chat­bots will trans­form user in­ter­ac­tion

The Smart Manager - - Leadership What’s In Store?what’s In Store? - Ralph Vaz, co-founder Ace­bot and Snippect

Ar­ti­fi­cial in­tel­li­gence (AI) cre­ated a loud buzz in the world of tech­nol­ogy. We have wit­nessed a dra­matic rise in its us­age, not only im­pact­ing the in­ter­net and soft­ware in­dus­try but also in other ver­ti­cals like health­care, au­to­mo­bile, man­u­fac­tur­ing, and more. AI is no longer a fu­tur­is­tic tech­nol­ogy; it is now used in sev­eral in­dus­tries. Here are trends we will see in two such in­dus­tries.

Be­ing present in the chat­bot space over the last three years has been about mak­ing con­ver­sa­tional user in­ter­face work across dif­fer­ent in­dus­tries with a fo­cus in re­search and mar­ket­ing. The fastest grow­ing trend in the AI space, con­ver­sa­tional in­ter­face (aka chat­bots), has changed the way users in­ter­act with busi­nesses.

Our take on chat­bots in 2019 is that they have been con­tin­u­ously proven to ef­fec­tively im­prove sales, mar­ket­ing, and sup­port kind of ac­tiv­i­ties.


The health­care sec­tor will be dra­mat­i­cally en­hanced by AI. To­day, when patho­log­i­cal tests are con­ducted, blood sam­ples are de­liv­ered to the lab, which then ex­am­ine them, and after the anal­y­sis pro­ce­dure is com­pleted, sub­mit the re­port. The lim­i­ta­tion here is the wait­ing pe­riod. AI will help cut down the time taken by run­ning im­age or pat­tern recog­ni­tion in blood cells quickly and ef­fi­ciently. This will also have a pos­i­tive im­pact on cus­tomer ser­vice.

Pre­vi­ously, bots were more preva­lent in pro­cesses such as the in­ter­ac­tive voice re­sponse (IVR)—ba­si­cally, a bot re­spond­ing to com­mands. In the ab­sence of a se­lec­tion menu, the IVR would not be able to func­tion. With AI com­ing into play, when one switches in­tent the bot would still un­der­stand and re­spond ap­pro­pri­ately.

Face recog­ni­tion will also be uti­lized in health­care as it is all about rec­og­niz­ing pat­terns to es­tab­lish a di­ag­no­sis. AI is not about math­e­mat­i­cal pre­ci­sion but about av­er­ag­ing—it is about group­ing re­sults that seem as close to the orig­i­nal data set. Hav­ing said that, if you take a very small data set, AI will give in­ac­cu­rate an re­sult. So, if only a small set of his­tor­i­cal data is con­sid­ered, it is less likely that the sys­tem would iden­tify pat­terns. Huge chunks of data leads to pre­cise anal­y­sis.

bank­ing and fi­nance

In 2019, chat­bots used in the bank­ing and fi­nan­cial sec­tors are go­ing to be more in­tel­li­gent. We have al­ready seen the first phase of chat­bots and the im­ple­men­ta­tion of AI. The next phase will be even bet­ter—AI will be used in fraud de­tec­tion. It will look at a bunch of pat­terns, an­a­lyze them his­tor­i­cally, and create new ones based on those to un­der­stand how fraud oc­curs. This tech­nol­ogy does not ex­ist yet, but it will, soon. An­other as­pect AI will prove to be ad­van­ta­geous in is ATMs. All ATMs have a cam­era mon­i­tor­ing them and there is a pos­si­bil­ity that some­one is on the other side look­ing at the footage. But what if this per­son is not at­ten­tive? If AI is used in­side an ATM, it can find pat­terns in the video. The ac­tions of how some­body comes in, looks around, and whether she tam­pers with the ma­chine, all of this can raise an alarm im­me­di­ately. The tech­nol­ogy is there and these ad­vance­ments will soon come to play. Stock mar­kets too may adopt AI tech­nol­ogy as it can study the pat­terns in mar­ket in­dices and his­toric data on mar­ket move­ments and pre­dict when the mar­kets will be volatile and will move in a cer­tain di­rec­tion, etc.

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