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The Smart Techie was renamed Siliconindia India Edition starting Feb 2012 to continue the nearly two decade track record of excellence of our US edition.

May - 2007 - issue > Technology

Artificial Intelligence in the Enterprise

Dr.Kaustubh Chokshi
Tuesday, May 1, 2007
Dr.Kaustubh Chokshi
Not too long ago, any mention of the term ‘Artificial Intelligence’ in front of CIOs would most likely evoke in them feelings of disdain, contempt and cynical dismissal. It’s no secret that Artificial Intelligence technology and neural network software suffered from a credibility gap, and the chasm between promise and delivery seemed unbridgeable.
All that is history now. Today, no CIO or IT Head worth his salt would risk cocking a snook at AI, for AI technology is firmly embedded in a wide range of applications software, and is gradually weaving its way into enterprise applications as well. In fact, cutting-edge AI techniques are being used to develop enterprise software that can dynamically adapt to rapidly changing business environments, while simultaneously providing high levels of decision support and trends forecasting for enterprise managers to act on.

The key difference between traditional, logic-based software and software based on AI is that the latter can be trained, and learns from experience. It is equipped to acquire knowledge from the data generated within the organization, as well as from expert opinion and external data sources.

Non-Linear Decision Making
The above consideration is extremely important because businesses operate in a non-linear environment, characterised by hard-to-predict (but non-random) cause and effect relationships. Mere logic-based software would only be able to provide a primitive level of decision support in such situations.

On the other hand, decision management using AI is a systematic approach to automating and improving decisions across the enterprise. AI-based decision support systems aim to increase the precision, consistency and agility of operational and tactical decisions made in the organization, while reducing the time taken to decide (decision latency), and the cost involved in making each decision.


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