Cognizanti Part III Navigating The Digital Age

enthusiasm and optimism aboutAI, it also revealed AI’s nascentstage of adoption. For instance, thevast majority of AI projects (78%)remain in experimental stages (i.e.,proofs of concept and prototypes).Moreover, most respondentsexpect major or significantbenefits in terms of revenuegrowth from their use of AI. Infact, almost all expect valueto increase significantly withinthree years, with financialservices and technology industrycompanies leading the pack (seeFigures 1 and 2).The state of the stateof AI in businessThe following are the keytakeaways gleaned from our study: Most respondents considerAI to be vital to businesssuccess. The vast majority ofrespondents across industriesview AI as extremely or veryimportant to their business. Notsurprisingly, respondents werealso optimistic about AI’s abilityto generate benefits, includingcost efficiency, revenues andnew products and services.AI is infiltrating multiplebusiness functions. Amongall business functions,customer service appearsto be a prime target for AIuse across industries. This isunderstandable, since customersatisfaction, engagement andbuy-in is critical to ensuringbusiness success and justificationof an AI-led transformationagenda (see Figure 3, next page).Importance of AI to company success40%TECHNOLOGY32%FINANCIAL ETAIL50%31%MEDIA0%20%24%40% Very importantBase: 975 senior leaders in the U.S. & EuropeSource: Cognizant841%46%INSURANCEFigure 153%60%80% Extremely important100%

Expected revenue boost from AI42%TECHNOLOGY39%38%FINANCIAL URING32%43%INSURANCE27%41% 10%MEDIA0%20%40% Significant benefit60%80%100% Major benefitBase: 975 senior leaders in the U.S. & EuropeSource: CognizantFigure 2Top business functions for AI use30%CUSTOMER SERVICE26%MANUFACTURING PROCESS20%OPERATIONS18%RESEARCH & DEVELOPMENTFINANCE13%SALES & MARKETING13%9%SUPPLY CHAIN/PROCUREMENT7%HUMAN RESOURCES6%RISK & COMPLIANCE0%5%10%15%20%25%30%(Percent of respondents naming each function)Base: 975 senior leaders in the U.S. & EuropeSource: CognizantFigure 3Cognizanti 9

Organizations are also focusingtheir AI efforts on areas thatare core to the business, suchas operations in the healthcareindustry, production in manufacturing and R&D in technology. Choice of AI technology isinfluenced by functional areaand associated processes.Respondents reported usingall five of the AI technologiesincluded in our study at a fairlysimilar rate (see Figure 4).Many AI technologies currently in useSMART ROBOTICS/AUTONOMOUS VEHICLES35 %40%33%ANALYSIS OFNATURAL LANGUAGE45%54%42%40%44%ADVICE ENGINES/MACHINE LEARNING56%58%53%53%44%35%41%50%55%52%56%COMPUTER VISION35%44%42%51%49%44%VIRTUAL AGENTS41%0%10%20% Retail Media Healthcare InsuranceBase: 975 senior leaders in the U.S. & EuropeNote: Multiple responses allowedSource: Cognizant1030%60%46%42%Figure 458%49%47%40%50%58%52%72%60%70%80% Technology Manufacturing Financial Services

Organizations seem to attachequal importance to the varioustechnologies that can poweran AI strategy. However, virtualagents (conversational AI)and computer vision (machineintelligence algorithms thatrecognize patterns, amongother things) led other AItechnologies by a smallmargin. Respondents saidtheir companies are selectivelydeploying technologies tailoredto specific functional areas, suchas virtual agents for customerservice and bots in production. Faster-growing organizationsappear to be more optimisticabout AI and more aggressivein their AI adoption. Roughly85% of respondents at fastergrowing organizations expectAI to provide a major orsignificant impact on revenues,compared with 71% of slowergrowing businesses (see Figure5). A higher percentage offaster-growth organizationrespondents (89%) alsoexpect AI to provide a major orsignificant benefit in terms ofefficiencies that translate intoExpected revenue increase29%SLOWER-GROWTH BUSINESSES42%FASTER-GROWTH BUSINESSES55%0%20%40% Significant impact30%60%80%100% Major impactBase: 975 senior leaders in the U.S. & EuropeSource: CognizantFigure 5Expected cost reduction32%SLOWER-GROWTH BUSINESSES45%56%FASTER-GROWTH BUSINESSES0%20%40% Significant impact33%60%80%100% Major impactBase: 975 senior leaders in the U.S. & EuropeSource: CognizantFigure 6Cognizanti 11

