DataArt：2026年数据与人工智能（AI）趋势报告（英文版）（21页）.pdf

1、2026 TRENDS REPORT:DATA&AI12026 Trends Report:Data&AI2026 TRENDS REPORT:DATA&AI2Report OverviewIntroduction:The(Great)DisconnectThe widening gap between AI ambitions and operational reality across industriesTop Data&AI Trends for 2026AI success in 2026 will be driven by data infrastructure,not new m

2、odelsWhy modern data infrastructure,not the latest AI model,delivers the highest ROI for enterprisesOrganizations are moving from broad experimentation to specific,high-value use casesThe shift from hype to focus:proven,measurable applications replacing unfocused experimentationAI is evolving from p

3、roof-of-concept to enterprise-wide deploymentAI moves from testing and pilots to strategic,production-ready adoption across industriesCompanies are rethinking short-term,tech-first AI strategies that fail to scaleHow organizations are learning from early mistakesSemantic modeling,conversational inte

4、lligence,and governance are becoming critical differentiatorsThe hidden enablers defining scalability,trust,and responsible AI adoptionEnterprises are prioritizing data lifecycle management,modernization,and human capabilityStrategic priorities shaping the next 18 months of AI-driven transformationH

5、igh-performing companies are aligning data,people,and purpose to scale AI responsiblyWhat successful organizations understand about themselves,their data,and their peopleIndustry-Specific Trends for 2026Sector forecasts for airlines,retail,media,healthcare,and technology,and how AI is reshaping oper

6、ations,innovation,and talentHow to Prepare for 2026 Key actions to build readiness and avoid common pitfallsConclusion:The Base Determines the FutureThe three paths ahead and why strong foundations decide which one you take1.2.3.4.5.6.7.2026 TRENDS REPORT:DATA&AI32026 Trends Report:Data&AIExpert ins