2026全球AI报告：AI领军者行动指南——从试点到盈利：将AI愿景转化为价值

Cover HeadingFrom pilots to profit: Turning AI vision into value Heading 2 Noto Sans Regular 20pt Contents 03Who is leading in AI? 07How AI leaders manage their organizations 24About the research 26Meet the AI mandate head-on Who is leading in AI? In the era of AI, the old dividing lines between business and technology strategies are vanishing.Today, AI strategy and business strategy are becoming one. An innovative technology that was once a supporting act for digital transformation has become the main event, withGenAI and agentic AI having a significant impact. Organizations’ operational and economic destinies now depend This playbook, the first in our2026 Global AI Reportseries, is based on extensive research among more than 2,500C-suite and other senior decision-makers across 15 industries and 35 countries in 5 regions. It covers developments Overall, the data shows that forward-thinking organizations are moving from early alignment — where AI wastreated as a complement to the business plan — to full fusion, where AIisthe business plan. To paint a clearer picture of this trend, we have classified respondent organizations asAI leadersif all of thefollowing are true, based on their survey responses: •Their AI strategy is well-defined or in progress.•Their level of AI maturity is “mature” or “evolved.”•They have realized significantly higher profits from AI than their peers. We also identified an opposite group, theAI laggards— organizations that have a poorly defined AI strategy(or none at all), rate their AI maturity as that of a “novice” or “explorer” (or have done no work in this regard) How we split the cohort From our2,567respondents, we identified: When we compare AI leaders in this playbook with all other organizations, “all other organizations”includes both the AI laggards and the unclassified organizations, a total of2,170 respondents (85%). Levels of AI maturity defined •No plans:Have not yet explored usage in our organization•Explorer:Strategies and plans under consideration, but no adoption or capability•Novice:Just starting; limited experience and/or use cases•Enabled:Use is sporadic and somewhat siloed; feasibility pilots and limitedadoption by individual business units in mostly noncore functions•Mature:Use is broad and strategic across business units and functions, with How AI leaders stand out Our data shows AI leaders are growth and margin outliers. They are nearly2.5 times more likelythan all other organizations to postrevenue growth of more than 10% and3.6 times more likelyto run at And while some of these leaders are very large organizations, as definedbelow, they are found in every revenue range in our research. In short, these AI leaders: •Outgrow the pack: 62.8%posted revenue growth of more than 10%in the last fiscal year, compared with25.3%of all other organizations. •Often have large-scale operations: 23.9%have more than 50,000employees, compared with just15.5%of all others. •Run at higher margins: 33.8%operate at margins of15%or more,compared with9.4%of all other organizations. AI leaders are found across all 15 industries, but our data shows theyappear slightly more often in insurance (11.6%versus11.3%of allother organizations), consumer packaged goods (9.6%versus6.8%),technology, media and telecommunications (7.8%versus4%), Conversely, there are fewer in banking and investment (10.1%versus11.8%of all others), the automotive industry (7.6%versus11.7%), and inenergy and utilities (1.8%versus4.7%). 9 key characteristics of AI leaders In this playbook, we present the following nine key characteristics of AI leaders in more detail to illustrate how theyoperate and why they are already seeing the benefits of their investment in AI. Strategy: Leaders treat AI as a core growthengine and rewire their strategies accordingly. Execution: AI leaders differentiate throughresilient foundations, empowered humans, Strategic alignment and speed Secure at scale AI leaders win by tightly aligning AI with businessstrategy and turning strategic focus and speed AI leaders build scalable and secure stacks,localize or relocate AI infrastructure forprivate/sovereign AI and invest to eliminate Focused end-to-end approach Expert-first AI Top performers focus on high-value domainsthat unlock disproportionate economic These front-runners use AI to amplify the impactof experienced, highly skilled employees rather Change that sticks Flywheel effect These front-runners create a cycle where initialinvestments fuel early success that drives Top performers treat adoption as acompany-wide change program and adopt Core reinvention Governed for scale Leading organizations centralize AI governance,formalize enterprise-wide oversight, andempower dedicated Chief AI Officers (CAIOs) Growth leaders rebuild core applications withembedded AI rather than limiting themselves Partner-powered growth Best-in-class players lean on strategic externalcollaborators and are open to