Technology is opening new doors for senior living operators – transforming resident experience, operational efficiency, and market positioning. According to a 2024 industry report, 83 percent of large multi-community operators say that using technology to support operational tasks saves more than eight staff hours per month. 

Opportunities are emerging across dining, care, and operations. In memory care, AI-powered food imaging systems like AFINI-T analyze meal plates before and after dining to track resident intake more accurately than staff observation. Robotics are also making inroads: Service robots such as Servi can free dining staff from repetitive tasks so they can focus more on resident support. (One Servi user, Cypress Living in Fort Myers, Fla. reports saving about 330 hours per week of front-of-house culinary staff time – and they have reinvested some of that benefit in higher staff pay.) Predictive analytics and remote monitoring tools can flag early changes in a resident’s gait, hydration, or activity that might signal a health decline, giving staff time to intervene. 
On the operations side, automation in scheduling, supply ordering, and compliance helps reduce paperwork and frees labor to support direct care. Resident-facing tech is also evolving: Digital ordering systems, adaptive dining utensils, and engagement platforms can personalize mealtimes and activities, reduce social isolation and boost independence.

At a time when so many functions of a foodservice business can be monitored and measured, data is a critical resource. Yet many businesses are still figuring out how to translate their collected insights into helpful action that can make the business perform better. Hospitality Technology’s 2025 Restaurant Technology Study addressed this issue, among other topics, and found some common themes in the businesses that are handling this well.
The businesses that are getting data collection/action right are doing four things: They are breaking down data silos by integrating information that lives in separate places so that people in different parts of the business all see the full story. They are moving beyond just describing what happened in their restaurant the previous week – instead, they’re using their data to predict what’s coming (then adjusting promotions, labor and other factors in response). They’re making analytics accessible beyond the headquarters of the business – so field managers, franchisees and general managers can access role-based insights that matter to them (and affect their decision-making). Finally, they are using the insights they gain to drive targeted changes, then measuring the result (and using that to inform future plans).
While many of these insights can be collected from within the business, partner data is useful and actionable too. The Japanese restaurant chain Maki & Ramen has used data from their third-party delivery partner to get real-time insights into delivery times and guest preferences. This has informed both their staffing and inventory management.
CKE Restaurants implemented a robust traceability system across its supply chain to enhance its food safety program. It allows them to track food items from suppliers to restaurant tables. The change has helped them target recalls with greater precision and alert locations to expired products. The sharing of this information – and actions taken as a result – have helped the company improve its overall inventory management.

​As artificial intelligence becomes a larger part of consumers’ daily lives, it is taking a couple of distinct paths in the restaurant industry. Its generative applications are helping restaurants respond in real time to guest questions in the drive-thru line, as well as draft emails to staff and develop ideas for guest promotions. Its predictive applications are enabling restaurants to make more educated decisions about how to manage inventory, schedule staff, and anticipate guest traffic over a holiday weekend. These applications are increasingly being woven into restaurant tech platforms and becoming just a part of doing business – Square and AzureOpenAI are among the companies whose generative and predictive AI applications being adopted by large brands right now, Restaurant Dive reports.

The past few years have delivered a combination of challenges that would have been difficult to predict. But imagine if you had had some information on hand in 2019 that allowed you to proactively make critical business decisions in 2020? By using technology to tap into the probabilities of an event, your business can better prepare for the different risks it may face. Predictive analytics is one tool that can help operators get a better handle on everyday food safety and quality risks, as well as how risks like climate change and extreme weather could impact the safety and supply of key ingredients down the line. As a recent report from Restaurant Technology News explains, predictive analytics uses advanced data analysis to predict the future based on probabilities, then refines those predictions using machine learning and artificial intelligence. It could help restaurants pinpoint potential threats, like pathogen-related outbreaks, before they occur, then take preemptive action to keep their business and guests safer.

Restaurant technology is not only about helping an operator respond with speed and precision to what’s happening in the moment; it’s also about predicting and preparing for what is likely to happen in the near future. In a recent report from FSR Magazine, the CEO of the restaurant Bartaco said that technology such as predictive prep lists, dynamic pricing and smart kitchen display systems will be critical to helping operators preserve margins without passing excessive costs on to guests this year. All of these solutions are about anticipating demand and preparing for it. How well does your current tech setup allow you to anticipate what’s coming – and rapidly change course as needed?