2025 AI脉搏调查报告：从探索迈向转型（第一卷）

What AI Success Looks Like Table of contents Executive summary03 Perceived benefits of AI: What success looks like Want to build momentum with AI? Think big, act fast —Bryan Throckmorton AI adoption and investment satisfaction06 11 Executive summary with maturity, investment goals, technology shifts, andmastery of integration and data challenges. In researchingAI adoption patterns, investment expectations andoptimisation challenges, Protiviti’s inaugural AI PulseSurvey presents a snapshot of this evolving process at apivotal moment in the AI revolution.Among many findings, our global survey reveals that most persistence as challenges with system integration, use casesand data access are prominent throughout the AI journey,especially in the early and late stages.The survey findings raise important questions: Is focusing exceeds expectations. Nearly half of our survey participantsare seeing value from AI and more than a quarter areexperiencing better-than-expected outcomes.As AI maturity levels increase, so does ROI satisfaction. At the most-mature stage of AI adoption, 95% of respondentsexpress high satisfaction with their AI investments,underscoring a strong correlation between maturity levelsand achieving or surpassing projected ROI.Perception of AI success also evolves with maturity.Companies in the early stages focus more on cost savingssolely on cost-cutting setting up early-stage organisationsfor underwhelming results? How can organisationstransition from short-term gains to sustainable AI-drivengrowth? How do you measure ROI if your goal is to buildlong-term innovation?Our experts offer critical insights into these questions, including actions companies can take now. Business organisations are actively testing AI or in the early stages ofadoption. This trend is consistent across surveyed regions,sectors and job functions.Just8% of the organisations surveyed place themselves at thehighest maturity level, a stage in the AI journey where the as a primary goal or ROI indicator, while organisations withmore AI maturity recognise the importance of investingin capabilities that drive long-term growth and resilience.Among roles, the C-suite is notably more optimisticabout AI driving the most benefits likely due to their broadpurview and ability to recognise benefits across operations.leaders should focus on developing a realistic view of AI’spotential and align AI with organisational strategy, cultureand business goals. And, as the results show, there’s a hugeopportunity to maximise the value of organisational dataand enhance data infrastructure to support AI use cases. technology fuels innovation and competitive advantage.Return on AI investment follows a nonlinear trajectory,gaining momentum as adoption and integration improve and initial hurdles are addressed. Overall, 85% of respondents 19% 32% 21% 20% 8% potential benefits but haslimited understanding andno strategic initiatives. Keyperformance indicators (KPIs)have not yet been defined. AI systems for performanceand scalability, with continuousimprovements based ondata feedback.transformation at theorganisation, creating newopportunities and reshapingthe industry landscape. AI solutions into existingbusiness processes, enhancingoperational efficiency anddecision-making. small-scale AI projects andpilot programs to assessfeasibility and benefits. 01Notable findings 02Overall, 85% of organisations indicate that their investment As organisations advance through the stages of maturity, Most organisations surveyed are in the early to middle stages of AI satisfaction with AI investment returns improves significantly.•At Stage 1, about one-third of organisations report returns•At stages 2 and 3, we begin to see a shift toward meetingin AI has met or exceeded their expectations. Only 15% oforganisations, however, state that returns have been belowexpectations. adoption, with nearly 51% reporting that they are just beginning toexplore AI or experimenting with AI through pilot projects.•The technology sector is significantly ahead in AI maturity; below expectations.expectations and slightly exceeding them.•At the most-mature stage, the number of organisationsreporting that returns have exceeded expectations surgesto nearly 75%. over 70% are in stages 3 or 4.•Among the sectors represented, a notably large number (37%)of manufacturing organisations are in the experimentationstage, a sign that companies are actively testing use cases likepredictive maintenance, quality control and robotics.04 05Across functions, IT consistently leads in AI use cases, withparticularly high adoption in the technology sector (82%). Regarding the perceived benefits of AI, employee productivity,cost savings and process efficiency remain top indicators across Integrating AI technology into existing systems is the biggestsingle challenge (30%). Lack of understanding and data all stages of maturity.•For early-stage companies (1–2), the focus is on cost s