforms, Cloud Ai Services, Open-Source Alternatives, And Infrastructure Choices
This session develops practical competence in AI-as-a-service platforms, cloud AI services, open-source alternatives, and infrastructure choices as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai Risk Management, Ethics, Pdpl Compliance, Model Explainability, And Governance
This session develops practical competence in AI risk management, ethics, PDPL compliance, model explainability, and governance as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
03

Day 3: Ai Use-Case Development, Business Objectives, Data Requirements, Technical Feasibility, And Economic Feasibility

Ai Use-Case Development, Business Objectives, Data Requirements, Technical Feasibility, And Economic Feasibility
This session develops practical competence in AI use-case development, business objectives, data requirements, technical feasibility, and economic feasibility as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Roi, Payback Period, Npv, Irr, Cost Estimation, And Benefit Estimation For Ai Projects
This session develops practical competence in ROI, payback period, NPV, IRR, cost estimation, and benefit estimation for AI projects as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai-As-A-Service Platforms, Cloud Ai Services, Open-Source Alternatives, And Infrastructure Choices
This session develops practical competence in AI-as-a-service platforms, cloud AI services, open-source alternatives, and infrastructure choices as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai Risk Management, Ethics, Pdpl Compliance, Model Explainability, And Governance
This session develops practical competence in AI risk management, ethics, PDPL compliance, model explainability, and governance as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai Adoption Roadmaps, Pilot Projects, Scaling Plans, And Organizational Change Management
This session develops practical competence in AI adoption roadmaps, pilot projects, scaling plans, and organizational change management as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai Value Creation, Automation, Predictive Analytics, Personalization, And Competitive Advantage
This session develops practical competence in AI value creation, automation, predictive analytics, personalization, and competitive advantage as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
04

Day 4: Roi, Payback Period, Npv, Irr, Cost Estimation, And Benefit Estimation For Ai Projects

Roi, Payback Period, Npv, Irr, Cost Estimation, And Benefit Estimation For Ai Projects
This session develops practical competence in ROI, payback period, NPV, IRR, cost estimation, and benefit estimation for AI projects as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai-As-A-Service Platforms, Cloud Ai Services, Open-Source Alternatives, And Infrastructure Choices
This session develops practical competence in AI-as-a-service platforms, cloud AI services, open-source alternatives, and infrastructure choices as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai Risk Management, Ethics, Pdpl Compliance, Model Explainability, And Governance
This session develops practical competence in AI risk management, ethics, PDPL compliance, model explainability, and governance as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai Adoption Roadmaps, Pilot Projects, Scaling Plans, And Organizational Change Management
This session develops practical competence in AI adoption roadmaps, pilot projects, scaling plans, and organizational change management as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai Value Creation, Automation, Predictive Analytics, Personalization, And Competitive Advantage
This session develops practical competence in AI value creation, automation, predictive analytics, personalization, and competitive advantage as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Ai Use-Case Identification Across Marketing, Sales, Customer Service, Operations, Hr, Finance, And Risk
This session develops practical competence in AI use-case identification across marketing, sales, customer service, operations, HR, finance, and risk as part of Artificial Intelligence in Business. Participants review relevant concepts, examine realistic business or organizational scenarios, use AI tools or templates where applicable, discuss risks and governance considerations, and prepare an applied output that supports productivity, insight, responsible AI use, and workplace implementation.
Next Available Date

Global Schedule

Date
2026-10-11
Delivery
Online
Session hours
6:00–10:00 PM (Riyadh time)
396 SAR
VAT included
Enrollment Summary
Secure Course Registration
Total Tuition
396 SAR
VAT included
madaVisaMastercardAmerican ExpressSTC Pay
Start Date
2026-10-11
Session hours
6:00–10:00 PM (Riyadh time)
Delivery
Online
Certificate
Attendance Certificate
days
3 Days
Ask on WhatsApp

By continuing you agree to the Refund Policy

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