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Behind the Counter, Ahead of the Curve:   The Rise of AI-Driven Restaurant Operations 

The Future of Restaurant Operations Is Here; And It’s Smarter Than Ever 

In a world where razor-thin margins meet sky-high customer expectations, restaurants are under constant pressure to deliver more: more consistency, more speed, more sustainability with less: less waste, less downtime, and less manual errors. In this world, traditional operating models fall short and need re-invented. 

Welcome to the era of intelligent restaurants, where the use of Artificial Intelligence (AI) and the Internet of Things (IoT) or AIoT, is quietly transforming operations from being reactive to proactive. Sensors monitor equipment activity, algorithms predict failures, and dashboards offer real time insights — not just data. It’s not about automation alone; it’s about operational transformation. 

Forward-thinking operators are already reaping the benefits: lower utility bills, extended equipment lifespans, reduced food waste, better occupant comfort and kitchens that practically operate autonomously. Beyond these advantages, technologies are also helping restaurants meet rising expectations for good customer service, regulatory compliance, and corporate sustainability goals. 

This article breaks down how smart technologies are being applied across four critical areas of restaurant operations: energy management, equipment maintenance, production management, and food safety, and what that means for the kitchens of tomorrow. 

Energy Management: Precision for Every Kilowatt 

Restaurants are among the most energy-intensive commercial spaces. According to US EPA, Energy Star data, restaurants, especially quick service restaurants, use 10x the energy of regular commercial buildings(1). Inefficient HVAC, lighting, and kitchen appliances can quietly drain profit margins. With real time monitoring and AIoT-driven automation, energy management is becoming smarter, more granular, and proactive. 

Enhancements: 

Multi-Tiered Dashboards deliver both enterprise-wide visibility and localized, role-specific insights. 

Asset Performance Dashboards track how efficiently each piece of equipment runs; flagging underperformers early. 

Energy Use Intensity (EUI) Analysis compares performances across stores and highlights hidden savings opportunities. 

AI-Driven Demand Control automates load shedding during peak hours to avoid spikes and penalties. 

Daylight Harvesting and Ventilation Tuning fine-tune environmental settings to match natural light and kitchen activity, reducing waste without compromising comfort. 

Occupancy-Based Controls and Remote Equipment Scheduling automate HVAC and food preparation equipment settings based on foot traffic and store hours. 

Benefits:  These technologies are turning energy management into a strategic advantage, helping streamline workflows, reduce manual oversight, and support smarter, more responsive kitchen environments. 

Lower utility costs and reduced wear on equipment 

Real time adjustments reduce energy waste 

Contribution to sustainability goals and compliance 

Example: 

A QSR chain rolled out an energy management program across its locations, using AI-powered analytics to monitor equipment and optimize performance. The initiative led to saving more than 15% in energy consumption (2). (Note: estimated based on reported project results; actual outcomes may vary.)  

Equipment Maintenance: From Break-Fix to Predictive 

Downtime in a kitchen is costly, not just in repairs, but in lost revenue and service disruption. AI-enabled diagnostics are shifting maintenance from reactive to predictive, increasing uptime and cutting service costs. 

Enhancements: 

Predictive-Based Maintenance eliminates guesswork, triggering service only when needed. 

Oil Life Monitoring maintains food quality while minimizing fryer oil waste. 

Digital PM Logs automate preventive maintenance tracking, ensuring compliance and eliminating manual errors. 

Remote Malfunction Resolution reduces downtime with faster diagnostics and fewer technician visits. 

Smart Scheduling aligns maintenance with off-peak hours to reduce disruption. 

Benefits: 

Maintenance is evolving into a data-driven, predictive process that improves reliability, minimizes disruptions, and frees up staff to focus on other aspects of the business’s operations rather than urgent fixes. 

Increased uptime and kitchen reliability 

Lower maintenance costs and extended asset lifespans 

Streamlined compliance and operational efficiency 

Example:  Across the foodservice and food processing industries, operators implementing AI-driven predictive maintenance systems report striking improvements in equipment reliability. Many organizations have seen 20–30% reductions in maintenance costs and 15–25% drops(3) in unplanned downtime. These gains stem from real-time diagnostics, usage-based maintenance & repairs, and automated maintenance tracking — shifting teams from reactive repairs to proactive operations. This transition not only boosts equipment uptime and lifespan but also gives staff more bandwidth to focus on delivering great customer service.  

