How Artificial Intelligence is Used – FESCH.TV

How Artificial Intelligence is Used & FESCH.TV:

DEFINITIONS:
Artificial Intelligence (AI) is the simulation of human intelligence in machines designed to perform tasks that typically require human cognition, such as understanding language, recognizing patterns, solving problems, and making decisions. AI encompasses various subfields, each with unique capabilities and applications in the business world. Below are some key uses of AI: Descriptive Analysis, Predictive Analysis, Recommendation Systems, and Generative AI.
1. Descriptive Analysis
DESCRIPTION:
Descriptive analysis is the process of using AI to analyze historical data and summarize it in a way that is easy to understand. It focuses on answering the question, „What happened?“ by identifying patterns, trends, and relationships in past data. This type of analysis is foundational and helps businesses make sense of large amounts of data by providing insights into past performance.
BUSINESS USE CASE EXAMPLE:
In retail, a company might use AI-powered descriptive analysis to evaluate sales data from the past year. The AI system could identify which products sold the most during different seasons, what the average sale amount was, and how customer behavior changed during sales promotions. This information helps the company understand its past performance and plan future inventory and marketing strategies.
2. PREDICTIVE ANALYSIS
DESCRIPTION:
Predictive analysis involves using AI to analyze historical data and identify patterns that can predict future outcomes. It answers the question, „What is likely to happen?“ by using models and algorithms to forecast trends, customer behaviors, and potential risks.
BUSINESS USE CASE EXAMPLE:
A financial services firm might use predictive analysis to forecast credit risk. By analyzing a client’s past financial behavior, the AI system can predict the likelihood that the client will default on a loan. This allows the firm to make informed decisions about lending, reducing risk and improving profitability.
3. RECOMMENDATION SYSTEMS
DESCRIPTION:
Recommendation systems are AI-driven tools that analyze user data to suggest products, services, or content that the user is likely to find appealing. These systems answer the question, „What should be suggested?“ by using data such as previous purchases, browsing history, or preferences to make personalized recommendations.
„What should be suggested?“ using previous purchases, browsing history, or preferences to make personalized recommendations.
BUSINESS USE CASE EXAMPLE:
A streaming service like Netflix uses a recommendation system to suggest movies and TV shows to its users. The AI analyzes what users have watched, liked, or rated highly in the past and recommends similar content, enhancing user experience and keeping customers engaged with the platform.
4. GENERATIVE AI
DESCRIPTION:
Generative AI refers to AI systems that can create new content, such as text, images, music, or even entire products, based on the data they have been trained on. This type of AI answers the question, „What can be created?“ by using existing information to generate novel outputs.
BUSINESS USE CASE EXAMPLE:
In the fashion industry, a company might use generative AI to design new clothing lines. The AI system can analyze current fashion trends and generate new designs that align with those trends. Designers can then use these AI-generated concepts as inspiration, accelerating the creative process and bringing new products to market faster.
These different uses of AI—descriptive analysis, predictive analysis, recommendation systems, and generative AI—demonstrate how AI can be applied to various aspects of business to improve decision-making, personalize customer experiences, forecast future trends, and even create new products or content.