Airports Council International (ACI) World has unveiled its “Airport Traffic Forecasts 2024–2053, projecting significant long-term growth in global passenger traffic.” ACI World says “over the next three decades, global passenger numbers are expected to reach 17.7 billion by 2043 and 22.3 billion by 2053, the later nearly 2.4 times the projected volume for 2024.”
According to ACI World, “The new forecasts, which cover 99.8% of global markets across 161 countries, highlight a compound annual growth rate (CAGR) of 3.4% from 2024 to 2043, with a slightly slower CAGR of 3% from 2024 to 2053.” The projections from ACI World indicates “a steady upward trajectory in global aviation, driven by factors such as rising middle-class travel demand in emerging markets, strengthened international travel, and continued investments in airport infrastructure.”
However, short-term challenges include geopolitical tensions, economic instability, trade shifts like reintroduced tariffs, and supply chain bottlenecks, which may slow recovery in some regions.
ACI World Director General Justin Erbacci said: “Despite the challenges in the near term, global air travel is poised for steady, sustained growth. It is crucial for airports, airlines, and policymakers to take bold, forward-thinking action to anticipate and meet the demands of the future. ACI World remains unwavering in its commitment to support its airport members, helping them navigate evolving dynamics and seize opportunities ahead.”
The Airport Traffic Forecasts from ACI World highlights the “Global passenger traffic growth, Domestic vs. international global traffic growth, Growth in emerging markets, Air cargo growth and Aircraft movements”
To help airport planners and investors navigate this evolving landscape, the ACI World Airport Traffic Forecasts 2024–2053 includes granular forecasts for: total passengers (international & domestic), air cargo volumes, and total aircraft movements. The latest report also introduces a new forecasting methodology based on advanced machine learning techniques, ensuring greater accuracy and relevance for long-term data-driven decision-making.
