How to Implement AI in Management: The 1st Step is Data Centralization
Every Chief Operating Officer (COO) wants to implement AI to scale. The problem is trying to plug AI into a company running on loose Excel spreadsheets and WhatsApp groups. AI is a powerful engine, but its fuel is your data. If data is fragmented or dirty, AI generates useless (or dangerous) results.
The Prerequisite of Intelligence
Before automating decisions, you need a Single Source of Truth (SSOT). AI needs to know exactly where the true client contract is stored.
The AI Hub in Jestor
This is where Jestor acts as the perfect foundation:
- Structured Data: By migrating from spreadsheets to Jestor's database, you create a clean relational mesh. AI can read that "Invoice X" belongs to "Project Y."
- Native AI (Built-in): You don't need to hire complex external tools. Jestor already has AI blocks that query your data directly within the workflow.
- Information Security: Feeding public AI models with client data is a GDPR risk. Jestor processes AI in a secure, closed cloud environment (Enterprise).
Frequently Asked Questions (FAQ)
Do I need data scientists? For most Backoffice use cases (summarization, extraction, classification), Jestor's No-Code model lets any manager implement AI. Meet Jestor.
Which process to migrate first? Start by centralizing the client registry and financial control.
Does AI clean old data? Yes, it can be used in sanitization routines to standardize names and remove duplicates from your legacy data.
Conclusion
With Jestor, it is possible to automate workflows, connect departments, and create internal systems your way, all code-free and AI-supported.
Discover Jestor and learn how to take your company's management to a new level of efficiency and integration.