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Artificial Intelligence Applications in Business
CoursesBusiness Administration Courses in the Private Sector
Professional Training Program

Artificial Intelligence Applications in Business

AI Applications in Business course designed to help professionals use AI tools to improve productivity, automate tasks, analyze data, support decisions, and drive innovation.

Certificate Included
Expert-Led Training
Practical Learning
Enrollment Support
days
3 Days
Language
English / Arabic
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Course Summary
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Runs monthly
Start Date
Flexible / Always Available
Certificate
Accredited Certificate
days
3 Days (Monthly)

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Course Details

Overview

The "Artificial Intelligence Applications in Business" course is an advanced practical training program designed to empower leaders, managers, and professionals to understand and utilize AI technologies in various business contexts, transforming them from emerging technologies into strategic tools that drive a quantum leap in organizational performance and competitiveness.

In 2026, which the Kingdom of Saudi Arabia officially declared the "Year of AI," artificial intelligence is no longer a technological luxury but a strategic necessity. Reports indicate that 33.1% of Saudi establishments are already using AI technologies, marking a 20% increase within a single year, and 40% of Saudi organizations have reached an advanced stage of AI maturity. Most notably, 38% of Saudi organizations are already using AI systems in production environments, positioning the Kingdom among the global leaders in deploying AI solutions.

This course takes participants from the fundamental concepts of artificial intelligence and machine learning, through generative AI tools (such as ChatGPT, Microsoft Copilot, and Google Gemini), to practical applications in key business functions: Marketing and Sales (intelligent recommendations, customer behavior analysis, sales forecasting), Human Resources (resume screening, employee sentiment analysis, turnover risk prediction), Operations and Production (process automation, predictive maintenance, supply chain optimization), Financial Services (fraud detection, credit risk analysis, algorithmic trading), and Customer Service (chatbots, predictive analysis of customer satisfaction).

The program is designed to be 70% practical, with hands-on exercises on real AI tools, case studies from the Saudi market, and group projects to develop AI solutions for real business problems. Studies indicate that 67% of Saudi companies reported that AI significantly improved their customer experience, compared to 39% globally, and 78% of companies confirmed that their AI strategy is closely aligned with their business objectives.

According to the latest KPMG reports for 2026, AI is rapidly transitioning from experimentation to enterprise deployment, with short-term ROI expectations being the strongest in survey history. Additionally, an SAP-YouGov survey showed that half of the participants said their AI initiatives exceeded expectations, while 41% said returns are meeting expectations. 59% reported that their organizations are strategically prioritizing AI investments at the enterprise level.

Objectives

Program Objectives

  • Understand the fundamental concepts and classifications of artificial intelligence – Distinguish between artificial intelligence, machine learning, deep learning, and generative AI, and identify the appropriate application areas for each in a business context.

  • Use AI tools to enhance daily productivity – Utilize large language models (such as ChatGPT, Microsoft Copilot, Google Gemini) for writing reports, drafting emails, summarizing meetings, analyzing documents, and creating presentations.

  • Analyze data and make predictive decisions – Use machine learning techniques to analyze customer behavior, forecast sales, optimize supply chains, and predict business risks.

  • Automate operational processes – Identify suitable opportunities for automation (RPA) in repetitive tasks, and design intelligent workflows using AI tools, as 86% of Saudi organizations view automation as the key to successful AI adoption.

  • Apply AI across various business functions – Formulate personalized marketing strategies, support HR decisions, enhance customer service through chatbots, and improve financial operations efficiency.

  • Assess and manage ethical and legal risks – Understand AI governance requirements, avoid data bias, and comply with data protection regulations (such as PDPL), as 62% of Saudi companies use formal frameworks for responsible AI use.

  • Develop an AI adoption roadmap for the organization – Build a practical action plan to identify AI opportunities, assess readiness, select appropriate tools, and measure return on investment.

Target Audience

Target Audience

  • Executives and General Managers – Seeking to understand how to integrate AI into their strategies to achieve competitive advantage.

  • Department Managers and Division Heads (Marketing, Sales, HR, Operations, Finance, Customer Service) – Responsible for leading digital transformation initiatives in their sectors.

  • Business and Data Analysts – Looking to enhance their analytical skills with AI.

  • Marketing, HR, and Customer Service Specialists – Seeking to automate their tasks and increase productivity.

  • Project and Technology Managers – Leading digital transformation initiatives in their organizations.

  • Entrepreneurs and SME Owners – Seeking intelligent solutions to grow their businesses.

  • Any professional seeking to keep up with technological developments – And enhance their career opportunities in the changing job market.

Competencies

Core Competencies

Text Drafting and Analysis Using AI

The ability to use Large Language Models (LLMs) to create report drafts, analyze legal documents, summarize studies, and rephrase texts in a professional manner.

Data Analysis and Visualization Using Machine Learning

Building simple predictive models using AI-powered analytical tools to analyze historical data and forecast future trends.

Designing and Implementing Automation Solutions

Identifying and implementing Robotic Process Automation (RPA) solutions for repetitive tasks, and integrating them with AI systems to create intelligent workflows.

Assessing Organizational AI Readiness

Conducting an initial assessment of data quality, technical infrastructure, and skills required for successful AI adoption in the organization.

