The Ultimate Retail AI Checklist: 10 Questions to Ask Before Selecting an AI Solution

AI is rapidly changing retail, but selecting the right solution requires more than an impressive demo.

The questions a retailer should ask a Voice AI provider are very different from the questions they should ask a pricing optimization, loss prevention, workforce management, inventory, or computer vision provider.

Retailers need to understand whether the technology works in a real-world environment, integrates with their existing systems, delivers measurable business value—and what it will actually cost once fully deployed.

That's why SimplifyRetailAI created the Ultimate Retail AI Checklist: 10 application-specific questions retailers should ask before selecting an AI solution.

1. Smart Drive-Thru Technology

AI-powered voice ordering and automation can improve order accuracy, increase throughput, reduce employee workload, and enhance the customer experience.

Before selecting a Smart Drive-Thru solution, ask:

1. What percentage of orders can your AI complete without employee intervention?

2. What is your order accuracy rate in actual restaurant environments?

3. How does the AI perform with accents, background noise, multiple passengers, children speaking, and customers changing their orders?

4. How does the system handle substitutions, modifiers, combos, unavailable products, and location-specific menus?

5. What happens when the AI cannot understand or complete an order, and how quickly can an employee take over?

6. Which POS, loyalty, menu management, payment, and kitchen systems do you currently integrate with?

7. Can the AI automatically upsell or recommend products, and what measurable impact have customers seen on average ticket?

8. What measurable improvements have existing customers achieved in speed of service, order accuracy, labor productivity, and sales?

9. What is our true total cost to implement and operate the solution? Include software, drive-thru hardware, microphones, speakers, installation, POS/menu integrations, training, support, maintenance, and any usage-based charges.

10. How could our costs increase after implementation? Are annual increases capped, and how will pricing change as we add restaurants, increase order volume, add functionality, or renew our agreement?

2. Shelf Intelligence & Inventory Management

AI-powered shelf intelligence can help retailers improve inventory accuracy, identify out-of-stocks, verify pricing, improve merchandising compliance, and reduce manual store tasks.

Before selecting a Shelf Intelligence or Inventory Management solution, ask:

1. How accurately can your technology identify individual products and distinguish between similar packages, sizes, and varieties?

2. How frequently can your system provide updated shelf and inventory information?3. Can the platform automatically identify out-of-stocks, low inventory, misplaced products, pricing errors, and planogram violations?

4. How is shelf data collected—robots, fixed cameras, handheld devices, shelf sensors, existing cameras, or another method?

5. How does the solution connect shelf conditions with our inventory and replenishment data?

6. Can identified issues automatically create prioritized tasks for store employees?

7. How does performance change based on lighting, shelf density, store layout, or product placement?

8. Which POS, ERP, inventory, replenishment, pricing, and merchandising platforms do you integrate with today?

9. What is our true total cost to implement and operate the solution? Include software, robots, cameras, sensors, handheld devices, installation, integrations, maintenance, support, and additional store infrastructure.

10. How could our costs increase after implementation? Are annual increases capped, and how will pricing change as we add stores, products, devices, data volume, functionality, or additional use cases?

3. Voice AI

Conversational AI can automate customer interactions, employee assistance, ordering, support, and other business communications.

Before selecting a Voice AI solution, ask:

1. What percentage of conversations can your AI successfully resolve without human assistance?

2. How accurately does the system understand accents, background noise, interruptions, industry terminology, and complex questions?

3. How quickly does the AI respond during a conversation, and what is the typical latency?

4. What happens when the AI doesn't know an answer or misunderstands the customer?

5. How seamlessly can a conversation be transferred to an employee while preserving the context of the interaction?

6. Can the AI access real-time information from our POS, CRM, inventory, order management, loyalty, or scheduling systems?

7. How much control do we have over the AI's voice, tone, terminology, responses, and brand personality?

8. How do you prevent the AI from providing incorrect or unauthorized information, and how is customer data protected?

9. What is our true total cost to implement and operate Voice AI? Include software, integrations, implementation, training, telephony, AI/model usage, minutes, conversations, support, and third-party charges.

10. How could our costs increase after implementation? Are annual increases capped, and will higher call volume, conversations, AI usage, locations, functionality, or model upgrades increase our price?

4. Self-Checkout AI

AI-powered checkout solutions can automate product recognition, accelerate transactions, reduce friction, and improve checkout accuracy.

Before selecting a Self-Checkout AI solution, ask:

1. What percentage of products can your system automatically recognize without the customer scanning a barcode?

2. How accurately can the AI distinguish between visually similar products and different varieties of produce?

3. What is the average transaction time compared with traditional self-checkout?

4. How often does an employee need to intervene during a transaction?

5. Can the AI detect missed scans, product switching, barcode manipulation, or other suspicious checkout behavior?

6. How does the system handle produce, weighted items, age-restricted products, coupons, loyalty programs, and promotions?

