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AI platforms enable airports to manage queues with confidence so passengers can wait less and shop more. Unlike existing sensors and data services, AI can gather accurate data easily using existing hardware or without having to spend at all on custom equipment or dedicated teams of people. No wonder AI is at the top of the shopping list for airports.
However, researching and buying an AI platform for the first time can be daunting. In this guide, you will learn how the AI buying process works, and what you should be doing in each stage to find the best AI solution for your organization.
Here are the 4 stages of buying an AI platform for your airport.
Stage 1: Discuss your priorities, timeline, and budget so you get accurate information from solution providers
Once you know that an AI platform could help your organization, it’s time to start looking at your options. Based on your internal conversation, setup evaluation criteria and start listing vendors and evaluate them based on the criteria you’ve setup.
Here are a few things you can do during initial research and vendor evaluation.
Decide what’s important to you
What are your goals for better understanding and improving the passenger experience? What do you need the most help with? Prioritizing different use cases and functions will help you choose the most impactful solution. Create success criteria based on your priorities.
Solidify your timeline
Is there a specific deadline that you need the solution by? Check which technology provider can launch on existing hardware versus those that need to wire & install their custom hardware, taking time and a large CAPEX investment.
Determine your budget bucket
Do you want to leverage existing infrastructure or completely outfit your airport with expensive sensors that require a large CAPEX investment?
Talk to peers that are technology experts NOT just other airports
Buying AI is vastly different from legacy technology solution. You’ll have much valuable tips and experiences from your peers who understand the technology and intricacies behind AI. You can save time by using the pro tip we’ve outlined below.
Start to evaluate technology vendors
Review vendor websites and read through each product page, help documents, and customer stories. You can also check with your solution providers like SITA, Microsoft Azure and AWS which have a vetted and certified list of software that suits your needs.
Stage 2: Understand the key criteria for looking at AI are different from traditional software
Buying AI has some unique difference from procurement of traditional software so we’ve outlined 5 evaluation criteria. Make sure to evaluate vendors using these.
AI learning and training: Essential for ensuring accuracy within the multifaceted airport environment
Airports present a highly complex environment with numerous departments cooperating to ensure seamless operations. The adoption of AI within such a setting requires careful consideration of learning and training capabilities. When selecting a vendor, make sure they are equipped to handle these complexities:
- AI Model Training: The AI system needs to be exposed to a rich variety of high-quality data for model training. This will help the system understand the airport's diverse operations and improve its accuracy over time.
- Human-AI Collaboration Training: Effective interaction between your team and the AI system is paramount. The vendor should offer comprehensive training programs to help your staff understand how to collaborate with AI, interpret results, and provide constructive feedback. This collaborative approach will ensure that the AI becomes a seamless part of your airport operations, driving greater efficiencies.
Customizability: Tailored to support your airport's unique operational needs
Every airport is unique, each with its own specific needs to enhance operations, passenger experience, and revenue generation. That's why the one-size-fits-all approach doesn't work when it comes to AI adoption. Additionally, AI implementation should not compromise your airport's privacy and security standards.
Therefore, two key aspects to consider are:
- Model fine-tuning: The vendor should provide the capability to tweak and adjust AI models to accommodate your airport's unique environment and specific needs. This will ensure that the AI system effectively addresses your particular challenges and enhances overall operations.
- Algorithm transparency: An understanding of the logic behind the AI's decisions is crucial, particularly when those decisions have a direct impact on safety or security matters. The vendor should be able to explain and justify the AI's decision-making processes transparently, ensuring alignment with your airport's operational and security protocols.
Real-world reliability: How will it be setup to avoid disruptions in airport operations
Poorly managed airport operations can result in millions of disrupted passengers, billions of dollars in losses due to missed, delayed, or canceled flights, and significant damage to an airport's reputation. Therefore, it's crucial that the AI solution you implement doesn't contribute to these issues. When evaluating an AI system's reliability, consider:
- Real-world accuracy: AI models can exhibit impressive performance in lab conditions but may underperform in real-world scenarios. It's essential to continuously evaluate the model's performance in the field, under the unique conditions of your airport.
- Redundancy: For applications critical to airport operations, the availability of backup AI models or systems is paramount. Remember that not all vendors provide this kind of assurance, so it's an important point of inquiry when evaluating different AI solutions.
Vendor support: AI is different than just buying a hardware device so it needs continuous visibility monitoring
Regardless of an AI system's capabilities, it will fall short without proper vendor support to ensure ongoing improvement and user-friendly communication about its functionality.
