从捕获到智能:利用AI驱动的业务自动化转型工作流程.pdf

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从捕获到智能:利用AI驱动的业务自动化转型工作流程.pdf

1、Capture to IntelligenceTRANSFORMING WORKFLOWS WITH AI-DRIVEN BUSINESS AUTOMATIONYour hostAlex SollidaySr.Sales DirectorDocuWareAgenda Welcome&Introductions The Challenge:Data Overload AI,IDP,&DMS:Definitions and Evolution Solving Real-World Workflow Problems DocuWare IDP VS ChatGPT:Whats Right for Y

2、our Business?Building Your Automation Roadmap Q&AThe Data Challenge 78%of companies are operational with AI,but data volumes continue to rise exponentially.61%of document driven processes still use paper documents.48%expect paper volume to increase next yearPolls1.Do you use AI in the workplace?2.Ho

3、w would you describe your current use of AI in workplace tasks?The Process Challenge Common Pain Points Reviews&Approvals:Slow,error-prone,email driven,hard to track Compliance Requirements:Increasing complexity,risk of audit failures,new data protection policies Manual Data Entry:Time-consuming,ris

4、k of mistakes(becoming very common use of AI)Storing&Searching Information:Siloed,way too much of it,lots of time looking for answers,integration issues,no structureThe Data Challenge Hype vs.Impact AI tools are widely available,but meaningful results lag behind adoption.Productivity gap:Automation

5、alone doesnt solve outdated processes or resistance to change.66%*of new IDP projects are replacing legacy systems that cant keep up.AI-driven automation is inevitable,but without practical strategies for adoption and integration,the data challenge will only grow*Source:Deep Analysis and AIIM Market

6、 Momentum Index:IDP Survey“Its one thing to use AI;its another to make it impactful.”The Data ChallengeTop reasons for replacing legacy scanning systems:17%Unable to meet current needs 16%Require too much external help 13%Difficult to integrate with business processes 11%Data accuracy not good enoug

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