cost reduction vs. slower growthbusinesses (77%) (see Figure6). While a significant majorityof faster-growth companies(66%) said AI will increase jobs,only 38% of respondents atbusinesses with slower growthrates said they believed this tobe true. AI adoption challenges spantalent acquisition, businesscases and ethics. Respondentsexpressed a similar level ofconcern regarding challengeson the path to AI, with 40% ofexecutives considering each ofthe 13 challenges listed to beextremely or very challenging.When that data is combinedwith the finding that only 15% ofrespondents were aware of a fullyimplemented AI project at theirorganization, it becomes clearthat most organizations have yetto hone a clear-cut AI strategy.Further, given that topchallenges related to seniormanagement commitment,business buy-in, adequatebudget and lack ofpreparedness, it’s apparentthat many companies are stillstruggling to define AI’s centralrole in advancing businessobjectives.Interestingly, technology industryrespondents were more apt thanrespondents in other industries tobe aware of ethical considerationsplaying a role in AI deployments(see Figure 7). This could be theresult of increased scrutiny ofthe FAANG (Facebook, Apple,Amazon, Netflix and Google)Concerns over ethical AI vary across industries55%TECHNOLOGY45%FINANCIAL RANCE41%29%MEDIA0%10%20%30%40%(Percent of respondents rating high orsignificantly high concern)Base: 975 senior leaders in the U.S. & EuropeSource: CognizantFigure 71250%60%

companies relative to their use ofdata- and algorithmic-enabledanalytical decision making, aswell as the issues they’ve hadto contend with regarding userprivacy. Sustainable and successfulAI deployments will need to bebuilt on a foundation that ensuresethical and responsible outcomes.be geared around solving ahuman problem and factor in theright combination of machinesand human talent – from development and deployment,through usage. Enact an effective governancestructure: Businesses needto engage teams in definingstandards, best practices andinvestment strategies to getthe most value from AI. Thegovernance model shouldensure that AI-led decisions arereached in a transparent andauditable way while obviating theinfluence of biases (unintendedor otherwise) that may creep intothe fabric of AI designs. Build an ethical foundation– and continually maintain it:For AI to take hold, businessesneed to embed processesthat ensure integration ofethical considerations into thedevelopment, deployment andongoing usage of AI, both insidethe organization’s four walls andwith customers and partners.The road ahead:strategy, governanceand ethics imperativesTo successfully move from thenascent stages of AI into fullbusiness value realization, webelieve organizations shouldfocus on three key areas: AIstrategy, governance and ethics.Addressing gaps in these areascan place AI on a sustainable pathto delivering desired results. Werecommend businesses take thefollowing actions when planningtheir path to AI: Embrace a human-centricstrategy: In addition to focusingon measurable business value,an effective AI strategy shouldThis article was adapted from our primary research-based report “MakingAI Responsible – and Effective.” To learn more, visit adoption-for-business.Cognizanti 13

Endnotes12“Artificial Intelligence Market,” Markets and Markets, February 2018, rtificial-intelligence-market-74851580.html.Alex Knapp, “Gartner Estimates AI Business Value to Reach Nearly 4 Trillion by 2022,” Forbes, April25, 2018, -4-trillion-by-2022/#47bf0f433f9b.AuthorRajeshwer Chigullapalli is an Associate Director within Cognizant’s thoughtleadership program. He has over 25 years of experience in the areas ofbusiness research and publishing. Previously, he was the Head of ICFAIUniversity Press and Chief Editor, SPG Media, India. He can be reached mentsThe author would like to thank Cognizant Digital Business’s AI and Analytics Practice for theircontributions to this article, including Poornima Ramaswamy, Vice President, James Jeude,Vice President and Practice Leader, and Bret Greenstein, Global Vice President and Head ofthe AI Practice.14

Scan the above image to hearabout MetLife’s use of blockchainas told by Zia Zaman.See inside cover for instructions to downloadthe Cognizant AR app.

