Navigating the AI Journey:

By Clinton Anderson|Nov 1, 2024|3:58 pm CDT

The restaurant industry has reached a pivotal moment in its adoption of artificial intelligence. While AI is no longer a futuristic concept, the journey to implementing it successfully varies based on business size. Independent operators face different challenges and requirements than multi-location enterprises, impacting the types of AI solutions they need. This guide highlights key considerations for both independent and multi-location restaurants, with essential questions to help evaluate AI vendors based on your unique needs. 

In this article you’ll learn: 

• How business size impacts AI adoption 

• Key questions to assess if an AI vendor meets your needs 

Both independent and multi-location restaurants can benefit from AI, but their needs and adoption journeys differ. Below is a break down the major considerations to keep in mind as you embark on your AI journey. 

AI Adoption Considerations: Key Differences for Independent Operators vs. Multi-Location Enterprises

Essential AI Evaluation Questions

Budget: Balancing Cost with Impact

Independent Operators: Small restaurants often operate on tighter budgets, so their focus is on cost-effective AI solutions that solve specific pain points quickly. They typically seek modular, “plug-and-play” tools that fit into existing operations with minimal disruption. 

• Key Question: “How does your pricing structure work for smaller businesses with limited budgets, and are there modular options that allow us to start small and expand as needed?” 

Multi-Location Enterprises: Larger businesses can allocate bigger budgets for comprehensive AI systems. They’re often interested in scalable AI platforms that can centralize operations and standardize processes across locations. 

• Key Question: “Do you offer customizable AI options that align with a larger budget, such as systems that can scale across locations with a staged pilot?”

Focus: Targeting Immediate Needs vs. Comprehensive Solutions

Independent Operators: Smaller restaurants typically focus on immediate, high-impact solutions, addressing areas like staffing or inventory management where AI can bring quick returns. 

• Key Question: “Can this solution address our most immediate needs, like staffing efficiency or inventory control, without a lengthy implementation process?” 

Multi-Location Enterprises: Larger enterprises require comprehensive solutions that can improve multiple areas of the business, such as supply chain management, customer analytics, and employee scheduling. 

• Key Question: “How does your platform address multiple operational needs, such as staffing, supply chain, and customer analytics, in an integrated way?”

Ease of Adoption: Plug-and-Play vs. Structured Implementation

Independent Operators: Smaller restaurants prioritize ease of adoption, often looking for plug-and-play solutions that don’t require technical expertise or disrupt day-to-day operations. 

• Key Question: “Is this solution plug-and-play? What level of technical expertise is required on our end?” 

Multi-Location Enterprises: With larger, multi-location companies, a structured and phased approach is often necessary to avoid disruption. These enterprises may dedicate resources to more complex, longer-term rollouts. 

• Key Question: “What does the implementation cycle look like for a phased rollout, and how can you minimize disruptions across locations?”

Scalability: Current Needs vs. Future Growth

Independent Operators: Small restaurants often focus on current needs and don’t always prioritize scalability. However, it’s crucial to consider AI tools that can grow with the business. 

• Key Question: “If our business grows, can this solution expand with us, or would we need a new system?” 

Multi-Location Enterprises: Scalability is a critical need for multi-location businesses. AI solutions must integrate seamlessly across various locations and align with existing systems to maintain consistency. 

• Key Question: “Can this AI solution scale seamlessly across our growing locations and integrate with existing tech systems?”

Implementation Time: Quick Wins vs. Strategic Planning

Independent Operators: Small businesses prefer AI solutions that provide quick wins and immediate returns on investment. 

• Key Question: “How quickly can we expect to see a return on investment once we go live with this solution?” 

Multi-Location Enterprises: For larger businesses, AI implementation often requires more strategic planning and may involve phased rollouts across locations. 

• Key Question: “What strategic planning and timeline considerations do you recommend for implementing AI at scale in our business?”

Data Utilization: Basic vs. Advanced Insights

Independent Operators: Small businesses typically use AI for basic data, such as day-to-day inventory or sales insights, to drive immediate operational improvements. 

• Key Question: “How does your system utilize our daily data (e.g., inventory) to offer quick, actionable insights?” 

Multi-Location Enterprises: Larger companies rely on centralized data analysis to understand customer behavior, inventory trends, and sales patterns across multiple locations. 

• Key Question: “How does your system centralize and analyze data across all locations to provide insights on customer behavior, sales trends, and inventory?”

Vendor Support: Essential Guidance vs. Collaborative Customization

Independent Operators: Smaller restaurants heavily rely on vendor support to help with adoption, integration, and ongoing troubleshooting. 

• Key Question: “What level of ongoing support and guidance can we expect as we start using your platform?” 

Multi-Location Enterprises: Larger businesses often work with vendors to create customized AI solutions, forming a collaborative partnership. 

• Key Question: “What level of ongoing, collaborative support do you offer for customizations and troubleshooting?”

Innovation: Immediate Needs vs. Experimental Technologies

Independent Operators: Smaller restaurants focus on AI that solves current operational challenges. They tend to be less experimental due to budget constraints. 

• Key Question: “Does this solution focus on solving day-to-day operational challenges, and are updates included to keep up with changes?” 

Multi-Location Enterprises: Larger enterprises are more likely to explore experimental AI technologies, such as robotics and advanced analytics, to stay ahead in the competitive market. 

• Key Question: “What new and experimental AI technologies, like advanced analytics or robotics, do you offer or have on your roadmap?”

Change Management: Small Teams vs. Large Distributed Teams

Independent Operators: Smaller teams often find change management more straightforward, with fewer training needs and a faster onboarding process. 

• Key Question: “What training resources do you provide to get our team up to speed quickly and effectively?” 

Multi-Location Enterprises: Managing change across large teams at multiple locations requires extensive training, ongoing support, and change management resources.

• Key Question: “How do you support change management for large, distributed teams, including training and ongoing education?” 

Conclusion

AI offers transformative potential for restaurants of any size, but choosing the right approach requires understanding your unique needs. For independent operators, the focus should be on immediate-impact, budget-friendly solutions, while multi-location enterprises require scalable platforms that provide comprehensive insights across their operations. By asking the right questions and aligning with vendors who understand your specific challenges, you can unlock the full potential of AI to streamline operations, boost efficiency, and ultimately enhance the customer experience.