Production Management: Consistency at Scale 

Maintaining consistency across multiple locations is one of the toughest challenges in the foodservice industry. Smart production systems help maintain quality and predict demand, without increasing manual effort. 

Enhancements: 

Remote Menu Pushes allow centralized updates across all stores, ideal for promotions, policy changes, or nutritional compliance. 

Cook Cycle Monitoring ensures optimal cooking times, quantities and conditions. 

IoT-Controlled Appliances standardize cooking across locations by enabling remote settings, that can be uniformly applied, for temperature and timing. 

AI Demand Forecasting predicts footfall, enabling stores to preheat and prep just the right amount of food. 

Benefits: 

Intelligent production tools enable consistent output across locations, reduce operational stress on teams, and ensure the brand promise is delivered with every order. 

Consistent food quality and presentation 

Reduced food waste and ingredient spoilage 

Enhanced productivity and less human error 

Example:  A large restaurant chain implemented a connected kitchen program to monitor cold storage across their locations. By leveraging real time data from walk-in chillers, the chain achieved a 20-25%(4) improvement in temperature compliance—ensuring ingredients were stored at optimal conditions, reducing spoilage, and preserving food quality across all locations. (Note: based on reported outcomes from multi-site implementations; actual results may vary.) 

Food Safety Management: Automated Compliance, Assured Trust 

Food safety is most important, but manual tracking of temperature logs, foodborne illness incidents, and cleaning/ sanitation practices is time-intensive and error-prone. Smart sensors and alerts provide 24/7 monitoring and peace of mind. 

Enhancements: 

HACCP Alerts notify staff of any deviations from food safety protocols in real time. 

Refrigeration & Door Monitoring ensure stable temperatures and flags fluctuations. 

Defrost Cycle Automation improve energy efficiency without compromising food safety. 

Benefits:  Food safety is shifting from manual checks to automated assurance — helping teams stay audit-ready, reducing food spoilage, and maintaining high standards with less effort. 

Reduced food waste 

Improved audit readiness and regulation compliance 

Decreased manual work for managers and staff 

Example: 

A restaurant chain implemented a connected program with IoT-enabled monitoring to improve food safety and compliance. With predictive insights and automated alerts, they maintained cold room temperature compliance at 91%, supporting HACCP(5) goals by reducing manual checks, preventing spoilage, and ensuring safer food storage conditions. (5) 

A Unified Vision for the Smart Restaurant 

What do all these systems have in common? They speak to a larger truth: the future of restaurant operations is data-driven, automated, and intelligent. By investing in IoT and AI technologies, operators aren’t just cutting costs, they’re building smarter, safer, and more sustainable restaurants. These investments will soon be table stakes when operating such businesses.  

The payoff isn’t just in numbers. It’s in better customer experience, happier staff, and a resilient operation that’s ready for whatever comes next. 

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AI-Powered ECM's are Shaping the Future of Retail Energy Management Strategy - Environment+Energy Leader

AI innovations in HVAC are helping retailers meet climate mandates, reduce emissions, and maintain operational reliability.

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AI-powered ECMs are shaping the future of Retail Energy Management Strategy 

As Heating, Ventilation and Air-Conditioning (HVAC) equipment consume up to 60% of a store’s energy1 , energy efficiency has moved from a back-office concern to a frontline priority. Rising utility costs, stricter sustainability mandates, and growing consumer expectations around climate-conscious practices are pushing retailers to adopt smarter strategies. That’s where AI-powered Energy Conservation Measures (ECMs) come in—enabling a more intelligent, automated, and scalable approach to energy management.  

Advanced ECMs are more than tweaking thermostat settings. By leveraging real-time data and analytics, retailers can optimize energy consumption, prevent equipment failures, and reduce downtime—driving greater efficiency and reliability across HVAC operations. 

AI is helping reshape energy conservation strategies for multi-site retailers through four key ways: Optimal HVAC Performance, Proactive Fault Detection and Predictive Maintenance, Intelligent Load Management, and Smarter Energy Use at Scale. 

Optimal HVAC Performance  

HVAC systems are at the heart of retail operations—critical not only for customer comfort, but also for ensuring optimal conditions for sensitive goods, especially in food and pharmaceutical environments. Yet, managing these systems efficiently across dynamic retail spaces remains a challenge. Traditional HVAC setups operate on static schedules and fixed temperature setpoints, often leading to unnecessary energy use. AI-powered Energy Conservation Measures (ECMs) address this gap by continuously analyzing real-time inputs—such as occupancy levels, weather data, indoor air quality, and historical trends—to make precise, context-aware adjustments.  