Health InsuranceFrom Vision to RealityHow MetLife AppliedBlockchain to Solve aDifficult Health InsuranceChallengeBy Zia ZamanWorking with well-placed partners, the global insurerlaunched the world’s first automated insurance solutionfor gestational diabetes in Singapore, taking enterpriseblockchain technology from the highly aspirational tothe incredibly practical and meaningful. Along the way,it uncovered the potential, and limitations, of distributedledger technology’s uplifting impact on both underservedcommunities and society as a whole.In September 2016, a colleague inour innovation center LumenLabwalked into my office with abold idea. At LumenLab, we’reaccustomed to this; based inSingapore, we were establishedto build disruptive businesses forMetLife. “Lumen,” a measure oflight, symbolizes our commitmentto illuminating new paths forsolving problems faced by peoplein Asia today.Still, I underestimated just howpivotal this moment would be.He enthusiastically pitched anew insurance idea based on asmart contract (contracts thatverify and carry out credibletransactions without third parties),to which I responded, “Wouldn’tit be great if we could make aninsurance payout as effortless asgetting a soft drink from a vendingmachine?”This ambitious idea tookadvantage of the technologyunderlying Bitcoin: blockchain, ormore precisely, distributed ledgertechnology (DLT).Cognizanti 17

ValidatingopportunitiesBack then, Bitcoin had yet to reachits peak valuation, and while therewas a lot of talk about use casesin the enterprise, nobody, in anyindustry, had gone and done it.LumenLab thrives on challengeslike this.Over the course of our four-yearexistence, we’ve developed andrefined our own “test & learn”process for building new ventures(see Figure 1). We measuresuccess in terms of knowledgegained through small experiments,which can subsequently turninto commercial impact. Test &learn is an exceptionally fast andinexpensive way to challengeassumptions, eliminate risk andtransform uncertainty into valuableinsights – be it consumer painpoints (what we call “jobs-tobe-done”), product-market fit ortechnology readiness.The process runs in two stages:exploration and experimentation.During the exploration stage, weframe the problem and definewhat success looks like. We thenrefine the true job-to-be-done forthe customer and generate ideasfor how to build solutions. At theend of this stage, we have “fallenin love with the problem” and mayhave found new ways of solving it.The test & learn TATIONCREATE4BLUEPRINTFigure 118 Goals and bounds Context capturerINNOVATIONUnderstand our consumersand unlock great insights Into-the-wild interviews Persona builder Jobs-to-be-done finderCURIOSITYGenerate a range ofideas, and alignon the best Solution developerDevelop andrefine our solutionto setup for success Value propositionSet-up and run“pretotypes” totest and learnEXPERIMENT efficiently6BEHAVIORSDefine and align onscope and success5PILOTTOOLSLaunch our pilot tobuild and movetoward scale Ideation sprintEXPANSIVITY Rule breaker Competitor mapper What-if financialsEXPERIMENTALITY Assumption mapper Adaptive planning Experiment designer Minimum viable product Elevator pitchVELOCITYBRAVERY

During the experimentation stage,we formulate a value proposition,run small-scale experiments totest our assumptions, and iterateuntil we’re confident with buildinga pilot. The result is real-worldvalidation that can be used to buildcommercial products – without therisk and uncertainty that typicallyaccompanies new ventures.Using blockchain toserve the underservedWhen we set out to build theworld’s first blockchain-poweredhealth insurance application, weneeded to make sure it offeredreal benefits. Do the benefitsof blockchain line up with realcustomer needs? Is the technologyready for actual insurancecustomers? Can we align theright group of partners to build asystem on blockchain? These arejust some of the questions we hadwhen we started, and we wouldmethodically answer every one ofthem as we moved forward.Our first challenge was to find aproper product scope. We neededto cover a risk that was relativelylow in cost but still represented alatent coverage gap for customers.It needed to be a niche marketso we could keep it small enoughto experiment. And we neededa short claim period, with a highenough incidence rate to ensurewe could learn enough about theend-to-end customer experiencein a short time span. After muchdeliberation, a team member’spregnant wife suggested asolution: gestational diabetesmellitus, or simply GDM.GDM is a form of diabetes thatdevelops during pregnancy,occurring either when anexpectant mother can’t produceenough insulin, or the insulinis not working well enough toact on the sugars in her body.This leads to excess glucose inthe bloodstream, which can bepassed on to the baby. Associatedcomplications during pregnancyand labor include excess birthweight, premature birth and, insome serious cases, stillbirth.GDM affects one in five pregnantwomen in Singapore1 and, crucially,is typically not fully covered bygeneral health insurance. In otherGDM affects one in five pregnant women inSingapore and is typically not fully covered bygeneral health insurance. In other words, we’dfound a real, address able need that cut acrossthe population.Cognizanti 19

