Artificial intelligence and aviation in Africa

With many debates ongoing about artificial intelligence, including the challenge of regulation, artificial intelligence (AI) is finally starting to deliver real-life benefits to early-adopting companies, say experts. Retailers on the digital frontier rely on AI-powered robots to run their warehouses — and even to automatically order stock when inventory runs low. Utilities use AI to forecast electricity demand. Automakers harness the technology in self-driving cars. 

Artificial intelligence (AI) is transforming the aviation industry in various ways, enhancing passenger experience and improving operational efficiency. For instance, AI-powered chatbots assist passengers with booking, check-in, and flight updates, providing personalised support. Predictive maintenance driven by AI optimises aircraft maintenance, reducing delays and cancellations. Leveraging on passenger preferences, AI curates content recommendations. With AI, traffic management is enhanced, optimising flight routes and reducing congestion. AI-powered facial recognition expedites security and boarding processes, so passenger experience is positively enhanced. For ground operations, AI streamlines ground handling, baggage handling, and cargo management.

Though there have been arguments around the dynamic pricing model in Africa, AI optimises pricing and revenue management, enhancing yield and passenger experience. Also for crew management and scheduling, AI comes in handy as it optimises crew scheduling, reducing fatigue and improving crew satisfaction. A satisfied crew will go a long way in ensuring that passengers are well taken care of on board.

It is good business when AI analyses data to optimise flight routes, reducing fuel consumption and emissions. And, with respect to Passenger Analytics and Insights; AI provides actionable insights on passenger behaviour and preferences. AI plays a crucial role in aviation fraud detection, minimising risks associated with fraudulent activities. By analysing extensive transaction data, AI algorithms swiftly pinpoint suspicious patterns and highlight potential fraud. 

The coming together of many factors is driving this new wave of AI development. Computer power is growing, algorithms and AI models are becoming more sophisticated, and, who knows, experts think – most important of all, the world is generating once-unimaginable volumes of the fuel that powers AI — data. Billions of gigabytes every day are collected by networked devices ranging from web browsers to turbine sensors.

The future of AI will be innovative but may not be shared equally, experts believe. China and the United States have grown AI “ecosystems” — clusters of entrepreneurs, financiers, and AI users — and have issued national strategic plans in the past 18 months with significant AI dimensions, in some cases backed up by billions of dollars of AI-funding initiatives. South Korea and the United Kingdom have issued similar strategic plans.

Artificial intelligence (AI) is obviously set to play a role in all aviation domains. Introducing such technology will be a platform for advanced assistance to aviation professionals and process optimisation in ways otherwise not possible, allowing for an even safer and more sustainable aviation sector.

Three types of risks have been identified with AI. AI-powered software that, say, interprets medical images, may not be perfectly accurate. Large language models (LLMs), which power “generative AI” services such as ChatGPT, may display prejudice or bias. And some fear that the most powerful “frontier models” could be used to create pathogens or cyber-weapons and might lead to superhuman “artificial general intelligence” that could even threaten humanity’s survival. These risks are obviously to be considered while discussion is ongoing about artificial intelligence. 

There are also hurdles that need to be crossed while adopting AI.  Integrating AI into aviation systems is not straightforward, there are technical challenges to be overcome. Ensuring it works well with different hardware and software across various aircraft models and manufacturers can be difficult. This will need to be considered.

Considering ethical issues is also important. Determining the extent of autonomy for AI decision-making, especially in critical situations, triggers ethical questions that need careful consideration.

Artificial intelligence and its adoption is not an overnight switch. AI needs a skilled team for development, maintenance, and operation. Bridging the skills gap by training aviation professionals is a big task. And the shift to AI might worry some about job security. Paying attention to these concerns and offering retraining options is crucial for a smooth transition.

The aviation industry has strict rules and introducing AI means playing by those rules. Adapting regulations to tackle the new challenges posed by AI in the aviation industry can be demanding. Experts say that national laws might be able to deal with simpler AI applications and LLMs, but frontier models may require global rules — and an international body to oversee them.

For aviation in Africa to become significant players in AI, the continent would be wise to emulate these leaders in AI. In the opinion of experts, significant gains are there for the taking. For aviation in Africa, this means accelerating the digital-transformation journey. The belief that aviation in Africa must also think through is that AI is not going to allow companies, and indeed airports and the aviation industry to leapfrog getting the digital basics right. They will have to get the right digital assets and skills in place to be able to effectively deploy AI.

business a.m. commits to publishing a diversity of views, opinions and comments. It, therefore, welcomes your reaction to this and any of our articles via email: comment@businessamlive.com