While the digital age is well underway in many areas of business aviation, a crucial element of aircraft ownership lags behind – financial management. The industry status quo sees aircraft owners wading through piles of delayed, opaque invoices subject to clerical errors and overcharging. Similarly, procuring a quote for a particular flight can take up to several hours and often lacks accuracy due to the use of flat rates and averages, rarely taking into account degrees of pricing that differs depending on location or departure and arrival times. For many private jet providers, these quote requests can climb to more than 1,000 per day, leading to a lack of capacity for ensuring accurate evaluations.
However, with the latest technology, including AI in Business solutions, the industry’s capability is changing. Using AI solutions for cost comparison, owners and operators can not only maximise value on their aircraft but increase their ROI on every flight. By digitalising transactions, machine learning algorithms can be used to catch invoice errors and offer predictive cost insights. In a wider sense, employing these technological tools can play a fundamental role in establishing greater transparency in the industry for both buying and maintaining aircraft and enabling cost-efficient flight planning for private jet owners and operators. This enhanced clarity brings more value, particularly for new entrants to the market and operators experiencing high demand since the onset of the Covid-19 pandemic.
Going digital: how does it all work?
The primary ways in which AI can be applied to the financial management of aircraft are threefold: invoice processing, invoice analysis and cost prediction. The first step is the use of specialised algorithms to read each character in an invoice and translate them into a digital format. A separate algorithm then matches the invoice to its corresponding flight, itemising each charge into its categorised cost code used to standardise each type of charge – ramp fees or fuel, for example. With every invoice it processes, the algorithm learns what to expect from specific business aviation vendors in terms of anticipating costs and knowing where to pay invoices.
AI as the instant analyst
Once invoices are processed into a digital format, AI can also be used to compile data from an exponential number of invoices and business aviation service sites. By comparing this data, AI algorithms can identify a common benchmark for pricing and value in an otherwise unstandardised business landscape. The algorithms designed to calculate and predict this information are highly sophisticated, having to account for a multitude of factors including type of aircraft, country of registration, airport location, and arrival or departure time. For example, as some airports do not use set hours to determine their day and night fees, algorithms linked to sunset calendars worldwide can provide the most up-to-date costs.
Using this database of cost information from all over the world, AI can be leveraged to build a sample invoice for a specific flight, predicting the costs for each leg and recommending the best-valued route. A process that has traditionally taken anywhere between four to six hours to achieve accurately is now possible in under 10 seconds.
What this means for aircraft owners
The difference owners will see in adopting AI solutions to manage their aircraft operations is staggering. Having the ability to segment all invoices down to a single fuel charge on one leg of a flight provides owners with a level of clarity and oversight of the financial management of their aircraft that has previously been difficult to achieve. With worldwide access to aviation service pricing data, AI software provides a tailored benchmark that allows owners to evaluate whether they are getting the best value on their aircraft. The analytical function of this benchmarking means owners will receive recommended strategies for cost-efficiency to find the best ways to manage and plan for their assets.
What this means for private jet fleet operators
While larger fleet operators have benefitted from the post-Covid wave of demand for business aviation travel, handling this has been taxing for many, placing strain on staff and resources. By incorporating AI solutions into financial planning and invoicing, operators are equipped with enhanced accuracy and speed for providing flight quotes, while also having access to pricing data that can help make their own pricing strategy more competitive. In this vein, fleet operations can take on the growing number of new clients the industry is seeing, by gaining a higher performance capability without the need to expand resources for additional staff.
Transparency for the industry
In an exciting field that has long been held back by the analogue processes of its financial side, machine learning brings business aviation into a new era of transparency through technology. By condensing data into clear and actionable information, AI protects aircraft owners and operators from invoice overcharging and price gauging because they’re provided with the tools to understand the costs they care about most. Pricing comparison on a global scale means flight planning selections are made on an even playing field with maximum visibility of options, placing more power into the hands of those whom the aircraft affects most. In this sense, the rise of AI in business aviation management is not just a technological shift in the industry, but also a more meaningful and valuable one for aircraft owners and operators.
