1、Executive findings to inform strategy,governance,and AI investmentsGENERATIVE AI FOR A COMPETITIVE PRODUCT STRATEGYThis ebook examines how Generative AI has shifted the focus of business executives such as Chief Data Officers(CDOs)and Chief Data Analytics Officers(CDAOS),balancing opportunistic use

2、cases for building an AI-fueled competitive advantage with the challenges faced in responsibly operating and scaling AI.It combines findings from the Capgemini Research Institute with recent independent Domino Data Lab reports to evaluate how Generative AI has renewed the focus on building and opera

3、ting AI at scale.While expectations(especially from Generative AI)are high,particularly for product and service development,concerns over governance,security and responsible AI has most organizations fine-tuning open-source/commercial Generative AI models,with strategies looking towards fully in-hou

4、se large language models(LLMs).There are promising applications of Generative AI for product design and customer experience,in-house AI development brings massive challenges.Investment commitments fall short-particularly in the resources enterprise analytics leaders need to deliver on the promise of

5、 fine-tuned or in-house developed Generative AI models.Underinvestment in people,process,and technology is all-too-common.Data scientists therefore lack the data,toolsets and infrastructure necessary for them to do their job.This results in major talent retention and hiring challenges.More important

6、ly,the lack of access to proper tool sets increases the risk and exposure to governance and responsible AI issues.In conclusion,we suggest that organizations which lack urgency and commitment to effective people,processes,and supporting tools-like AI CoEs and AI platforms supporting hybrid-and multi