For example, during periods of low foot traffic and favorable outdoor conditions, AI can shift HVAC operations to capitalize on free cooling through economizers. During peak hours or sudden weather shifts, it fine-tunes performance to maintain a consistent in-store environment without excessive energy use. A key advancement is dynamic setpoint optimization—AI recalibrates temperatures throughout the day in response to fluctuating variables like electricity pricing and thermal load. This intelligent control not only reduces energy costs but also enhances operational consistency without compromising shopper or staff comfort. 

Proactive Fault Detection & Predictive Maintenance  

Unplanned HVAC downtime is one of the most expensive challenges for multi-site retail operations, with repair and associated costs potentially costing a company up to $200,000 per hour, according to analyst firm Aberdeen Research. Failures during peak shopping hours or extreme weather events don’t just disrupt store comfort—they lead to lost revenue, customer dissatisfaction, and costly emergency interventions. 2 3 AI can help transform HVAC maintenance activities from reactive to proactive. Through continuous monitoring of system components—like compressors, fans, valves, and sensors— 1 https://areacooling.com/areacademy/energy-consumption-share-in-a-standard-retail-store/ 2 https://www.iiot-world.com/predictive-analytics/predictive-maintenance/the-actual-cost-ofdowntime-in-the-manufacturing-industry/ 3 https://www.aberdeenessentials.com/techpro-essentials/stat-of-the-week-the-rising-cost-ofdowntime/ 

AI algorithms detect early signs of degradation or malfunction. For example, a subtle change in pressure or abnormal vibration might indicate a small fault which could lead to compressor failure. With this data, maintenance teams can intervene before the issue escalates.  

Another major threat AI helps mitigate is refrigerant leaks. These leaks not only compromise system efficiency but also release potent greenhouse gases that harm the environment. Left unaddressed, they can also lead to non-compliance with environmental regulations, exposing retailers to reputational risk and potential penalties. AI-driven monitoring of temperature, pressure, and refrigerant flow enables early detection—helping retailers act swiftly, protect the environment, and stay aligned with both sustainability goals and regulatory standards. 

Moreover, AI-based fault prediction goes beyond fault detection and diagnostics (FDD), which is meant for alerting human operators — it can also initiate autonomous corrective actions. AI ensures uninterrupted performance and dramatically reduces the need for on-site technician visits. 

Intelligent Load Management  

Retailers with multiple locations, spread across many states and/or countries, face an additional challenge: ensuring consistent and efficient performance across a fleet of HVAC equipment. One major inefficiency arises from uneven workload distribution, especially in stores that operate several rooftop units (RTUs). Over time, some units bear more load than others, leading to premature wear and higher maintenance, and replacement, costs.  

This is where AI-driven dynamic load redistribution makes a critical difference. These algorithms balance HVAC loads across all available RTUs, extending equipment lifespan and improving overall efficiency. Think of it like rotating tires on a car—by sharing the workload evenly, you reduce strain and get more life out of your system. 

AI also helps eliminate mode mismatches, a common and costly issue in HVAC equipment where one unit is heating while another is cooling the same zone. Not only does this create inconsistent indoor climates, but it also drives up energy consumption and increases the wear of the equipment. AI continuously monitors and aligns system operations to prevent such conflicts in real time.  

Furthermore, AI helps optimize energy usage during peak demand periods. Through Automated Demand Response (ADR), HVAC equipment, lighting, and even refrigeration equipment can be adjusted in response to utility pricing signals. By shedding or shifting loads strategically, retailers can avoid hefty peak demand charges and operate more cost-effectively. 

Smarter Energy Use at Scale  

Perhaps one of the most transformative aspects of AI in retail energy management is the ability to centralize control and decision-making. With AI-powered remote service and diagnostics, facilities teams can oversee hundreds—or even thousands—of HVAC equipment across multiple geographies without being physically present. 

These remote platforms, which can be managed from anywhere with a mobile phone, tablet, or computer, allow for real-time monitoring, troubleshooting, and even resetting of systems. This not only lowers operational costs but also reduces response time and improves service quality. Many issues that would traditionally require an on-site visit can now be handled remotely, lowering the overall maintenance costs. 

