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AI in Business

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Definition of AritificialIntelligence(A)

AI is the ability of computers to mimic or duplicate the functionsof the human brain

Artificial Intelligence(AI) is the intelligence of machines and htebranch of computer science that aims to create it.

It is the study and design of intelligence agents AI is a broad discipline that promises to simulate numerous

innate human skills such as automatic programming, case-basedreasoning, neural networks, decision-making, expert systems,natural language processing, pattern recogrnition and speech

recognition etc.

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Nature of Intelligence

Learn from the experience and apply knowledge acquired fromexperience

Computerized AI chess software

Handle complex situations

Solve problems when important information is missing Determining what is important

React quickly and correctly to a new situation

Understand visual images

Perceptive systems : approximate teh way human see, hear , or feel objects Process and manipulate symbols

On a limited basis with machine vision hardware and software

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Importance of AI

Enterprise that utilize AI enhancedapplications, are expected to become morediverse, as the needs for the ability to analyze

data across:- Multiple variables

Fraud detection

Customer relationship management

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Applications of AI

AI based systems have many apoplications indifferent fields such as

Medical diagnosis

Exploration for natural resources Determining what is wrong with mechanical

devices

Assisting in designing and developing othercomputer systems.

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Emergence of AI in business

AI aims to improve machine behaviour intackling complex tasks.

Humans have an interesting approach to problem

solving, based on abstract though, high-leveldeliberative reasoning and pattern recognition.

AI can help us understand this process byrecreating it, then potentially enabling us to

enhance it beyond our current capabilities.

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Applications of AI

Business applications such as

Unknown patterns / relationships in sales data

Customer bying habbits

Complex problem solving and decision supporttechniques in real time business applications

AI techniques are spread across functions rangingfrom finance management to forecasting and

product.

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Artificial Neural Networks

An artificial neural network(ANN) is a mathematical model orcomputational model based on biological neural networks

It consists of an interconnected group of artificial neurons andprocesses information using a connectionist approach to

computiation. In practical terms neural networks are non-linear statistical

data modeling tools. They can be used to model complexrelationships between inputs and outputs or to find patterns indata.

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Real life applications of ANN

The tasks to which artificial neural networks areapplied tend to fall within the following broadcategories

Function approximation or regression analysis,including time series prediction and modelling

Classification, including pattern and sequencerecogntion, notely detection and sequential decisionmaking.

Data processing including filtering, clustering, blindsource separation and compression.

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Advantages of ANN

View your best product runs and thecorrecsponding settings

Increase efficiency and quality by using

optimal settings from pastt production Artificial intelligence can optimize your

schedule beyond normal human capabilities.

Increase productivity by eliminating downtimedue to unpredictable changes in the schedule.

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AI in Financial Services

In the field of finance, artificial intelligence has longbeen used. Some applications of artifical intelligence are

Credit authorised screening

Mortgauge risk assessment

Project management and bidding strategy

Financial and economic forecasting

Risk rating of exchange-traded, fixed income investments

Detection of regularities in security price movements

Prediction of default and banruptcy

Security / and or Asset Portfolia Management

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AI in Markteting

In Marketing, Some applications of artificialIntelligence are

Computerized neural networks

Customer relationship management High tech data mining can give companies a

precise view of how particular segments of thecustomer base react to a product or service

Buying patterns, analytics could help companiesreact much more quickly to the marketplace.

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AI in HR

Some applications of AI in HR are

Use of neural networks and fuzzy logic in humanresource information system(HRIS)

Fuzzy neural network, to construct a new modelfor evaluation of managerial talent, andaccordingly to develop a decision support systemin human resource selection.

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AI in banking

Bank business intelligence (BI) is the collection of information concerning a bank's operations to help itaddress issues, develop strategies, and improve services to customers.

Banks can rely on an internal department to collect, analyze, and contextualize information, or they can hireconsultants to provide this service. Firms across the financial industry use BI to be more flexible andpowerful in the market, and numerous seminars provide instruction in how to gather and use informationeffectively.

One aspect of bank business intelligence involves the collection of data on customers and customer relations.This includes raw statistics on numbers of customers, types of accounts, and assets held with a given financial

institution. It can also involve surveys, demographic analysis, and other measures to learn who banks with agiven company and why. The bank may also perform analysis of competing institutions to find areas ofsimilarity and difference, to learn more about the industry as a whole and its role in it.