words, we’d found a real, addressable need that cut across thepopulation.Hence, Vitana was born. But wecouldn’t do it alone.Assembling the rightpartnersA key benefit of blockchain is thatit eliminates many of the processesthat add to the cost of insurancefor customers – including underwriting, onboarding and claimsprocessing. Our vision for Vitanawas to shortcut the process toprovide a frictionless experience forcustomers. We wanted customersto sign up in just a few minutes andour policies to be issued completelyhassle-free. To top it off, we wantedto completely eliminate the claimsprocess for customers afflicted withGDM. This meant payouts wouldautomatically appear in patients’bank accounts upon diagnosis –zero paperwork.To realize this vision, we had toconnect disparate data from manydifferent systems. We neededclinics to help us distribute Vitana,electronic medical records (EMR)providers to record customer data,and a technology provider withdeep expertise with DLT to help usimplement our ambitious plans.Because MetLife doesn’t havea traditional insurance businessin Singapore, we also partneredwith Swiss Re to reinsure therisk and offer valuable insight onproduct design and delivery in theSingapore market. Additionally, theMonetary Authority of Singapore(MAS) provided the regulatorysandbox that made the wholeexperiment possible.Our team of collaborators alsoconsisted of Singapore’s largestclinic group, Singapore MedicalGroup (SMG), EMR start-up VaultDragon, and business servicesprovider Cognizant. Together –over the course of six months – wedeveloped a customer journey,reengineered clinical processesand built the technology thatturned Vitana into reality.Our vision for Vitana was to shortcut theprocess to provide a frictionless experience forcustomers. We wanted customers to sign up injust a few minutes and our policies to be issuedcompletely hassle-free. To top it off, we wantedto completely eliminate the claims process forcustomers afflicted with GDM.20

The truly transformational moment happensat the “claim” stage. From a customer’sperspective, it’s all invisible and completelyfrictionless.Vitana in practiceVitana has two elements: amobile app for customers and ablockchain back-end to act asthe source of truth for all involvedparties. But for all the technologyinvolved in Vitana, our focus wason the customer journey.Early in her pregnancy, afterbeing informed about the risksof GDM and being told aboutthe innovative new coverage, theexpectant mother is encouragedto sign up by simply downloadingthe app and entering hergovernment-issued ID number.The app automatically connects tothe customer’s electronic medicalrecords and populates personalinformation. All that remains isfor the customer to answer threesimple underwriting questions andenter payment information. Thistakes about two minutes – and sheis instantly covered.A smart contract is automaticallycreated, encrypted and deployedto an Ethereum blockchain.This creates a policy document,which is emailed to the customervirtually simultaneously. All parties– clinics, insurers, reinsurers andregulators – now have visibility ofnew policies in real time. It doesn’tjust strengthen communications; iteliminates much of the transactioncosts for the parties interactingwith one another.The truly transformational momenthappens at the “claim” stage.From a customer’s perspective,it’s all invisible and completelyfrictionless. Around Week 25, theexpectant mother is tested forGDM by her clinic, which updatesher EMR with the results. Shouldthe customer test positive forGDM, the EMR automaticallywrites the result onto theblockchain. The smart contractthen executes, and a payout isautomatically triggered to thecustomer’s bank account.Again, all parties are instantlynotified, and the insurers – in thiscase, us – can process the “claim”and make the payment, withoutthe customer ever contactingMetLife.Cognizanti 21

Triggering the smart contractWhen downloaded, the Vitana app automatically connects to thepatient’s electronic medical record and deploys a smart contract to theblockchain. All parties now have visibility into new policies in real time.If the patient tests positive for GDM, the EMR auto matically writesthe result onto the blockchain, which executes the smart contract andtriggers the payout to her bank account.MOBILE APPBLOCKCHAININSURERELECTRONICHEALTH RECORDREGULATORREINSURERFigure 2Takeaways to dateVitana was designed as atime-bound experiment in thesandbox of MAS. As a progressiveregulator, MAS delivered onthe spirit of a public-private22partnership and was pivotal in thecocreation of this initiative. At thetime of writing, many conclusionsare still to be drawn; however, somelessons stand out already:

We found a real customer needin GDM, and blockchain helpedus put together a seamless,frictionless experience forcustomers afflicted by thecondition.Offering real value to expectantmothers in a time of need hasbeen a rewarding and gratifyingexperience. We are serving theunderserved;

in the U.S., Cognizant is ranked 193 on the Fortune 500 and is consistently listed among the most admired companies in the world. Learn how Cognizant helps clients lead with digital at www.cognizant.com or follow us @Cognizant. U.S. Headquarters: 211 Quality Circle. College Station