Applying Responsible AI Principles

Identifying potential ethical risks (e.g., bias) and applying basic control procedures to ensure fair and responsible AI use.

Developing an AI Roadmap

Building a practical action plan to identify AI opportunities in the organization, assess readiness, select appropriate tools, and measure return on investment.

Learning Journey

Program Outline

01

Day One: Foundations of AI and Its Applications in Daily Productivity

Introduction to AI for Business
Definition of artificial intelligence and its importance in the digital age. The difference between AI, machine learning, deep learning, and generative AI. The Saudi AI Landscape 2026: Declaration of 2026 as the "Year of AI," AI adoption rate in Saudi establishments (33.1% with a 20% increase), and 40% of organizations at an advanced maturity stage. Examples of AI applications in leading Saudi companies.
Generative AI Tools
Overview of key tools: ChatGPT, Microsoft Copilot, Google Gemini, Claude. Practical Applications: (1) Writing reports and official correspondence, (2) Summarizing lengthy documents and meetings, (3) Translating and editing texts, (4) Creating presentations, (5) Simple data analysis. Prompt Engineering Skills: How to craft effective prompts to obtain accurate and useful results.
AI in Enhancing Personal Productivity
Using AI for email management (summarizing, drafting replies), organizing tasks and appointments, creating executive summaries, and quickly analyzing documents. Practical applications on real work scenarios.
Practical Workshop
Part One: Using ChatGPT or Microsoft Copilot to draft an executive report, summarize a legal document, and write a professional email. Part Two: Comparing the performance of different AI tools on the same task and analyzing the results.
02

Day Two: Data Analysis, Automation, and Functional Applications

Predictive Analytics
Using machine learning to forecast future trends. Practical Applications: (1) Sales forecasting, (2) Identifying customers most likely to default, (3) Predicting employee turnover rates, (4) Analyzing customer behavior and product recommendations. Simple Tools: Using Excel with AI add-ins and cloud analytics platforms.
Process Automation with AI (RPA + AI)
Definition of automation and its role in AI success (86% of Saudi organizations view automation as a crucial step before AI implementation). Practical Examples: Invoice processing automation, data entry, approval management, and customer request processing. Integrating Automation with AI: Creating intelligent workflows combining RPA and AI for automated decision-making.
AI in Marketing and Sales
(1) Personalization: Personalized product recommendations based on customer behavior. (2) Sentiment Analysis: Analyzing customer comments on social media. (3) Sales Forecasting: Predicting demand and optimizing pricing strategies. (4) Marketing Content Writing: Using AI to create advertisements and posts.
AI in Customer Service
(1) Chatbots: Designing and implementing intelligent chatbots to respond to customer inquiries 24/7. (2) Customer Sentiment Analysis: Using AI to analyze calls and messages to determine satisfaction levels. (3) Customer Behavior Prediction: Predicting customers most likely to churn or make repeat purchases.
Practical Workshop
Part One: Analyzing a dataset (sales or customers) using an AI-powered analytics tool to forecast future trends. Part Two: Designing an automated workflow to automate the "customer inquiry response" process using an intelligent chatbot.
03

Day Three: Governance, Ethics, and Roadmap Development

AI in Human Resources and Financial Operations
(1) Human Resources: Automated resume screening, employee sentiment analysis, turnover risk prediction, and personalized development path creation. (2) Financial Operations: Fraud detection, credit risk analysis, algorithmic trading, and automated financial auditing.
AI Governance and Risk Management
Understanding risks associated with AI: data bias, privacy violations, explainability challenges, and loss of control. Regulatory Frameworks: Personal Data Protection Law (PDPL) requirements, and Responsible AI principles in Saudi Arabia. The Role of Governance: 62% of Saudi companies use formal frameworks for responsible AI use.
Assessing Organizational AI Readiness
Assessment Dimensions: (1) Data Quality: Is data available, clean, and organized? (2) Infrastructure: Can current systems support AI solutions? (3) Skills: Does the team have the necessary skills? (4) Organizational Culture: Is the organization ready to embrace change? (5) Budget: What investments are required?
Developing an AI Adoption Roadmap
Practical Steps: (1) Defining strategic AI objectives, (2) Identifying priority AI opportunities (high impact, low effort), (3) Selecting appropriate tools and technologies, (4) Developing a phased implementation plan (6-12-24 months), (5) Defining KPIs to measure success, (6) Building a change management and employee training plan.
Comprehensive Case Study
Case: A medium-sized Saudi company (retail sector) faces challenges: (1) High customer service costs, (2) Difficulty forecasting product demand, (3) Weak personalization of marketing offers. Required from Participants (Small Teams): (1) Identify 3 AI application opportunities in the company with justification, (2) Propose appropriate tools and technologies for each opportunity, (3) Estimate costs and expected returns, (4) Develop an implementation roadmap in two phases (6 months, 12 months), (5) Identify potential risks and mitigation strategies, (6) Present to senior management (5 slides).
Final Test and Review
Written test (20 questions – multiple choice, true/false) covering basic concepts (AI types, tools, applications, ethics, governance). Review of key points over the three days: the difference between AI and machine learning, generative AI tools, AI applications in business functions, AI governance, and roadmap development.
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