Internal research can also be important. Part of bank business intelligence may involve analysis of personnel,from management to the mail room, to learn more about how they feel about their work.

A bank that remains alert to employee concerns and issues can improve employee retention and reduce therisk of problems caused by upset employees.

A bank staffer might, for instance, feed confidential information to a rival in retaliation for unpleasantworking conditions.

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Information Overload

hose who are able to handle the problem, will be able to convert this problem toopportunities, an excess of information is essential to business decision-making. In otherwords, managers wish that they had all available information to help them makedecisions.

To be able to analyse information and locate the useful gold nuggets in this informationmine is understandably imperative in the highly competitive business market.

t seems that various types of AI solutions to the information problem are slowly creepinginto the business arena. Many people have contact with AI without knowing it (forexample, search engines, the Microsoft office package, and knowledge-based systems.

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CRM: Behaviour Analysis...

Internet bookstore Amazon.com uses AI to learn about its customers'tastes in books. When someone signs on toAmazon, the software greets the customer by his or her name, and gives him or her recommendations on books. Theserecommendations, which are based on the customers previous buying patterns, suggest similar reading material.

Dr. Martin (2000) writes about the importance of collecting and analysing customerinformation in the article AlienIntelligence in Journal of Business Strategy, he implies: Electronic commerce can be designed so thatsoftware can learn what products customers are likely to buy, what changes they would like inthe products, where to look for new customers, and so on

Federal Express Corporation (FedEx), the world' s largest express transportation company, discovered, through an

internal analysis, that picking up customers packages from them cost significantly more than servicing customers whodropped off their own packages

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...CRM: Behaviour Analysis

Expert Systems can help card issuers determine whether to accept a proposed credit cardpurchase. John McCarthy (2000), a Professor of Computer Science at StanfordUniversity and is one of the founders of modern AI confirms this statement.

MasterCard and Visa both offer their members a Neural Network (NN) method, whichcan identify deviations in spending habits of cardholders that could indicate fraud

Rabkin and Tingley (1999) confirm that credit card companies use ANN to detect fraud,

in their article Life & health/financial services ed in the National Underwriter. Theynote further that not only ANN, but also Genetic Algorithms and Expert Systems, areused to improve the detection of fraud.

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CRM: Support and Marketing

The most common AI-based advisory system is probably the Office Assistant in Microsofts Office 97 and 2000. the Office Assistantuse uses Bayesian belief network to guess when the user needs help and why

In 1997, the Toronto Dominion Bank Financial Group (TD) was receiving more than 2,000 e-mail per month from its customers, andthat number kept rising. TD went with Brightwares (now Firepond) AI-based software eServicePerformer, which handles TDs e-mailby automatically understanding the content of the messages, classifying them for appropriate handling, and dynamically composingreplies to questions in incoming messages. TDs workers only have to review, approve and send the fully composed, personalizedresponses

Hewlett Packard (HP), one of the leading manufacturers of computer network technology, wanted to increase the support of sales staff,employees, customers and potential clients by providing an online advice system.The interactive advice system CAST/BW, providesquick, accurate hardware sizing, network configuration, and usage recommendations. The system turns expert knowledge from SAP,HP internal competency centres, the HP Enterprise Server Group, and existing SAP Business Warehouse implementations into an easy-to-use advisory tool.This Case Study shows how an Expert System can provide worldwide knowledge support, 24 hours a day, andreduce work, phone calls, and e-mail.

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CRM: Support and Marketing

I techniques can be used to find patterns that indicate which customers withcertain characteristics should be targeted for highly focused marketing.

eOffers is a Hybrid System that is partly an ANN and partly an ExpertSystem. eOffers analyses proposed marketing messages and campaignsusing rules set by marketing managers and filtered through multiple

messages that may be directed at the same customer to select the mostappropriate one. The system also controls how often a message should besent to the same customer. The company Fidelity is working with thismarketing management agent system.

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Company Management

Control;

An American Management Association survey this year found that 38 percent of the major U.S. companies (2100 firms)check their employees' e-mail and 54 percent monitor Internet connections. Of the 2,100 firms responding to the survey,17 percent have fired employees for misusing the Internet. Twenty-six percent have given workers formal reprimandsand 20 percent have issued informal warnings. (FORMAN, 2000)

IT managers have increasingly had problems with employee abuse of the Web. RuleSpace Inc.' s WebTraffic Control is a tool that uses Neural Network (SLAUGHTER, 1999) to analyse the content of a Webpage. It can prevent employees from visiting sites that are judged inappropriate based on content such as:

pornography, hate material, weapons, drugs, gambling, stock trading, or job searches. nstead of relying onlists of already identified URLs or keywords, it examines text, images and network associations to identifyand classify the page (RULESPACE, 2001).

