Generative AI has the potential to add jet fuel to the airline business engine. It's beginning to have a monumental impact as it starts to reshape processes, drive new growth opportunities, and introduce cost optimizations. As covered in the first two parts of our airlines blog series, many of the investments made so far in this regard affect front- and mid-office processes that directly impact the customer experience, including order, purchase, and service delivery.
However, these aren't the only areas where generative AI can help streamline and redesign airline operations for greater efficiency.
Generative AI also stands to have a transformative impact on what are traditionally defined as back-office processes, such as settlement and shared services management. This third blog will look at the impact of this technology on back-office functions and how it can drive significant cost savings.
Not Settling on Settling
Payments is a well-recognized pain point for airlines. In fact, as highlighted by the IATA, it has long been considered a back-office cost center. In part, this is because airlines have to deal with a sprawling network of players, but also because local regulations in different markets add an extra layer of complexity. And, as is often the case, more complexity means more cost.
Settling payments is a highly data intensive function. Huge volumes of information are generated which must be analyzed to discover discrepancies and trends that can inform future business decisions. By integrating with internal payments systems to digest transaction data and make this information accessible for settlement teams in an intuitive way, generative AI can provide a range of benefits that reduce the complexity airlines face.
Rather than spending time wading through different systems and data stores to track cash flow and measure performance against KPIs, settlement teams can use generative AI to quickly find the information they need. In turn, this can transform the impact of internal business process dashboards.
Internal dashboards, which are critical to business success but can often become clunky and difficult to navigate due to data overload, can be augmented with generative AI. By allowing teams to uncover information they need through natural language questions, the operational queries of airline executives can be answered immediately, with those answers turned into charts and reports on the fly.
Transforming the Finance Department
As we move deeper into the finance department, the value of generative AI for creating cost savings through efficiency becomes clearer. By linking generative AI to finance systems and data warehouses, this technology can help streamline finance processes and auditing functions for airlines, allowing the human in the loop to focus on higher value tasks.
Some of the tasks that can be transformed and supported through generative AI include:
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Accounting. Generating financial statements, including balance sheets, income statements, and cash flow statements, based on airline financial data.
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Reporting. Interpreting data and generating reports.
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Cash Flow forecasting. Analyzing historical cash flow data, accounts receivable, and accounts payable information to provide cash flow forecasts.
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Financial insights. Analyzing broad data sets, identifying trends, and providing actionable insights.
Streamlining access to key information using generative AI can also help bring clarity to back-office teams. Especially as research suggests 47% of knowledge workers struggle to find the information they need to perform their role, and that the volume of data they have to manually deal with clouds their judgment.
Automating Regulatory Compliance
Another area where generative AI technology can be applied to drive greater efficiency – while also helping airlines avoid fines – is compliance.
The airline industry operates in a highly regulated environment. It must comply with a range of complex regulations and standards across multiple territories, and the consequences of non-compliance are significant. By analyzing regulatory documents and requirements, generative AI can quickly create activity summaries, operational checklists, and compliance reports.
Again, this takes the administrative burden away from the human in the loop. It allows them to concentrate on high value activities, such as ensuring adherence to industry standards and minimizing the risk of regulatory violations.
Allowing MRO to Take Off
A third back-office area where AI can have a significant impact is asset management – particularly maintenance, repair, and overhaul (MRO) – which is arguably one of the biggest cost areas for airlines. This becomes especially important in light of current supply chain issues.
Here, generative AI can help with:
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Predictive maintenance. Generative AI can analyze data from aircraft sensors, maintenance records, and flight reports to predict future repairs. This can help teams proactively schedule maintenance activities to avoid unexpected downtime, thereby reducing operational disruptions and ensuring the reliability and safety of aircraft.
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Inventory management. Effective management of spare parts inventory is critical for MRO operations. Generative AI can mine historical data to assist in managing inventory levels, thereby reducing surplus and associated costs.
Conclusion
Through this series, we have shown how generative AI has applications across all business functions. This is true for businesses in any sector, but particularly for airlines where the benefits of generative AI run deep. By introducing this technology across the board, airlines will be able to discover the full transformative effect it holds.
Get in touch if you're planning your generative AI journey. We're here to help your business soar to new heights.
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