- Model updates: Look for a vendor that provides regular model updates, allowing the AI to adapt to emerging challenges and continually enhance accuracy.
- Explainability: Ensure that the vendor is able to make the AI's decisions clear and comprehensible to non-experts, particularly when it comes to contentious or critical areas. This transparency is crucial in fostering trust and understanding between the AI system and its human users.
User experience: AI is complex, so ensure it's designed to simplify work, not complicate it
AI platforms are designed to simplify your teams' work, not complicate it. It's essential that the platform offers an intuitive, user-friendly experience, especially in the following areas:
- Visualization tools: Look for platforms that offer clear, easily understood visualization tools that allow users to interpret AI or computer vision results with ease.
- Feedback mechanism: The platform should have an accessible feedback system that enables users to flag incorrect AI decisions effortlessly, contributing to the system's ongoing refinement and improvement.
You don't have to do all the heavy lifting in figuring out what AI you'll need. Talk to our AI experts today.
Stage 3: What to do in running an evaluation process to systematically move forward
Now that you have a list of top AI vendors, reach out to the company to get more information about their services. Use the vendor vetting table like below to see how their AI technology can be applied to your business and satisfy your needs. Here are a list of questions ask in each of the evaluation step.
What to ask during a product demo
- Can you demonstrate how the AI model is trained and how it learns over time?
- How user-friendly is the platform, particularly for staff unfamiliar with AI systems?
- Can you demonstrate how AI decisions and reasoning can be interpreted?
- Does your platform have the ability to adapt to our unique needs, such as fine-tuning the model or adjusting the algorithm?
What to ask to understand AI limitations
- How does your AI model perform in real-world scenarios?
- Can you provide a proof-of-concept or a case study demonstrating real-world performance?
- What redundancy measures do you have in place, particularly for critical applications?
- Can the system be deployed on-premise, or is it cloud-based?
How to ensure AI is learning and not just hype marketing?
- Can you explain the AI's decision-making process in layman's terms, especially in contentious or critical areas?
- How often are AI model updates provided to address emerging challenges and improve accuracy?
- What level of technical support and training does your vendor provide?
- How are the AI's decisions and results visualized for non-expert users?
Always ask vendors for a Proof of Value (PoV)
AI platform for airports answers data questions for curb-to-gate passenger experience that were previously impossible with AI. Like any trend that gains attention, some companies can simply use the word “AI” in their copies to hype the technologies they offer.
Discuss the POV process
- Does your platform offer a feedback mechanism for users to flag incorrect AI decisions and refine the system?
- How can we measure the success of the AI implementation in our environment?
- What are the key deliverables during the POV phase?
- What are the success criteria for the POV?
Stage 4: How to get started with the selected AI solution to ensure early success
After you've met with vendors and all your questions have been answered, it's time to choose the right AI solution for your airport. Use the information below to guide your investment decision and ensure the success of your AI implementation.
Move forward by choosing an AI platform with a 30 to 60 day Proof of Value (POV) process
Remember, the aim is to ensure that the AI platform is not only capable but also compatible with your unique operational environment and able to deliver value over the long term. POV is a crucial step in determining this. Additionally, a POV simplifies the buying process. Once you finish a successful POV with 1-2 zones and a single use case like queue management, you can scale it across your terminals, check-in, and security zones without additional onboarding work.
Choose a partner that fits your business goals not just technology
AI platforms should be able to support your needs today and in the future. Have agreed upon business outcome(s) in mind; ensure you and your technology vendor of choice are working towards the same goal.
Pick an expert partner and let them do the heavy lifting
Choosing an AI expert partner streamlines the deployment process, saving time and effort. An expert guides you through implementation, provides customized solutions, anticipates common challenges, and offers ongoing support and updates. This allows your team to concentrate on strategic tasks while the AI deployment is expertly handled.
Review the Statement of Work together
Make sure there is a clear onboarding timeline and success criteria. Onboarding timeline should only take a few weeks, not months. Define what mutual success looks like as quantifiable goals so when the POV concludes everyone is well aware whether or not it will scale to the rest of the business.
Use a shared project management system to capture blockers
Opt for a shared project management system over scattered emails for more efficient and organized communication. This approach centralizes all action items, discussions, and resources, promoting transparency and ensuring no detail gets overlooked.
Download this template to get started in your AI journey
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