AI+ Sales Practitioner™

About Course

Course Overview 

Duration: 8 Hours
Course delivery method: online 
Course price: 4,407.75 EGP (Self-paced online)
For groups instructor-led course inquiries, please Whatsapp us and our Sales team will get in touch.

Comprehensive AI Understanding: Learn core AI concepts for streamlined sales workflows, trend forecasting, and client engagement.
Predictive Sales Analytics: Learn to leverage AI for predictive modeling, forecasting sales, and enhancing decision-making.
AI-Enhanced Customer Insights: Explore AI tools to analyze behavior, automate scoring, and personalize outreach effectively.
Ethical AI Integration: Gain insights on addressing ethical concerns and establishing AI governance in sales.

Course Objectives

  • Understand the fundamentals of Artificial Intelligence (AI) and its growing role in modern sales organizations.
  • Identify key AI technologies and tools used to improve sales performance, customer engagement, and business growth.
  • Recognize the benefits, challenges, and future opportunities associated with AI adoption in sales environments.
  • Understand different types of sales data and apply effective data collection, management, and analysis techniques.
  • Utilize AI-driven insights to support data-driven decision-making and sales strategy development.
  • Apply Machine Learning, Predictive Analytics, Natural Language Processing (NLP), and automation technologies to sales processes.
  • Leverage AI-powered CRM capabilities to improve lead scoring, customer insights, sales automation, and personalized communication.
  • Develop more accurate sales forecasts using predictive models, real-time data, and AI forecasting tools.
  • Enhance sales productivity through AI-enabled lead generation, customer segmentation, email marketing, and sales activity monitoring.
  • Implement AI solutions to improve customer experiences, increase conversion rates, and identify upselling and cross-selling opportunities.
  • Understand ethical considerations related to AI in sales, including bias mitigation, transparency, accountability, privacy, and regulatory compliance.
  • Develop practical approaches for implementing AI technologies within sales teams and business processes.
  • Evaluate AI-driven sales initiatives and measure their effectiveness against business objectives.
  • Understand the fundamentals of AI Agents and explore their applications in sales automation, customer engagement, and intelligent decision support.

Course Outline

Module 1: Introduction to Artificial Intelligence (AI) in Sales

  • 1.1 Fundamentals of AI
  • 1.2 Historical Journey and Evolution of AI in Sales
  • 1.3 AI Tools & Technologies Transforming Sales
  • 1.4 Benefits and Challenges in Adoption of AI in Sales
  • 1.5 Real-World Examples and Applications of AI in Sales
  • 1.6 Future of AI in Sales

Module 2: Understanding Data in Sales

  • 2.1 Categories of Sales Data
  • 2.2 Techniques for Effective Data Collection
  • 2.3 Basics of Data Analysis and Interpretation
  • 2.4 Data Management Methods
  • 2.5 Data Protection Principles
  • 2.6 Data Integration in CRM Systems
  • 2.7 Overview of Analytical Tools
  • 2.8 Ethical Use of Sales Data
  • 2.9 Case Studies: Real-World Data Applications

Module 3: AI Technologies for Sales

  • 3.1 Introduction to Machine Learning in Sales
  • 3.2 Predictive Analytics: Forecasting Sales Trends
  • 3.3 Natural Language Processing (NLP): Enhancing Customer Interactions
  • 3.4 Chatbots: Automating Customer Service
  • 3.5 Segmentation: Tailoring Customer Experiences
  • 3.6 Personalization: Customizing Sales Approaches
  • 3.7 Recommendation Engines: Driving Product Suggestions
  • 3.8 Sales Automation: Streamlining Sales Processes
  • 3.9 Performance Analysis: Measuring Sales Effectiveness

Module 4: Implementation of AI in CRM Systems

  • 4.1 Foundation of CRM Systems
  • 4.2 AI Integration into CRM Systems
  • 4.3 Lead Scoring
  • 4.4 Customer Insights
  • 4.5 Sales Automation
  • 4.6 Personalized Communication
  • 4.7 Chatbots in CRM
  • 4.8 Gaining Actionable Insights from Data
  • 4.9 Case Studies

Module 5: Sales Forecasting with AI

  • 5.1 Introduction to Sales Forecasting
  • 5.2 Overview of Predictive Models in Forecasting
  • 5.3 Data Preparation for Analysis
  • 5.4 Identifying Sales Patterns and Trends
  • 5.5 Enhancing Forecast Reliability
  • 5.6 Key AI Tools for Sales Forecasting
  • 5.7 Utilizing Real-Time Data for Forecasts
  • 5.8 Developing Forecasts for Different Outcomes
  • 5.9 Measuring the Success of Sales Forecasts

Module 6: Enhancing Sales Processes with AI

  • 6.1 Task Automation
  • 6.2 AI-Driven Email Marketing
  • 6.3 Social Media Analytics with AI
  • 6.4 AI-Powered Lead Generation
  • 6.5 Customer Segmentation
  • 6.6 Optimizing Sales Visits and Calls
  • 6.7 Tailoring Content with AI Insights
  • 6.8 Real-Time Sales Activity Monitoring
  • 6.9 Upselling and Cross-Selling with AI

Module 7: Ethical Considerations and Bias in AI

  • 7.1 Ethical Use of AI in Sales
  • 7.2 Bias Identification in AI Systems
  • 7.3 Bias Mitigation Techniques
  • 7.4 Transparency in AI Decision-Making
  • 7.5 Accountability for AI Actions
  • 7.6 Safeguarding Customer Data
  • 7.7 Regulatory Compliance
  • 7.8 Building Customer Trust through Ethical AI
  • 7.9 Anticipating Ethical Issues in AI Advancements

Module 8: Practical Workshop

  • 8.1 Scenario-Based Exercises
  • 8.2 Addressing Sales Challenges with AI
  • 8.3 Collaborative AI Implementation Plans

Optional Module: AI Agents for Sales

  • What Are AI Agents?
  • Types of AI Agents
  • Applications and Trends of AI Agents in Sales

World Food Programme (WFP)

Our work with the World Food Programme (WFP) focused on enabling the effective adoption of digital field technologies and essential digital literacy capabilities. Participants utilized mobile-based data collection platforms within operational contexts, enhancing accuracy, consistency, and confidence in digital data handling. The engagement strengthened WFP’s ability to rely on digital tools to support field operations and humanitarian programs.

Raya

For Raya, we delivered technology enablement focused on automation-driven operations and scalable application development. Participants gained hands-on experience with automation technologies and modern front-end development frameworks, supporting more efficient processes and the delivery of flexible, high-performance digital solutions aligned with business growth objectives.

EgyptAir

Our engagement with EgyptAir focused on enabling the effective use of application development technologies alongside the adoption of cybersecurity and secure computing practices within operational environments. Participants worked with Microsoft-based development platforms and programming technologies while gaining practical exposure to secure application usage, access control mechanisms, and threat-aware system interaction. This integrated technology enablement supported more secure digital operations, improved system reliability, and reinforced cyber resilience across aviation technology environments.

Banque Misr

We collaborated with Banque Misr to enable integrated enterprise technology capabilities across multiple domains. The engagement supported effective utilization of IT infrastructure environments, data analytics platforms, and professional capability development frameworks, allowing teams to operate confidently within complex enterprise systems. Our delivery approach focused on practical technology adoption, operational alignment, and building sustainable competencies that support reliable banking services and informed, data-driven decision-making.

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