Since ChatGPT rocketed to the mainstream in late 2022, AI has jumped into public focus. But there’s more to AI than large language models like ChatGPT and Google’s Gemini.
Several weeks ago I attended the Manifest conference in Vegas (a conference focused on innovation in the world of supply chain and logistics). A mix of startups and solution providers, venture capital firms, and supply chain industry professionals, I had many fascinating conversations and walked away reflecting on the growing role of AI in the world of shipping.
While AI is posed to shape the future of shipping, the truth is, AI is already in use.
Autonomous navigation, route optimisation, collision avoidance, and predictive maintenance (to name just a few) are all being helped by AI solutions, and although adoption isn’t yet widespread, the trend is clear.
With around 25 million containers in circulation, 100,000 cargo ships on the seas, and an increasingly digital shipping industry, AI is set to reshape the shipping industry.
It’s not the data, it’s how you use it
As shipping becomes more digital, the volume of data will become enormous.
At a small scale, humans can process and interpret data reasonably well. But as that scale increases, so does the complexity, difficulty and chance of error. A well-programmed AI model, on the other hand, can transform staggering volumes of data into actionable insights to enable better decisions.
And it’s already doing so.
Predictive models are being used to optimize vessel maintenance schedules, combining real-time ship sensor data (of temperature, vibration, pressure etc) with other sources to allow the models to better predict trends and identify possible issues before they happen.
Ports use similar types of models to predict arrival times, reduce port congestion, optimize berthing schedules and improve operational efficiency and container flow.
Many vessels are also now equipped with situational awareness tools, processing data from cameras, GPS, G-force sensors, radar, and laser for collision avoidance and enhanced safety. As well as solutions for route optimisation, improved fuel efficiency and overall fleet management.
The next phase of AI in shipping
If that’s what’s already happening, what can the shipping industry expect in the future?
The potential is really only limited by the availability of good data (putting aside adoption, regulatory and other challenges for the moment).
When the data is available, AI can be put to use to help us make the most of it, and that amount of data is always increasing.
The industry also has smart containers equipped with sensors tracking location, temperature, humidity, and container access, location data from ships, port capacity, data from land transportation networks; the potential gains in visibility, efficiency and effectiveness within all this data is profound.
Also, just as how AI is being used to personalize the customer experience in other industries, we can anticipate it could be used in shipping to provide tailored recommendations based on a customer’s purchases, preferences and behaviors. For simple enquiries, AI driven chatbots and assistants could provide fast answers to common questions and even assist with the ordering process. However, it will be important to ensure the personal touch remains at the forefront and isn’t replaced in the name of efficiency.
Another application of AI could even be specialized natural language models in the style of ChatGPT trained on specific and relevant data sets. Rather than having to roll out and train an entire workforce on new software, one could imagine a natural language interface to access all kinds of data.
But, of course, achieving these kinds of outcomes isn’t always so simple.
Foundations first
The reality is, as it stands, shipping is still in the infancy of its digitalisation journey. While there is some deployment of AI tools, quality, standardized, and available data is still not commonplace. Quality data is the foundation. Without it, AI can have little impact.
So, while the potential is exciting, we must put the foundations in place first. What I will say however, is that thinking about the opportunities is good motivation to speed up digital adoption. Let’s get the basics right then move on to the fun stuff!
As always, I want to know what you think. What are you most excited about with AI in shipping? What are some other use cases you can think of?