Innovations in QSR could be rolled out in months thanks to Gen AI

Key AI applications include predictive forecasting, finance automation, and personalisation.

Gen AI has shortened the innovation cycle from five to 10 years to just six to 12 months, according to Emma Pitfield, Partner, Consulting at KPMG during a speaking session titled AI - Beyond the Hype during the QSR Media Conference & Awards 2024.

This means the quick-service restaurant (QSR) industry is witnessing a significant shift as artificial intelligence (AI) becomes a critical tool for streamlining operations to enhance customer experiences and address labour challenges, Pitfield said.

Brad Daffy, Partner, Intelligent Automation, AI & Low Code at KPMG echoed this sentiment, emphasising that the rise of gen AI technologies has also brought AI into mainstream business conversations. 

“I think what we're seeing now is these technologies— that we've become quite familiar with using in our personal lives— are entering the workforce and with the rise of platforms like Microsoft's copilot which is being rolled out as a desktop assistant. We're seeing a continued push of these technologies into becoming our little digital assistants in the workplace,” Daffy said. 

In the QSR sector, personalisation and predictive analytics for inventory management are emerging as key areas where AI is delivering tangible results. Pitfield noted that 66% of recent statistics show that AI is being used to analyse customer data and create personalised recommendations. 

Moreover, 62% was around generating content marketing copy and product summaries, and 58% was around customer service chatbot. 

Daffy also highlighted how predictive and intelligent forecasting is being used to inform critical business decisions. 

“It is the ability to leverage data from the marketplace, population movements, demographics, building approvals, and even sort of the frequency of things like Uber drop-offs, that start to inform forecasting of where to open new sites, the demand for goods, the margin, etc.,” said Daffy. 

Whilst large QSRs like Starbucks are at the forefront of AI-driven personalisation and operational efficiency said Daffy, smaller chains can also tap into AI’s potential. 

Pitfield added that AI tools like Copilot can help with automating simple tasks such as drafting emails or analysing customer feedback.

However, as AI is utilised in the QSR industry, concerns about job displacement persist; but both Pitfield and Daffy argue that AI can complement human labour rather than replace it. 

“There's a lot of manual tasks in QSR that are exhausting,” said Pitfield, who reflected on her decade of experience working in QSR stores.

“So if we can find ways to make those tasks easier, we give more time to our crew and managers to spend more time on the floor looking after their customers as well,” she said. “So I think, it's about how do we have that talent, focusing on more of the hospitality elements versus the sort of mechanical operational elements as well.”

Daffy also emphasised the need for training and development as AI changes the nature of work. 

“Training and development will be a major focus as we teach both new and existing workforce members how to use these technologies, and how roles need to evolve and adjust to leverage AI,” he said.

Looking ahead, AI’s ability to unlock new levels of efficiency and customer satisfaction will be pivotal for QSRs seeking to stay competitive and Daffy said that the key to increasing the adoption of AI is its ability to prove success. 

“And I would encourage everyone to think about what are those use cases where you can start to pilot and scale the use of AI, and once you can start to demonstrate within the organisation— here are the use cases, here are the benefits— it works,” he said.