7. Can the solution integrate with our existing POS and payment infrastructure?

8. What happens when the system incorrectly identifies a product or flags a legitimate transaction?

9. What is our true total cost to deploy and operate the solution? Include software, cameras, kiosks, scales, sensors, installation, POS/payment integrations, maintenance, support, and replacement hardware.

10. How could our costs increase after implementation? Are annual increases capped, and how will pricing change as we add checkout lanes, stores, transaction volume, new capabilities, or hardware upgrades?

5. AI Pricing Optimization

AI-powered pricing solutions can optimize everyday pricing, promotions, and markdowns by analyzing demand, inventory, competition, and customer behavior.

Before selecting an AI Pricing Optimization solution, ask:

1. What data does your AI use to generate pricing recommendations?

2. Can the platform separately optimize everyday pricing, promotions, and markdowns?

3. How does the AI account for demand elasticity, inventory, competitor pricing, seasonality, product relationships, and customer behavior?

4. Can we establish pricing rules such as minimum margins, maximum price changes, competitive indexes, and other business guardrails?

5. Can your system explain why it recommends a specific price change?

6. Where does your competitive pricing data come from, and how frequently is it updated?

7. Can pricing recommendations vary by store, region, channel, customer segment, or inventory position?

8. How do you measure whether increased revenue or margin was actually caused by the AI recommendations?

9. What is our true total cost to implement and operate the pricing platform? Include software, implementation, data integration, competitive pricing data, consulting, training, support, and additional modules.

10. How could our costs increase after implementation? Are annual increases capped, and will additional SKUs, stores, users, data sources, pricing modules, channels, or transaction volume increase our price?

6. Computer Vision AI

Computer vision AI can analyze video and in-store activity to improve inventory visibility, reduce shrink, optimize merchandising, generate shopper insights, and enable frictionless experiences.

Before selecting a Computer Vision AI solution, ask:

1. Which specific activities, objects, behaviors, or conditions can your computer vision models reliably identify?

2. What detection accuracy should we expect in an actual retail environment?

3. What are your typical false-positive and false-negative rates?

4. Can your technology operate using our existing security cameras, or will new cameras be required?5. How do camera positioning, resolution, lighting, store layout, crowds, and blocked sightlines affect performance?

6. Is video analyzed locally at the store, in the cloud, or through a combinationofboth?

7. What video or customer information is stored, and how is personally identifiable information protected?

8. Can detected events automatically generate alerts, tasks, or actions for employees, and how does the platform integrate with our other retail systems?

9. What is our true total cost to deploy and operate Computer Vision AI? Include software, cameras, edge devices, networking, cloud processing, video storage, installation, integrations, maintenance, and support.

10. How could our costs increase after implementation? Are annual increases capped, and how will additional cameras, stores, video volume, cloud processing, storage, analytics, or new use cases affect pricing?

7. Loss & Fraud Prevention AI

AI-powered loss prevention and fraud detection can analyze transactions, video, and store activity to detect theft, identify fraud, improve investigations, and reduce shrink.

Before selecting a Loss & Fraud Prevention AI solution, ask:

1. Which types of loss can your AI detect—external theft, employee theft, self-checkout loss, return fraud, organized retail crime, or operational errors?

2. What data does the AI analyze to identify suspicious activity?

3. What are your typical false-positive rates, and how do you prevent store teams from becoming overwhelmed with alerts?

4. Can your system connect suspicious POS transactions directly to the corresponding video?

5. Can the AI identify patterns involving the same individual, employee, transaction type, product, or behavior across multiple stores?

6. How does the solution prioritize incidents based on potential risk or financial impact?

7. What tools are provided for investigations, case management, evidence collection, and reporting?

8. How do you address privacy, biometric, employee monitoring, data-retention requirements, and appropriate employee responses to AI-generated alerts?

9. What is our true total cost to implement and operate the loss prevention platform? Include software, cameras or hardware, POS/video integrations, data storage, implementation, investigation tools, training, maintenance, and support.

10. How could our costs increase after implementation? Are annual increases capped, and will adding stores, cameras, transactions, users, investigations, data storage, or additional fraud capabilities increase our price?

8. Shopping Assistant AI

AI shopping assistants can improve product discovery, answer shopper questions, personalize recommendations, increase conversion, and strengthen customer loyalty.

Before selecting a Shopping Assistant AI solution, ask:

1. How does the AI learn and understand our complete product catalog?

2. Can shoppers ask conversational questions rather than searching with specific product keywords?

3. Can the assistant compare products and explain meaningful differences between them?

4. Can recommendations incorporate real-time inventory so customers aren't directed toward unavailable products?

5. Can the AI personalize recommendations using loyalty, purchase history, browsing behavior, or stated preferences?

6. How do you prevent hallucinations, inaccurate product information, or incorrect answers about retailer policies?

7. Can the assistant understand follow-up questions and maintain context throughout the shopping conversation?

8. Can the same AI experience operate across our website, mobile app, messaging platforms, kiosks, and stores, while allowing our merchandising teams to control recommendations?

