DocumentCode
1109641
Title
AI tools for business-process modeling
Author
Hedberg, Sara Reese
Author_Institution
Issaquah, WA, USA
Volume
11
Issue
4
fYear
1996
fDate
8/1/1996 12:00:00 AM
Firstpage
13
Lastpage
15
Abstract
For more than a decade, artificial intelligence techniques have served as critical building blocks for cutting edge business applications. Knowledge based systems (KBS) in particular have helped numerous Fortune 1000 companies solve pressing business problems-everything from scheduling their manufacturing operations to managing their investment portfolios. AI has helped many companies improve productivity and reduce costs to meet the demands of today´s competitive global economy. Today, business management itself is undergoing fundamental change. For the past several years, business process reengineering (BPR) has become the watchword. This move to rethink and redesign the way a company works aims at further boosting productivity and cutting costs. No wonder then that business managers worldwide are turning to explicit KBS techniques, long proven to achieve the very goals of BPR, to model change. The first wave of AI based tools and applications for business process modeling (BPM) is just hitting the shore. Organizations such as IBM, EDS, the US Army, and Swiss Bank are among the first to adopt AI for BPM. Some are using traditional KBS tools such as ART*Enterprise and ProKappa, while others are turning to ReThink, the first AI tool designed specifically for BPM
Keywords
business data processing; knowledge based systems; systems re-engineering; AI tool; AI tools; ART*Enterprise; Fortune 1000 companies; KBS techniques; KBS tools; ProKappa; ReThink; artificial intelligence techniques; business management; business managers; business process modeling; business process reengineering; competitive global economy; cutting edge business applications; investment portfolios; knowledge based systems; manufacturing operations; productivity; Artificial intelligence; Business process re-engineering; Companies; Costs; Job shop scheduling; Knowledge based systems; Manufacturing; Pressing; Productivity; Turning;
fLanguage
English
Journal_Title
IEEE Expert
Publisher
ieee
ISSN
0885-9000
Type
jour
DOI
10.1109/64.511772
Filename
511772
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