AI also plays a pivotal role in improving sensor accuracy. Faulty or missing sensors can lead to erroneous temperature readings, causing HVAC equipment to overcompensate and waste energy. AI-driven data replacement models detect anomalies and intelligently fill in missing or incorrect values, ensuring seamless and reliable operation.  

This level of data integrity is crucial when managing hundreds of assets across locations with varied climates, foot traffic patterns, and energy tariffs. By having a clear, accurate picture of system performance, retailers can make smarter decisions—not just reactively, but proactively and strategically. 

Towards A Smarter, More Sustainable Retail Future  

Retailers can now proactively make smarter decisions with AI technologies. Those already leveraging these innovations are seeing measurable benefits: lower utility bills, reduced carbon emissions, improved operational reliability, and enhanced customer comfort. Just as importantly, they’re aligning with the values of today’s climate-conscious consumers.  

As energy prices climb and sustainability expectations grow, AI-driven ECMs are quickly becoming the standard in modern retail operations. Strategic investments in predictive maintenance, intelligent load management, and remote diagnostics are essential for retailers aiming to boost efficiency, strengthen resilience, and lead in sustainable operations.  

For retail businesses aiming to operate more efficiently and responsibly, the path forward is clear: start where you are, scale thoughtfully, and let AI guide the transition to a smarter, greener future. 

Author  

Parminder Singh, Director - Presales & Offering Management for Americas at Carrier Abound  

Parminder Singh leads Presales & Offering Management for Americas at Carrier Abound in North America and is primarily focused on crafting innovative and award-winning energy management and IoT enabled solutions for multi-site operators. He has over 20 years of experience working in product management, solution design, client engagement, operations management, business consulting, new product development, launch and global delivery. He holds a graduate degree in Mechanical Engineering and is a post-graduate in Business Administration. 

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CapitaLand offers enterprise colocation services to elevate your data centre capabilities. Uncover robust solutions for enhanced performance

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CapitaLand Investment partners with major domestic insurance company to establish its first onshore master fund in China with RMB5 billion equity

CapitaLand Investment Limited (CLI), a leading global real asset manager, has established its first onshore master fund in China, CLI RMB Master Fund, with a total equity commitment of RMB5 billion (S$921 million)1 . CLI has secured a major domestic insurance company to take up a majority stake in the master fund in line with its asset-light strategy to grow its funds under management (FUM). The master fund is expected to contribute RMB20 billion (S$3.7 billion)1 to CLI’s FUM when fully deployed.

The master fund will invest in a series of sub-funds that will seek to acquire high-quality, incomeproducing assets with long-term growth potential. The sub-funds will invest in business parks, retail, rental housing and serviced residences across Tier one and top Tier two cities. Future subfunds may also invest in special opportunities in other sectors such as data centres, logistics parks and offices.

Mr Puah Tze Shyang, Chief Executive Officer of CLI China, said: “Leveraging our over 30 years of experience in China and deep on-the-ground expertise, our first master fund in China demonstrates CLI’s capabilities in structuring and launching a diversified suite of RMB funds tailored to domestic investors’ needs. This allows us to tap into a rising trend of insurance companies increasing their capital allocation to real estate in China, providing them opportunities to invest in a diversified and resilient portfolio of stabilised assets with core returns. With a major domestic insurance company as a co-investor in the master fund, we are well-placed to attract other insurance firms to invest in the sub-funds and rapidly expand our domestic investor base. With this new fund, we have successfully raised RMB54 billion across seven RMB funds since 2021, demonstrating the strong momentum of our domestic-for-domestic fund strategy to grow FUM and recurring fee income.”

Ms Kara Wang, Chief Investment Officer of CLI China, said: “CLI’s strong balance sheet enables us to co-invest in our private funds, aligning our interests with those of our capital partners. The master fund’s strategy of investing in asset classes such as business parks, retail, rental housing 1 Based on exchange rate of RMB1 to S$0.184250. 2 and serviced residences aligns closely with China’s national priorities, supporting its transition into a consumption- and innovation-driven economy.” CLI in China

CLI has a resilient and well-diversified portfolio of more than 300 properties across over 40 cities. This includes office, retail, lodging, business parks, logistics and data centres in five core Tier one and two city clusters2 . The launch of the master fund follows CLI’s announcement in April 2025 that it has applied to list its first real estate investment trust in China, to be named CapitaLand Commercial C-REIT3 . The first international-sponsored retail C-REIT will broaden CLI’s access to domestic capital and further grow its recurring fee income. About CapitaLand Investment Limited (www.capitalandinvest.com) Headquartered and listed in Singapore in 2021, CapitaLand Investment Limited (CLI) is a leading global real asset manager with a strong Asia foothold. As at 31 March 2025, CLI had S$117 billion of funds under management held via stakes in seven listed real estate investment trusts and business trusts and a suite of private real asset vehicles that invest in demographics, disruption and digitalisation-themed strategies. Its diversified real asset classes include retail, office, lodging, industrial, logistics, business parks, wellness, self-storage, data centres, private credit and special opportunities.

