This presentation provides an overview of AI technologies, with a specialization in Machine Learning, Robotics, and Generative AI. It offers a gentle introduction to these concepts, making it accessible to readers with varying levels of knowledge. The presentation shares case studies showcasing the application of AI in different business domains. In Sales & Marketing, one case study focuses on sales forecasting. AI algorithms analyze historical data and market trends to predict future sales, enabling businesses to make informed decisions and optimize their strategies. In the Customer Support domain, the case study highlights the use of Product Specialist Bots. These AI-powered bots assist customers by addressing their queries and providing relevant information. They enhance customer support efficiency by offering quick and accurate responses, ultimately improving customer satisfaction. The Product Management case study emphasizes the application of AI in ideation and brainstorming processes. AI tools aid in generating innovative ideas by leveraging data insights and providing design recommendations. This enables businesses to enhance their product development and stay ahead in a competitive market. In the Finance sector, the case study focuses on account reconciliation. AI automates the reconciliation process, reducing manual effort and minimizing errors. By streamlining this crucial financial task, businesses can achieve greater accuracy and efficiency in managing their accounts. The presentation also provides guidance on identifying opportunities for AI implementation. It emphasizes the importance of assessing business needs and identifying areas where AI can bring significant benefits. By understanding specific challenges and requirements, organizations can identify the most suitable AI applications and align them with their goals. Additionally, the presentation offers insights into building a business use case for AI. It outlines a systematic approach to developing a strategy for AI implementation. This involves understanding the potential impact of AI on business processes, evaluating available AI solutions, considering resource requirements, and creating a roadmap for successful integration. In summary, the presentation provides an overview of key AI technologies, namely Machine Learning, Robotics, and Generative AI. It presents case studies in Sales & Marketing, Customer Support, Product Management, and Finance, showcasing the practical applications of AI in these domains. The presentation also provides guidance on identifying AI opportunities and building a business case for AI implementation, helping readers understand the value and potential of AI in their organizations.

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Introduction to
Artificial Intelligence
Thomas Chea
h
Solution Architect

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Our Specialties in AI
Machine Learning
Training computers to
learn patterns and make
intelligent predictions.
• Image Recognition
• Fraud Detection
• Personalized Recommendations
• Financial Market Prediction
• Customer Sentiment Analysis
Software Robotics
Automate repetitive tasks
using software robots for
efficiency and accuracy.
• Report Generation
• Customer Onboarding
• Invoice Processing
• Claims Processing
• Customer Service and Support
Generative AI
Generates new content,
such as images, music, or
text without human input.
• Content Generation and Marketing
• Chatbots and Virtual Assistants
• Virtual Prototyping and Design
• Market Simulation and Forecasting
• Pricing Optimization

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Case Study: Sales Forecasting
Global electronics manufacturer
and retailer adopted AI and
machine learning techniques to
enhance its sales forecasting
accuracy and optimize inventory
management.
Challenge:
Limitations with traditional sales forecasting methods had led
the company to inaccurate projections, excess inventory, and
missed sales opportunities.
Solution:
Machine learning-based solution that captured patterns and
relationships in sales data, leading to accurate demand
forecasting and continuous adaptation to changing market
dynamics.
Results:
Enhanced accuracy, optimized inventory, providing insights for
efficient planning and decision-making, and meeting customer
demand effectively.

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Case Study: Product Specialist Bot
Local town council implemented
AI-powered Product Specialist
Bots to improve service efficiency
and deliver timely information for
addressing inquiries from
residents.
Challenge:
Wide range of resident inquiries, including services, permits,
events, and local regulations. The high volume of inquiries often
led to delays, long wait times, and overwhelmed staff.
Solution:
AI-powered Product Specialist Bots trained with comprehensive
dataset of local regulations, frequently asked questions, service
offerings, and previous resident interactions, to provide real-
time, accurate responses to resident inquiries.
Results:
Improved service efficiency, delivered timely information,
achieved cost savings, and enhanced resident engagement.

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Case Study: Ideation & Brainstorming
Software R&D company
implemented AI-driven tools to
support their product managers
in the ideation process.
Challenge:
Traditional brainstorming process was time-consuming and
often resulted in limited creativity and repetition of ideas.
Solution:
Generative AI tools trained on diverse data of existing products,
market trends, and consumer preferences to generate novel
product ideas based on specific requirements.
Results:
Constant source of inspiration, expanded the scope of ideation,
and facilitated the identification of market opportunities.

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Case Study: Account Reconciliation
Large healthcare organization
implemented software robotics to
automate complex financial
transaction reconciliation,
improving accuracy and
efficiency.
Challenge:
High transaction volume, multiple data sources, and complex
reconciliation rules, leading to delays and errors in the manual
account reconciliation process.
Solution:
Software robotics tools to automate and streamline account
reconciliation, involving data extraction and integration,
automated reconciliation, exception handling, and error
resolution, as well as validation and reporting.
Results:
Improved accuracy, efficiency, cost savings, streamlined
processes, enhanced compliance, and improved financial
control.

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How To Identify AI Opportunities
• Assess Business Processe
s
• Identify Data-Intensive Task
s
• Analyze Repetitive Task
s
• Look for Complex Decision-Makin
g
• Seek Customer Experience Improvement

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How To Identify AI Opportunities
• Examine Unstructured Data Challenge
s
• Address Predictive Analytics Need
s
• Analyze Customer Feedback / Sentimen
t
• Focus on Personalization /
Recommendatio
n
• Assess Risk and Compliance

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How to Build Your AI Business Case
Analyze Current
Process
Define New
Process
Identify Cost &
Benefits
Present
Business Case

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Thank you! Ask me about:
✓ Free AI Opportunity Assessment
✓ Free AI Opportunity Mapping
✓ Free AI Business Case Consulting
thomascheah@procto.biz