Im­pact of AI on Pre­dic­tive Anal­y­sis

Distinguished Magazine - - CONTENT - NAMRATA GULATI SAPRA

When ap­plied to prob­lems be­yond hu­mans ca­pa­bil­i­ties, AI can drive ef­fi­cien­cies, pro­duc­tiv­ity to scale busi­ness op­er­a­tions to gen­er­ate higher prof­its and sales.

Ar­ti­fi­cial In­tel­li­gence (AI) is de­fined as the part in ma­chines that en­able them to re­act and work much like hu­man be­ings. Ma­chines can of­ten act and re­act like hu­mans, only if they have abun­dant in­for­ma­tion re­lat­ing to the world. Ar­ti­fi­cial in­tel­li­gence must have ac­cess to ob­jects, cat­e­gories, prop­er­ties, and re­la­tions be­tween all of them to im­ple­ment knowl­edge engi­neer­ing. Ini­ti­at­ing com­mon sense, rea­son­ing and prob­lem-solv­ing power in ma­chines is a dif­fi­cult and te­dious task. So re­search as­so­ci­ated with ar­ti­fi­cial in­tel­li­gence is highly tech­ni­cal and spe­cial­ized.

To shape a ma­chine into func­tion­ing as a hu­man be­ing, the fol­low­ing traits have to be fac­tored:


Hu­man be­ings have the abil­ity to learn and gain knowl­edge of var­i­ous sub­jects


Hu­mans do try to find the cause for each and ev­ery ac­tion or do have the ex­pla­na­tion for it


Ma­chines are also used for solv­ing dif­fer­ent prob­lems, but only after re­ceiv­ing in­struc­tions. Hu­mans, how­ever, have the self-abil­ity to find a so­lu­tion


Hu­mans can per­cept or il­lus­trate the ideas of a cer­tain con­cept.

Ro­bot­ics is also a ma­jor field re­lated to Ar­ti­fi­cial In­tel­li­gence. Ro­bots re­quire in­tel­li­gence to han­dle tasks such as ob­ject ma­nip­u­la­tion and nav­i­ga­tion, along with sub-prob­lems of lo­cal­iza­tion, motion plan­ning, and map­ping.


In simple terms, pre­dic­tive an­a­lyt­ics is look­ing at a set of data what is al­ready known and try­ing to make an ac­cu­rate guess at some­thing which will happen in the fu­ture that is some­thing un­known. Pre­dic­tive anal­y­sis is im­prov­ing sales pro­cesses with bet­ter lead scor­ing, mar­ket­ing with cheaper, more ef­fec­tive ads and op­ti­miz­ing cus­tomer suc­cess by pre­dict­ing and re­duc­ing churn.

With re­cent ad­vance­ments in com­puter tech­nol­ogy; AI is no longer just a cy­ber­punk fan­tasy. Cloud com­put­ing, cy­ber­se­cu­rity, and Robotic Process Au­to­ma­tion are a few of the in­dus­tries reap­ing all the ben­e­fits of this, with many com­pa­nies seek­ing to stream­line their work­flow by au­tomat­ing key events in the pipeline.


Ar­ti­fi­cial In­tel­li­gence is grad­u­ally de­vel­op­ing it­self as the undis­puted face of mod­ern tech­nol­ogy. But tra­di­tional pre­dic­tive anal­y­sis method in­cludes au­ton­o­mous tools to get in­sight ap­proach de­pend­ing on tech­nol­ogy based on old tech­nolo­gies. Ar­ti­fi­cial In­tel­li­gence can self-adjust with­out hu­man in­ter­ven­tion and change un­der­ly­ing al­go­rithms based on vast new sim­u­lated data in­puts to find the optimal out­come while pre­dic­tive anal­y­sis may uti­lize ma­chine learn­ing in that it ad­justs based on new limited data sets based only on the his­tor­i­cal in­for­ma­tion avail­able.

When ap­plied to prob­lems be­yond the ca­pa­bil­i­ties of hu­mans, AI can drive ef­fi­cien­cies, pro­duc­tiv­ity, and al­low com­pa­nies to scale busi­ness op­er­a­tions to gen­er­ate higher prof­its and sales, and out­flank the com­pe­ti­tion.

Like ev­ery­thing, sci­ence also has its ad­van­tages and dis­ad­van­tages. Ar­ti­fi­cial in­tel­li­gence may be more ef­fi­cient with in­creased work rates and would pro­duce more out­put but be­ing too de­pen­dent on ar­ti­fi­cial in­tel­li­gence may lead to harm­ful con­se­quences. After all, re­ly­ing on hu­man be­ings and ar­ti­fi­cial in­tel­li­gence are two dif­fer­ent things and each of them has their say in de­cid­ing the out­come of a cer­tain in­stance.

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