CLI aims to scale its fund management, lodging management and commercial management businesses globally and maintain effective capital management. As the investment management arm of CapitaLand Group, CLI has access to the development capabilities of and pipeline investment opportunities from CapitaLand Group’s development arm. In 2025, CapitaLand Group celebrates 25 years of excellence in real estate and continues to innovate and shape the industry.

As a responsible company, CLI places sustainability at the core of what it does and has committed to achieve Net Zero carbon emissions for Scope 1 and 2 by 2050. CLI contributes to the environmental and social well-being of the communities where it operates, as it delivers long-term economic value to its stakeholders.

Follow @CapitaLand on social media LinkedIn: linkedin.com/company/capitaland-limited Facebook: @capitaland / facebook.com/capitaland Instagram: @capitaland / instagram.com/capitaland X: @CapitaLand / x.com/CapitaLand YouTube: youtube.com/capitaland

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2021 has been a year of transformation for us. Amid ongoing challenges from the pandemic, CapitaLand has taken the bull by its horns, seized opportunities and made bold steps forward to set ourselves apart from the competition.

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CapitaLand Investment Group scores five wins at the Singapore Corporate Awards 2023

 CapitaLand Investment Group has scored five awards at this year’s Singapore Corporate Awards (SCA).  Among its wins, CapitaLand Investment Limited (CLI) took home the Gold Award for Best Risk Management for listed companies with S$1 billion and above in market capitalisation – a first for the company.  CLI also clinched the Bronze Award for the Best Annual Report.

In the Real Estate Investment Trusts (REITs) and Business Trust category, CapitaLand Ascendas REIT (CLAR) won the Gold Award for Best Annual Report, the sixth time it has received an award in this category.  CapitaLand India Trust (CLINT) also obtained the Bronze Award for Best Annual Report, the first time it has received an award in this category.  It had previously won the Gold Award for Best Investor Relations in 2018.  In addition, CapitaLand Integrated Commercial Trust (CICT) bagged the Silver Award for Best Investor Relations, the third recognition it has received in this category at the SCA. 

CLI – Best Risk Management Award (Gold) and Best Annual Report (Bronze)

The Best Risk Management Award was introduced in 2019 to recognise and raise awareness of the core and leading risk management practices required to support and sustain the strategic direction of companies, especially in the age of technology and disruption. 

The Best Annual Report Award recognises excellence and clarity in financial reporting and presentation while considering a broader scope of disclosure beyond minimum regulatory requirements that are in tandem with the needs of investors and other stakeholders such as employees, creditors and the general investing public.

Mr Kee Teck Koon, CLI Board Risk Committee Chairman, said: “CLI adopts a strategic approach by regularly scanning for future and emerging risks, such as in geopolitical and environmental shifts, which could potentially impact the risk-reward relationships for our portfolio of diverse businesses.  Business units are then empowered to operate within an agreed risk appetite and management framework.  This strategy fosters risk ownership and performance accountability in business decision-making.

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Enhancing End User Experience: A Comprehensive Guide  - 1E

The A – Z of End User Experience  

What is end user experience? When we talk about end user experience in the context of IT operations, we’re referring to the performance of IT resources from the perspective of an end user. How do your employees experience the digital workplace provided to them? How do they experience the end-user device (e.g., laptop, tablet, mobile), applications, and everything in between?  

What is end-user experience monitoring (EUEM)?: Another term you’ll no doubt come across in the world of end user experience is end-user experience monitoring (EUEM). This refers to monitoring the performance of IT resources from the end user's perspective and focuses on quantifying that end user’s experience.  

What is end-user computing (EUC)?: To stay aware of end user experience and monitor the performance of resources, IT teams turn to end-user computing (EUC). This term refers to technologies that IT professionals use to deploy, manage and secure the devices, applications, and data that form the digital workplace employees experience.

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