9. What is our true total cost to implement and operate the AI Shopping Assistant? Include software, implementation, catalog integration, AI/model usage, conversations, API calls, personalization, support, and third-party services.

10. How could our costs increase after implementation? Are annual increases capped, and will increased shopper usage, conversations, AI/model consumption, channels, product volume, personalization, or new capabilities increase our price?

9. Retail Analytics & Intelligence

AI-powered retail analytics can help retailers understand customer behavior, predict demand, optimize operations, identify trends, and make better business decisions.

Before selecting a Retail Analytics & Intelligence solution, ask:

1. Which retail data sources can your platform combine and analyze?

2. How quickly can new data become available for analysis after a transaction or event occurs?

3. Can business users ask questions in natural language without needing SQL, analysts, or technical expertise?

4. Can the AI move beyond reporting what happened and explain why it happened?

5. What predictive capabilities are available for demand, customer behavior, inventory, sales, traffic, and other retail KPIs?

6. Can the system proactively identify anomalies, opportunities, or risks without someone searching for them?

7. Can the AI recommend specific actions based on the insights it identifies?

8. Can dashboards and insights be customized for different roles, and can users understand the data and reasoning behind AI-generated recommendations?

9. What is our true total cost to implement and operate the analytics platform? Include software, implementation, data integration, storage, cloud computing, users, AI queries, training, consulting, support, and additional analytics modules.

10. How could our costs increase after implementation? Are annual increases capped, and how will additional users, stores, data sources, data volume, AI queries, storage, analytics capabilities, or computing requirements affect our price?

10. Workforce Management

AI-powered workforce management solutions can help retailers forecast labor demand, optimize employee scheduling, improve productivity, control labor costs, streamline workforce operations, and enhance the employee experience.

Before selecting a Workforce Management AI solution, ask:

• 1. What data does your AI use to forecast labor demand?

• 2. How accurately can the platform forecast staffing requirements by store, department, role, and time of day?

• 3. Can schedules automatically account for employee availability, skills, preferences, seniority, and required certifications?

• 4. How does the AI balance labor cost against customer demand and service requirements?

• 5. Can the platform automatically account for overtime, breaks, minors, predictive scheduling laws, union requirements, and other labor rules?

• 6. Can employees view schedules, request time off, update availability, swap shifts, and claim open shifts from a mobile device?

• 7. Can managers understand why the AI is recommending a particular staffing level or schedule?

• 8. Which payroll, HRIS, timekeeping, POS, and other workforce systems do you integrate with, and how much manager time can the solution realistically save?

• 9. What is our true total cost to implement and operate the workforce management solution? Include software, implementation, payroll/HRIS/POS integrations, training, mobile capabilities, support, maintenance, and additional modules.

• 10. How could our costs increase after implementation? Are annual increases capped, and how will additional employees, stores, users, modules, integrations, or functionality affect our price?

  
  

The Final Retail AI Test

While the questions differ by application, every Retail AI investment should ultimately pass the same test:

Does it solve a real business problem?

AI should address a clearly identified operational, customer, employee, revenue, margin, or risk-related challenge.

Does it work in our actual retail environment?

A controlled demonstration is not the same as operating successfully across real stores, restaurants, employees, customers, products, and peak periods.

Does it integrate with our technology?

The value of AI can be dramatically reduced if it cannot effectively communicate with the retailer's existing POS, ERP, CRM, inventory, workforce, payment, loyalty, or other systems.

Can the vendor prove measurable results?

Ask for results from retailers with similar environments, store counts, transaction volumes, and business challenges.

What will it really cost?

The initial proposal is only part of the equation.

Retailers should understand the complete Total Cost of Ownership (TCO), including:

Software + Implementation + Integration + Hardware + AI/Usage Charges + Data/Cloud Costs + Support + Maintenance + Internal Resources + Future Price Increases

And perhaps most importantly, ask:

“If this solution is successful and we deploy it across our entire organization, what will we actually be paying three years from now?”

That number may be significantly different from the cost of the initial pilot.

From AI Demo to Business Decision

The goal of an AI evaluation shouldn't be to determine which vendor gives the most impressive demonstration.

It should determine which solution can deliver the greatest measurable business value with an acceptable level of cost, risk, complexity, and organizational change.

Before selecting a vendor:

Ask the questions. Establish the baseline. Define the KPIs. Understand the total cost. Run the pilot. Measure the results.

Then make the decision.

Because the best Retail AI solution isn't necessarily the one with the most impressive technology.

It's the one that delivers the greatest measurable value to the retailer.