1、1A I R E A D I N E S S R E P O R T 2 0 2 4ii01AI Year in ReviewApply AIBuild AI Evaluate AI ConclusionMethodology41326384849IntroductionThe hype for generative AI has reached its peak.Developers continue to push the limits,exploring new frontiers with increasingly sophisticated models.At the same ti

2、me,without a standardized blueprint,enterprises and governments are grappling with the risks vs.rewards that come with adopting AI.Thats why in our third edition of Scale Zeitgeist:AI Readiness Report,we focused on what it takes to transition from merely adopting AI to actively optimizing and evalua

3、ting it.To understand the state of AI development and adoption today,we surveyed more than 1,800 ML practitioners and leaders directly involved in building or applying AI solutions and interviewed dozens more.In other words,we removed responses from business leaders or executives who are not equippe

4、d to know or understand the challenges of AI adoption first-hand.Our findings show that of the 60%of respon-dents who have not yet adopted AI,security concerns and lack of expertise were the top two reasons holding them back.This finding seems to validate the“AI safety”narrative that dominates today

5、s news.Among survey respondents who have adopted AI,many feel they lack the appro-priate benchmarks to effectively evaluate models.Specifically,48%of respondents referenced lacking security benchmarks,and 50%desired industry-specific benchmarks.Additionally,while 79%of respondents cited improving op

6、erational efficiency as the key reason for adopting AI,only half are measuring the business impact of their AI initiatives.And while performance and reliability(each at 69%)were indicated as the top reasons for evaluating models,safety ranked lower(55%),running counter to popular narratives.This rep