Companies are not only concerned about lost productivity, he point out, but also are afraid of lawsuits thatcould arise from employees being exposed to an inappropriate Web site on a colleague' s screen. Yasininforms us in his article that Xerox Corp has fired more than 40 employees ver the past year forinappropriate use of the Web.

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Company Management

Content Management

Managers in companies pray for correct and timely information to support their decisions,instead of having torely on a gut feeling. Information like faxes, e-mails, commercial information, Intranets (small-scale Internetswithin a company), the Internet, and corporate databases is now flooding companies. Thus, there is anoverwhelming need for intelligent agent software that operates on behalf of humans, processing suchinformation in a highly automated and customized fashion.

NQL, whose customers include General Motors, CMGI, Lycos, and other Fortune 1000 companies, haspatented a Network Query Language development platform used for the creation of an intelligent agent. NQL

uses: Bayesian inference, Neural Network, and Fuzzy Logic that, in combination, make it possible to handlecategorization and delivering the right content to the right person inside Microsoft Office applications.

Dallas Teachers Credit Union (DTCU) decided to become a community bank. The problem was where tobuild a branch office that would allow them to achieve their goal? One of their targets was to locate peoplewho might open checking accounts (which DTCU considered easy money). Through IBMs BusinessIntellegence Software By using this geographical data analysis, which draws information about the physicallocation of bank customers or prospective customers, it increased its customer base from 250,000professional educators to 3.5 million potential customers

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Production Management

Scheduling

A rich set of choices sometimes causes severe headaches in manufacturing.

Martin point out that half-assembled machines could easy pile up at one workstation while another workstation remainedidle. He describes a case were Genetic Algorithms have helped John Deere & Company with scheduling. Deere, founded in1837, produces farm products, does business in more than 160 countries and employs approximately 43,000 people worldwide(DEERE, 2001). Martin (2000) concludes that the company, which found it difficult to control their inventory, was able tosolve their problem by employing Genetic Algorithm (GA) technique that learned to breed factory schedules far better thanthose humans could. Dr. Martin reports that with help of GA the farm production line is running more smoothly.

When an oil company exploits a reservoir, many wells are drilled through similar topography and under similar drilling

conditions. Human experts learn from the experience gained during the drilling of the first several wells, and subsequent wellsare often brought in more quickly. Neural Networks are a technology that is particularly well suited to automating this type ofcomplex activity. tools like ANN give oil companies the advantage of drilling fewer dry holes, hitting drilling targets faster,and exploiting reservoirs more efficiently than their competitors

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Finance Management

Some believe that computers with Neural Networks are better at selecting stocks than people are.

more and more companies are starting to use AI, including Fidelity Investments Inc., NeuWorldFinancial, Advanced Investment Technologies, the Dutch pension fund ABP, etc.

NeuWorlds AI system, which uses Neural Network technology to recognise patterns and intricaterelationships, is called Eagle 12. It is pattern recognition that allows the machine to analyse largeamounts of data for forecasting purposes. According to Barreto (2001), Eagle 12 analyses 4,000 U.S.stocks quarterly, using 116 variables while Wall Street analyst covers 30 to 40 stocks and uses fewer

than 10 variables. After the analysis Eagle 12 categorizes the stock into five categories. The first category is stocks that the computer forecasts to increase by 50% or more within the next 12 months,

they are normally recommended for purchase.

The second category, stocks up between 20 and 50%, are also recommended for purchase.

In the third category are the stocks that are expected to be up between zero and 20%. Those stocks are neitherrecommended for purchase or sale.

The last two categories contain stocks that are expected to drop and are, therefore, recommended for sale if theyare in the portfolio.

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Conclusion

It is difficult for business to see general relevance from AI.

AI can have a positive effect for business benefits and has lead to somevery useful systems that have found their way into the heart of businessactivity. Business should not loose sight of where

AI could go because there are many potential benefits to current and

new business of future research. The idea of robotic domestic workers is still far fetched but companies

are mking progress even here.

There is already a robot vaccum cleaner marketed by Electrolux anddoubtles improved systems with better functinoality will follow...