跟上人工智能的发展

artificialintelligenceis a co-pilot and fundamentally an inventionthat can help us do research, learn more,communicate more, sift through data better.“We are entering a profound age of age of AI. AI brings hugeopportunities for economies of the future, for the future ofwork, and for the future of workers. The ways AI is able to be sointelligent is through pattern recognition and correlation. Thisis due to the huge amount data or digital footprints that we areconstantly releasing, particularly by our phones, but also whenwe use our credit cards.We have a huge opportunity with AI and machine learningsystems to hire people, and create a robust and progressivefuture-centered digital economy. We need to expand our digitalliteracy and arm people for the jobs of the future, so they canwork with technologists and engineers to represent our values,our corporate values, our business values and our ethical values.”Ramesh Srinivasan,UCLA ProfessorReinventing technology for the global societyRamesh Srinivasanis a professor in the UCLA Department of Information Studies anddirector of UC Digital Cultures Lab, and a leading voice on the intersection of technology,innovation, politics, business, and society. In his talk on Reinventing technology for theglobal society, Ramesh discusses how technology shifts such as algorithms, AI, automation,machine bias, data sets and cryptocurrencies are having the greatest impact on businesses,the economy, labor, medical care and more.https://www.rameshsrinivasan.org/LinkedIn: https://www.linkedin.com/in/ramesh-srinivasan-1081261a/ © Oliver WymanGenerative artificial intelligence (AI) has arrived in force and has the potentialto transform many ways insurers do business. Poster child of “The Age ofAcceleration,” it has gained daily media coverage, and its possibilities havecaptivated headlines.Earlier this year, we explored the fundamentals of generative AI and the impactit may have in the insurance industry, as we saw many insurers experimentingwith its potential. We are now seeing industry discussions progressively shiftingaway from “What is generative AI?” to “What can I do with generative AI that isimpactful, and how soon can this impact be delivered?”. In this article series, wewill explore the world of generative AI through the lens of insurance industryleaders, addressing practical questions with the goal of helping the industrymove forward — thoughtfully — on the impact curve.Our initial edition discusses, “The Generative AI Opportunity” for insurers, howsignificant generative AI will be for insurance organizations’ business strategiesand ways-of-working, and how quickly the impact is likely tomaterialize.the futureis nowIn this article, we cover the following questions:1.Is Generative AI anydifferentfrom previous disruptive technologies?2.Why should I worry about itnow?3.How should I think aboutopportunitiesfor my business?4.Howquicklywill these different opportunities come tolife? IS GENERATIVE AI ANYDIFFERENT FROM PREVIOUSDISRUPTIVE TECHNOLOGIES?The opportunityis massive,but with many“unknown unknowns”The ecosystemis nascent,even within big techSignal vs. noiseis a greaterproblemthan usual“Buildingthe machine”at scalewill take timeBETAThe opportunity is massive,but with many “unknown unknowns”A recent Celent survey found that by the end of 2023, half of insurers will havetested generative AI solutions, with more than 25% of insurers planning to havesolutions in production by year-end. These numbers are significantly higherfor larger insurance companies, and are likely to keep increasing as enterprisegenerative AI solutions and platforms proliferate and become more accessible.However, the speed at which the technology is evolving requires leaders andteams to “learn as they go,” both around “What to do” and “How to implementthe models, tools, and solutions.” While the short-term benefits are still unclear,we believe it is important for insurers to continue experimenting, exploring, andscaling the potential of certain solutions in order to stay ahead of the curve, andgain a first-moveradvantage.Unlike prior disruptive technologies — such as the internet, mobile, cloud, lowcode and no code, or even blockchain — whose mere early adoption took yearsto materialize, generative AI fostered large scale experimentation practicallyovernight. This was driven by a combination of ease of access to consumersolutions (such as OpenAI’s ChatGPT or Google’s Bard), worldwide mediacoverage, and the promise of near-instant benefits (howeverreal). Exhibit 1: Many insurers are testing generative AI solutions, and 25% plan tohave solutions in production by the close of 2023% of OW/Celent survey respondents, all sizes/> $5 billion gross written premium(GWP)US insurers developing Generative AIsolutions in atestenvironmentUS insurers developing Generative AIsolutions in aproductionenvironmentAll sizes>$5 BN GWPAll sizes>$5 BN GWPYesNo, but planto end of yearNo29%50%21%57%14%29%17%74%9%29%57%14%Source: Ol