2025年AI准备度基准调查报告

Core Insights - The report highlights a significant gap between enthusiasm for AI and its practical implementation, with businesses struggling to translate potential into tangible results [12][40] - Generative AI is rapidly being integrated into daily workflows, with 59% of employees using it regularly, but the impact on productivity is still being evaluated [30][36] - The role of IT departments remains crucial in AI implementations, although business units are increasingly taking the lead in promoting AI initiatives [13][49] AI Adoption and Integration - 59% of employees incorporate generative AI tools into their daily work, indicating a strong adoption rate [30] - However, only 36% of respondents report a significant increase in productivity, while 46% remain undecided about its effects [36] - 73% of organizations report moderate to low integration of AI into existing IT systems, with only 8% achieving seamless integration [25][24] Key Challenges - The main barriers to effective AI implementation include a lack of clear business use cases (37%) and difficulties in measuring AI's impact (24%) [18][41] - There is a notable skills gap, with 32% of companies lacking business understanding and domain expertise related to AI applications [2][14] - Infrastructure issues persist, with less than half of the organizations effectively utilizing data to support AI applications [2][14] Trust and Perception - Trust in AI tools is relatively high, with 62.63% of respondents rating their trust at 4 or 5 on a scale of 1 to 5 [45] - Despite this, 28% of respondents remain neutral, indicating a need for greater transparency and confidence-building measures [45] Future Directions - Successful AI implementation will require a focus on defining business-oriented use cases, developing a robust value measurement system, and enhancing data management and application modernization [3][40] - Bridging the skills gap through training in both technical and business domains is essential for maximizing AI's potential [3][14]