50 AI & Data use cases for mid-market companies
Quick answer
This page lists 50 AI and data use cases for mid-market teams, grouped by business domain, company size, and horizon. Use the filters to compare ROI and complexity, then pick the ideas that fit your context before we validate them together.
Filtered by business domain, company size, time horizon, and ROI. Find what applies to you.
Recommended use cases to start with
A short list of concrete cases to visualize impact and deliverables.
Sales & Commercial · 3-6 months
Predictive lead scoring: prioritize prospects who will close
Prioritize prospects based on their conversion probability using an ML model trained on CRM history.
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Sales & Commercial · 3-6 months
Sales forecasting
Predict future revenue by product/region/rep using statistical or ML models.
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Sales & Commercial · 3-6 months
B2B churn analysis
Identify customers at risk of churn using behavioral and transactional signals.
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Marketing · 1-3 months
AI-assisted content generation
Produce marketing content (articles, posts, emails) with AI assistance while respecting brand tone of voice.
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Operations & Supply Chain · 3-6 months
Demand forecasting
Forecast order volumes by product/SKU to optimize inventory and supply.
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Operations & Supply Chain · 3-6 months
Route optimization
Compute optimal delivery routes given multiple constraints.
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Visible results in under 3 months
Priority quick wins to trigger fast impact.
AI-assisted content generation
Produce marketing content (articles, posts, emails) with AI assistance while respecting brand tone of voice.
x3 content productivity gain
People analytics & HR dashboards
Analytical dashboards for HR KPIs (headcount, absenteeism, training, diversity, costs).
+20% HR KPI visibility
Ticket sentiment & categorization
Automatically classify support tickets by topic, urgency, and sentiment for better routing.
-30% response time reduction
Highest-impact use cases
Selected for ROI and business relevance.
Predictive lead scoring: prioritize prospects who will close
Prioritize prospects based on their conversion probability using an ML model trained on CRM history.
+30% conversion rate improvement
Sales forecasting
Predict future revenue by product/region/rep using statistical or ML models.
-30% forecast error reduction
B2B churn analysis
Identify customers at risk of churn using behavioral and transactional signals.
-15% churn reduction
AI-assisted content generation
Produce marketing content (articles, posts, emails) with AI assistance while respecting brand tone of voice.
x3 content productivity gain
Demand forecasting
Forecast order volumes by product/SKU to optimize inventory and supply.
-20% stockout reduction
Route optimization
Compute optimal delivery routes given multiple constraints.
-15% route cost reduction
Accounts payable automation
Automatically extract and validate supplier invoice data (OCR + AI) for straight-through processing.
-75% data entry time reduction
Automated financial reporting
Automatically generate consolidated financial reporting (P&L, balance sheet, cash flow) with AI commentary.
-80% close time reduction
Cash forecasting
Forecast short/medium-term cash flows using models integrating invoices, orders, and seasonality.
-30% forecast error reduction
Customer service chatbot
AI assistant to handle level-1 customer requests (FAQ, order tracking, basic support) 24/7.
40% L1 tickets automated
Dynamic pricing
Adjust prices in real time based on demand, competition, inventory, and elasticity.
+3% margin uplift
Enterprise knowledge management & RAG
Deploy an internal AI assistant that answers questions from enterprise documentation (procedures, wiki, technical docs).
+25% information productivity gain
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Predictive lead scoring: prioritize prospects who will close
Prioritize prospects based on their conversion probability using an ML model trained on CRM history.
+30% conversion rate improvement
B2B churn analysis
Identify customers at risk of churn using behavioral and transactional signals.
-15% churn reduction
Next Best Action: the right sales move at the right time
Recommend the optimal next action (call, email, meeting) for each account/opportunity.
+20% win rate improvement
Sales forecasting
Predict future revenue by product/region/rep using statistical or ML models.
-30% forecast error reduction
Buying signal detection
Capture external buying signals (hiring, funding, leadership changes) indicating purchase intent.
+20% qualified pipeline increase
Decision network mapping
Identify introduction paths and key decision makers via professional network analysis.
-20% sales cycle reduction
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