Scope of Artificial Intelligence in Business enterprise

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The business applicability of AI techniques is spread across functions ranging from finance management to forecasting and production. AI technologies help enterprises reduce latency in making business decisions, minimize fraud and enhance revenue opportunities.Definition of AI AI is a broad discipline that promises to simulate numerous innate human skills such as automatic programming, case-based reasoning, neural networks, decision-making, expert systems, natural language processing, pattern recognition and speech recognition etc. AI technologies bring more complex data-analysis features to existing applications.There are many definitions that attempt to explain what Artificial Intelligence (AI) is. I like to think of AI as a science that investigates knowledge and intelligence, possibly the intelligent application of knowledge. AI is really an investigation into the creation of intelligence and that there is no reason for the intelligence that is created to be exactly the same as human intelligence.Importance of AI Enterprises that utilize AI-enhanced applications are expected to become more diverse, as the needs for the ability to analyze data across multiple variables, fraud detection and customer relationship management emerge as key business drivers to gain competitive advantage. Our ability to combine knowledge from all these fields will ultimately benefit our progress in the quest of creating an intelligent artificial being.Emergence of AI in business Artificial Intelligence (AI) has been used in business applications since the early eighties. Artificial Intelligence aims to improve machine behavior in tackling such complex tasks.Together with this, much of AI research is allowing us to understand our intelligent behavior. Artificial Intelligence can help us understand this process by recreating it, then potentially enabling us to enhance it beyond our current capabilities.Applications of AIThe potential applications of Artificial Intelligence are abundant. AI technologies bring more complex data-analysis features to existing applications.Business applications utilize the specific technologies mentioned earlier to try and make better sense of potentially enormous variability (for example, unknown patterns/relationships in sales data, customer buying habits, and so on). However, within the corporate world, AI is widely used for complex problem-solving and decision-support techniques in real-time business applications. The business applicability of AI techniques is spread across functions ranging from finance management to forecasting and product Artificial Neural NetworksAn artificial neural network (ANN), often just called a "neural network" (NN), is a mathematical model or computational model based on biological neural networks. In more practical terms neural networks are non-linear statistical data modeling tools. Real life applications of ANNThe tasks to which artificial neural networks are applied tend to fall within the following broad categories:• Function approximation, or regression analysis, including time series prediction and modeling.• Classification, including pattern and sequence recognition, novelty detection and sequential decision making.• Data processing, including filtering, clustering, blind source separation and compression.Application areas include system identification and control (vehicle control, process control), game-playing and decision making (backgammon, chess, racing), pattern recognition (radar systems, face identification, object recognition and more), sequence recognition (gesture, speech, handwritten text recognition), medical diagnosis, financial applications (automated trading systems), data mining (or knowledge discovery in databases, "KDD"), visualization and e-mail spam filtering.The proven success of Artificial Neural Networks (ANN) and expert systems has helped AI gain widespread adoption in enterprise business applications. Artificial Intelligence in manufacturing can be applied to a variety of systems. Artificial Intelligence can optimize your production schedule and production runs. • Artificial Intelligence can optimize your schedule beyond normal human capabilities. Sophisticated technologies encompassing neural networks and business rules along with AI-based techniques are yielding positive results in transaction-oriented scenarios for financial services. This study focuses on applying AI in Finance, particularly in stock trading. In the field of Finance, artificial intelligence has long been used. Then, we move into how AI systems for stock trading will affect traders, companies and individuals. Recommendations include getting management buy-in, implementing the system and managing the whole structure to succeed.Artificial Intelligence in MarketingAdvances in artificial intelligence (AI) eventually could turbo-boost customer analytics to give companies speedier insights into individual buying patterns and a host of other consumer habits.