Establish momentum: The path to confident AI adoption

Our latest research highlights strong leadership commitment to generative AI but reveals gapsin business readiness. By addressing weaknesses and capitalizing on strengths, businesses can In this report 11Closing the businessreadiness gap#1: Strong leadership commitment highlightsAI’s strategic importance#2: Strategies emphasize productivity over cost cutting#3: Organizational agility remains a major challenge 17Strategic actions fornavigating gen AI adoption 2024 was the year generative AI moved frombuzzword to business imperative—with largeorganizations worldwide spending an average of $47.5 million average per-company expendituresthis year on gen AI This substantial commitment underscores its perceivedimportance. Nearly three-quarters of respondents in our studysay it’s vital to their continued success, which has spurred a say gen AI is vitalto their continuedsuccess While recent headlines have fueled fears of AI-related job loss, our research tells adifferent story. Rather than cutting headcount, companies are redirecting productivitygains from gen AI into funding business growth. This shift highlights a broader trend:Organizations aren’t just looking to do more with less—they’re aiming to do more with The path to widespread adoption, however, is not without obstacles. Our study identifiedseveral factors that will either accelerate or inhibit generative AI momentum at aglobal and regional level. Knowing which levers to pull—and how these differ in various are fearful they’renot moving fast For instance, although respondents voiced strong leadership commitment and businessstrategies, a critical gap remains: Many senior executives express doubts about thereadiness of their technology infrastructures, talent/skills and organizational agility. This To obtain a comprehensive view of generative AIadoption around the world, we surveyed 2,200 businessexecutives across 23 countries and 15 industries about In this report, we’ll look at: The global factors that will inhibit oraccelerate generative AI adoption1. Building on our previous “New work, new world” research,which highlighted the potential economic gains andchallenges of generative AI in the US, this study delvesdeeper into global adoption trends, including investment The regional and country differences in2. By understanding these factors,businesses can identify whereto focus their efforts and how How respondents rate themselves infive areas of business readiness for3. Key takeaways for moving forward4. Generative AI adoptionis driven by manyfactors, both globallyand regionally, that willslow down or speed up 18 factors impacting gen AI momentum Operating model flexibilityMarket demand for gen AI-enabled products and servicesData readinessQuality of output from gen AI In our study, we asked respondents to rate 18 factors thatwe believe will have the greatest impact on generativeAI momentum on a scale of positive to negative impact Based on these ratings, we assigned each of the factorsa score, calculating for both respondents’ perceptionof its impact (accelerator, neutral, inhibitor) and theintensity level (high, medium and low). Here’s what we Catalysts for change: In effect, businesses recognize they have huge amounts of valuable data but areunsure of their technological capabilities to enable generative AI to use it. Leadersare more likely to rate the quality and cleanliness of their data as either good orexcellent (53% of respondents sit in this category). However, only 18% of respondents Topping the list of accelerators isflexible operating models.Business leaders expressed confidence in their overall ability to This adaptability can be seen in the rapid rollout of pilots, proofsof concept and, in some cases, full deployment of generative AIacross a wide range of use cases. Already, 96% of respondentssay they are making progress on using the technology to add a The second driver ismarket demand. Respondents recognize thatit’s become essential to embed generative AI into their operationsor product and service offerings, if they want to meet customerexpectations. In our “New work, new world” study, we found the USeconomy alone will see $1 trillion in annual productivity growth by2032 through the use of generative AI, and businesses clearly don’t Respondents are also optimistic about thereadiness of their data as a critical accelerator, with businesses confident in their abilityto harness data for AI applications. This enthusiasm may, however,be dampened by concerns about technology infrastructure, with ascant 9% citing this as a gen AI accelerator, as the quality of data Base: 2,200 global business leadersSource: Cognizant and Oxford EconomicsFigure 1 Barriers to progress: Factorsslowing AI momentum On the flip side, the most pressing inhibitor is theavailability and cost oftalent, which is set to bog down adoption efforts. In our study, no regionis exempt from the shortage of skilled workers, whether in AI or othernee