{"title":"The AI transformation of product innovation","authors":"Robert G. Cooper","doi":"10.1016/j.indmarman.2024.03.008","DOIUrl":null,"url":null,"abstract":"<div><p>Artificial Intelligence (AI) is revolutionizing every facet of the business landscape. Early adopter firms have implemented AI for various reasons, but the number one benefit realized is increased innovation (<span>Jyoti & Riley, 2022</span>). Early adopters of AI for new product development (NPD) not only demonstrate that AI finds many applications in NPD, but also offers substantial payoffs. This AI revolution is coming fast, estimated to have a 13–15 year window of adoption, peaking before the end of this decade.</p><p>This article focuses on AI applications in three target areas in the new product process, where the need for better solutions is high, and the applications for AI show significant benefits. They are: 1) idea generation and concept creation and testing; 2) building a robust business case leading to better “go-to-development” investment decisions; and 3) the design, engineering, development, and testing of the product. AI applications in each of these three target areas are described briefly, along with some in-depth case illustrations of AI at work in NPD, and the benefits achieved by leading firms. These benefits include a remarkable reduction in development and testing times; optimally designed products; better and more appealing new product ideas and concepts; and more effective and productive voice-of-customer studies.</p><p>Despite the reported benefits of AI in NPD, the adoption rate is quite low, about 13% across firms globally (<span>McKinsey, 2023</span>); thus, AI for NPD was in the “early adopter” stage of the Rogers diffusion of innovation curve by early 2023. Impediments to adoption are outlined, based on numerous studies: the lack of a strong business case; high perceived costs of adoption; the lack of corporate readiness and the right mindset; and risks and ethical issues.</p><p>High uncertainties remain regarding the adoption of AI in NPD, and many unknowns still exist; thus, numerous opportunities for academic research are identified in the form of research questions begging to be answered. The article ends with a call to action, aimed at both practitioners and academics: AI is the most significant innovation in our lifetime! It's time we all got on board.</p></div>","PeriodicalId":51345,"journal":{"name":"Industrial Marketing Management","volume":"119 ","pages":"Pages 62-74"},"PeriodicalIF":7.8000,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Industrial Marketing Management","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0019850124000464","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial Intelligence (AI) is revolutionizing every facet of the business landscape. Early adopter firms have implemented AI for various reasons, but the number one benefit realized is increased innovation (Jyoti & Riley, 2022). Early adopters of AI for new product development (NPD) not only demonstrate that AI finds many applications in NPD, but also offers substantial payoffs. This AI revolution is coming fast, estimated to have a 13–15 year window of adoption, peaking before the end of this decade.
This article focuses on AI applications in three target areas in the new product process, where the need for better solutions is high, and the applications for AI show significant benefits. They are: 1) idea generation and concept creation and testing; 2) building a robust business case leading to better “go-to-development” investment decisions; and 3) the design, engineering, development, and testing of the product. AI applications in each of these three target areas are described briefly, along with some in-depth case illustrations of AI at work in NPD, and the benefits achieved by leading firms. These benefits include a remarkable reduction in development and testing times; optimally designed products; better and more appealing new product ideas and concepts; and more effective and productive voice-of-customer studies.
Despite the reported benefits of AI in NPD, the adoption rate is quite low, about 13% across firms globally (McKinsey, 2023); thus, AI for NPD was in the “early adopter” stage of the Rogers diffusion of innovation curve by early 2023. Impediments to adoption are outlined, based on numerous studies: the lack of a strong business case; high perceived costs of adoption; the lack of corporate readiness and the right mindset; and risks and ethical issues.
High uncertainties remain regarding the adoption of AI in NPD, and many unknowns still exist; thus, numerous opportunities for academic research are identified in the form of research questions begging to be answered. The article ends with a call to action, aimed at both practitioners and academics: AI is the most significant innovation in our lifetime! It's time we all got on board.
期刊介绍:
Industrial Marketing Management delivers theoretical, empirical, and case-based research tailored to the requirements of marketing scholars and practitioners engaged in industrial and business-to-business markets. With an editorial review board comprising prominent international scholars and practitioners, the journal ensures a harmonious blend of theory and practical applications in all articles. Scholars from North America, Europe, Australia/New Zealand, Asia, and various global regions contribute the latest findings to enhance the effectiveness and efficiency of industrial markets. This holistic approach keeps readers informed with the most timely data and contemporary insights essential for informed marketing decisions and strategies in global industrial and business-to-business markets.