How SMEs Can Use AI for Stock Control and Inventory Management

1. Stock control is a common headache for SMEs

Many SMEs struggle with inventory because:

• stock records are inaccurate,
• staff forget to update systems,
• there’s no clear reorder process,
• old stock sits unused,
• deliveries arrive incomplete,
• demand fluctuates unpredictably,
• multiple sites or vans hold stock.

AI can reduce these problems by improving accuracy, forecasting demand and automating routine stock tasks.

2. What AI can help with in stock management

AI can support SMEs by:

• forecasting stock levels,
• predicting demand,
• preventing overstock and shortages,
• detecting anomalies,
• tracking usage patterns,
• automating purchase suggestions,
• identifying dead stock,
• verifying delivery notes or photos.

3. Use case #1 — Forecasting demand more accurately

AI can analyse:

• past job history,
• seasonal patterns,
• customer behaviour,
• supplier lead times,
• industry trends.

This helps SMEs know what stock will be needed, when, and in what quantity.

4. Use case #2 — Automatic reorder suggestions

AI can monitor stock levels and suggest when to reorder based on:

• current usage rates,
• upcoming jobs,
• delivery lead times,
• minimum stock levels,
• supplier reliability.

Some systems can even auto-generate a draft purchase order.

5. Use case #3 — Identify slow-moving or dead stock

AI can analyse sales and usage patterns to highlight:

• stock not used for months,
• stock costing storage space,
• duplicate or obsolete items.

This helps SMEs free up capital and reduce waste.

6. Use case #4 — Spot anomalies or errors in stock records

AI can detect when quantities seem suspicious, such as:

• recorded usage higher than expected,
• missing items,
• incorrect quantities on delivery notes,
• patterns suggesting theft or shrinkage.

It alerts staff before discrepancies become serious problems.

7. Use case #5 — Analyse supplier performance

AI can evaluate:

• delivery times,
• pricing consistency,
• quality issues,
• order accuracy.

This allows SMEs to choose better suppliers and negotiate more effectively.

8. Use case #6 — Read delivery notes and invoices automatically

AI can extract structured data from:

• photos of delivery notes,
• PDF invoices,
• scanned documents,
• handwritten notes.

This ensures stock systems remain accurate even when paperwork varies.

9. Use case #7 — Assist with stocktakes

AI can help by:

• highlighting likely discrepancies,
• predicting where errors are most common,
• pre-populating expected quantities,
• analysing variance data after checks.

This reduces the time needed for full or partial stocktakes.

10. Use case #8 — Manage multi-location stock more effectively

AI can track usage patterns across vans, warehouses, containers or satellite offices and suggest:

• internal transfers,
• balancing stock between sites,
• optimising storage costs.

11. Use case #9 — Link stock usage to job notes or photos

AI can read engineer notes or site photos to extract which items were used on a job.

For example:

• scaffold fittings,
• HVAC components,
• electrical consumables,
• plumbing parts.

This eliminates manual effort and improves billing accuracy.

12. Use case #10 — Predict future storage needs

AI can forecast how much storage space will be required based on upcoming contracts, seasonal cycles and long-term demand trends.

13. Best practice: start with data you already have

Even partial stock usage or job data is enough for AI to begin producing useful insights.

14. Best practice: keep humans in charge of approval

AI can suggest reorder quantities, but staff should confirm before placing any orders.

15. Best practice: integrate stock with job management

AI becomes even more powerful when job systems, stock systems and scheduling tools talk to each other.

16. The bottom line

AI makes stock control far easier for SMEs by forecasting demand, improving accuracy and reducing administrative workload.

Whether you manage tools, materials, spare parts, consumables or hire stock, AI can help reduce waste, prevent shortages and improve operational efficiency.

In the next guide, we’ll explore how SMEs can use AI to reduce costs and identify savings across the business.