Cost-efficient AI is changing airport operations without the traditional Hefty Data Project Price Tag
AI is changing everything about physical operations, just as the steam engine, electricity, and the internet did when they first emerged. Those who fail to adopt AI will inevitably fall behind those who recognise its potential and leverage it to their advantage.
People and businesses around the world are already leveraging AI to enhance operations and productivity. They all see that AI is not inherently expensive and first steps can be quickly taken to show the value and ROI. Another big advantage for AI is that existing infrastructure and data can be used - meaning existing CCTV cameras and sensors with various technologies can easily be integrated and combined with structured and unstructured data.
💡 Microsoft found that “for every $1 a company invests in AI, it realises an average return of $3.5X, while the leading 5% of organisations realise $8X.”
Professionals and companies delaying implementation of AI solutions will lose competitiveness to those deploying AI and realise business values faster.
Foundation AI models are evolving to augment every human role
Answering strategic questions like “How efficient are our operations at delivering an amazing customer experience and where could we improve further?” requires IT departments to procure dozens of different solutions, each capturing a part of the business process only.
AI technology has advanced to the point where a single AI model can replace or enhance many different solutions collecting data and making sense of them - all without lengthy and costly data mapping projects.
🚀Within weeks, AI will produce holistic operational insights. Business leaders will have a live snapshot of an entire business process on one screen, for example, the customer journey.
AI does not need to be blocked by typical budget cycles?
Many enterprise leaders who recognize the importance of fast AI adoption are blocked by budget constraints. Budgets set at the end of each fiscal year typically only include known expenses, often excluding or limiting new and emerging technologies like AI and its rapid breakthroughs.
Waiting years for the budget to become available for adopting AI is not an option, as the cost of delay is huge:
- Staying behind in a business environment which is becoming vastly more agile and missing out on the previous stated 3.5X to 8X returns using AI technology.
- Missing the opportunity to optimize operations, reduce cost and increase passenger experience - which in turn positively influences non-aeronautical revenues.
- Competing with AIs that are years ahead due to the vast data, experience, and improvements they've gained over time.
- Good CIO’s are realising that AI is too critical for just not having a budget and it’s important that they also find discretionary budgets or budgets from traditional IT projects and assign them to AI initiatives.
⚠️With the 2025 budget season right around the corner, it’s essential for leaders to secure the budget to stay competitive and relevant. ✅
Measuring ROI in terms of human capital gains
Establishing a separate budget category for AI not only facilitates procurement but also aids in calculating the return on AI investment. There are three components you should consider:
- AI can often make staff rostering more efficient and staff work more productive which can be easily measured with the amount of passengers processing per man hour invested.
- Cost savings from replacing multiple legacy providers with a single AI solution.
- The new business value created by having AI’s holistic insights compared to the individual pieces of data it replaces.
If your budget season is already over, you can still utilize the budgets set for legacy solutions and software to procure AI. It’s always recommended to start small and scale once you’ve verified the significant value of AI. This means using the budget set for a single use case or legacy solution initially, and expanding to other items that AI can handle.
AI budgeting and deployment should be iterative
AI is not inherently expensive.
AI has been proven in many industries and is fast evolving. It has become mature and is easily deployable. There is no need to do a big bang deployment which may require a large budget allocation - this is unlike data warehouse and data mapping projects. The initial step in implementing a comprehensive AI strategy involves integrating your existing sensor infrastructure, applications and data sources. Often, starting with proof-of-value implementations can be achieved at relatively low cost, typically within the 5-digit range. Given this affordability and the substantial benefits AI technology offers, demonstrating a rapid ROI becomes straightforward and achievable. Key operational challenges like airport security, immigration, aircraft turnaround, curbside vehicles, and more are a natural first step in this process. So what are you waiting for? This is the most cost effective way of heavily reducing budget risks compared to large scale interdependent data projects.
During your first phase of AI deployment which can be done in days, you should look for:
- How quickly AI adapts to your unique business environment to capture data accurately.
- Whether the AI is meeting its performance KPIs in the real-world environment, not just in the lab.
- Whether the data and insights the AI produces are relevant to your business.
Starting small doesn’t mean testing waters, but laying the groundwork for a system capable of growing with your needs. 90% of enterprise data initiatives fail to start small and end up investing in unsuccessful projects.
Remember, AI deployments don’t come with large CAPEX investments that need to be depreciated over many years. The majority of the AI cost are OPEX cost which allows for flexibility in quickly adjusting the spend in areas which show a bigger ROI.
Are you ready to go for an Airport AI solution to experience the ROI and operational benefits?
- Option 1: Initial AI Proof of Value (PoV) projects can be set up in an efficient way starting in the 5-digit Dollar range as a perfect fit for discretionary innovation budgets.
- Option 2: If you struggle with the expansion of an existing point solution, then allocate some of the budget to see how AI can help you in a more cost efficient way.
Avoid budget overspend on legacy point AI solutions
Deciding on the appropriate budget for AI can be daunting, especially for companies taking their initial steps into this technological arena. Fortunately, a larger budget isn't a prerequisite for success in AI deployment. In fact, hefty investments can introduce unnecessary risks and may slow down the deployment process and the rate of end-user adoption.
To give you an idea of current investment trends, Omdia's survey of 369 companies revealed the following for AI budgets in 2023 consistent across companies of various sizes, regions, verticals, and industries:
- 42% allocated $1 million or more.
- 23% allocated $2 million or more.
- 9% allocated $5 million or more.
Companies with established AI applications, in particular, were observed to invest more substantially, indicating that businesses increase their AI budgets after validating the business value for the technology.
With AI technologies becoming more advanced and accessible, significant achievements are now possible without massive spending. For instance, a budget of $1 million provides a broad scope to experiment with various AI solutions and identify those that deliver tangible benefits to your business. Remember, with the absence of high CAPEX investments, the flexibility to adjust spending into solutions that have been proven to deliver on promises is a given.
When planning your AI budget, focus on strategic impact rather than convenience:
- Avoid the trap of opting for the simplest AI solutions, such as chatbots, merely because they are widespread and straightforward to implement.
- Target AI solutions that are in line with your company's strategic goals and that bolster your competitive advantage.
- Employ a thorough AI buying guide to sift through the marketing noise and choose a solution that genuinely fits your business requirements.
By grasping the scalable nature of AI and starting with targeted, manageable deployments, your AI initiative is more likely to succeed, enhancing operational efficiency and significantly improving your bottom line.
Are you ready for AI at your airport now?
AI solutions are mature and cost effective. Due to the low upfront investments, they can be put in place within weeks which means Fast Value at Reasonable Cost.
Ready to explore more? Zensors AI has over the years invested into training an Airport Foundation AI Model which is ready for a quick deployment at any airport in the world.
Toronto Pearson is capturing accurate queue-level wait time data, even as queue layouts constantly change which was considered impossible before. New Jersey Transit is capturing real-time ridership data as if they had a human data collector in every car, around the clock.
Our experts are ready to show you more and recommend the best approach for getting started in the wider AI world giving you the operational insights for making informed decisions in the airport operations and customer experience improvement programmes.
