|
|
|
You can get e-magazine links on WhatsApp. Click here
|
|
|
|
|
|
AI, integrated technology reshape restaurant operations
|
|
Tuesday, 25 August, 2026, 08 : 00 AM [IST]
|
|
Anurag More, Mumbai
|
Artificial intelligence (AI) and integrated technology platforms are increasingly transforming the way restaurants manage costs, inventory, menu pricing and day-to-day operations, according to Shivprakash S. Mogali, Founder of Digitory.
Mogali said restaurants have traditionally calculated their actual costs only at the end of the month, often after the expenditure had already taken place. Connected technology platforms can change this by bringing billing, inventory and recipe data together, allowing operators to assess the actual cost of a dish in real time.
“AI does not create margin on its own. It surfaces margin that was always hidden in daily operations,” Mogali said, adding that the effectiveness of AI depends heavily on clean data and properly integrated systems.
Technology can also help restaurants identify food wastage and improve inventory management by tracking ingredient consumption against actual sales. When every dish sold automatically deducts the corresponding ingredients from inventory, restaurant operators can compare expected stock levels with actual stock, helping identify potential wastage, pilferage and other discrepancies.
Integrated systems can also flag slow-moving inventory and shelf-life risks before they translate into losses. However, Mogali cautioned that the underlying inventory configuration, recipe links and yield calculations must be accurate for such systems to function effectively.
AI is also making recipe costing and menu pricing more dynamic, particularly as ingredient and supplier prices fluctuate. Rather than relying on periodically updated spreadsheets, AI-enabled systems can continuously recalculate recipe costs as input prices change and provide alerts when margins begin to erode.
This can help restaurant operators identify menu items that may be generating lower margins and make more informed decisions on pricing and promotions. However, accurate recipes and yield data remain essential for reliable cost calculations.
In day-to-day operations, technology can reduce the manual and repetitive tasks that consume a significant portion of restaurant managers' time. Orders flowing directly from the point of sale to kitchen display systems can reduce errors, while automated inventory updates can minimise the need for manual stock reconciliation.
“When the front of house and the back office run on the same data, staff can spend less time reconciling numbers between systems and more time focusing on guests,” Mogali said.
For restaurant chains, integrated technology platforms can help maintain operational consistency across multiple locations while accounting for regional differences in procurement and operating costs. While recipes can remain standardised across outlets, the cost of preparing the same dish may differ depending on local suppliers, procurement conditions and rental expenses, particularly in premium locations.
A connected platform can provide the head office with a clearer view of outlet-level performance and help identify deviations in costs, recipes or profitability before they become larger operational issues.
Technology is also playing an increasingly important role in improving customer experience and personalisation. Beyond QR-based ordering, faster billing and shorter waiting times, restaurants can use ordering and feedback data to better understand customer preferences and engagement.
Data on frequently ordered dishes, visit patterns and customer feedback can help restaurants deliver more relevant experiences and strengthen loyalty without relying on generic personalisation strategies, Mogali said.
Looking ahead, Mogali expects India's restaurant and food and beverage industry to move away from disconnected technology tools towards more integrated platforms that bring operational and financial data together.
AI is expected to increasingly move beyond reporting past performance and act as a decision-support tool for restaurant owners and managers, supporting areas such as demand forecasting, purchasing, menu engineering, margin monitoring and data quality management.
“The restaurants that succeed will be the ones that get the basics connected first,” Mogali said, stressing that reliable data and integrated systems will remain the foundation for effective AI adoption.
|
|
|
|
|
|
|
|
|
|