Where Silicon (Ai) needs Carbon (Hx)
How Human Experience increases the R.O.I. of AI, CRM, ERP, BI, ect.
AI and Business Automation

AI needs Human Intelligence (Hi): An example is AI Labeling. This is where humans assist AI Models by labeling, correcting & teaching AI models. Human general knowledge is critical in lowering AI hallucinations and improving accuracy.
Sales & Cust Support - CRM

Humans Open Up to Humans: Many data-points covering customer satisfaction, sales & marketing can be automatically captured then analyzed by business software systems. However, unstructured information including intel from customers, prospects, salespeople and partners still needs to be captured, reviewed then categorized by humans to ensure reporting accuracy. Much of this comes from dynamic conversations that are driven by human and general intelligence.
Accounting & Compliance

Managing Structured & Unstructured Data: Many contractual, financial, government and compliance interactions, especially those between vendors and customers require human follow-up/ engagement. Emails and automated signals are not always responded to within needed timeframes nor with needed details; and content is not always structured or easy to understand. Reviewing documents and the 'process to complete them', with customers can be invaluable to completing all objectives.
Analytics and System Outputs

GIGO can Cascade: The accuracy of information provided by a BI, Analytics or reporting system is critical. Some information can be captured electronically, and should be reviewed for anomalies. Some of it will need to be adjusted. Too many anomalies can begin to create major reporting problems and cascade.
Solid ERP & Core Business Data

Data flows across the enterprise: Data can be communicated between different companies' core business systems via the internet (ie ERP, SCM, HRIS, Records, Purchasing, Matter Mgnt ect). Humans are integral in ensuring data is correctly captured, especially when this data comes from other humans. If it is bad in 1 place, it is bad in many places.
Custom adds Complexity

Different Systems need Varying Data Types: Having custom software systems can add to the complexity of data automation and system connectivity. Human integration can be important to ensure multiple systems are updated correctly.
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