The container concept has turned routing and scheduling into predictable corporate levers
The global shipping sector cannot wait for regulators to agree on emissions frameworks. Instead, vessels crossing the oceans today are using data and AI to prepare for the future, asserts Nayef Bou Chaaya, VP, Middle East, Turkey & Central Asia, AVEVA.
When the SS Ideal X set sail for the Port of Houston, Texas from the Newark, New Jersey on April 26, 1956, the converted wartime oil carrier also shaped the course of history. The intermodal containers pioneer Malcolm McLean introduced on that ship have since become an anchor of the global economy, carrying nearly half of all trading volumes 70 years later.
The container concept turned routing and scheduling into predictable corporate levers that every entity along the value chain—ports, carriers, trucking firms—could measure, schedule and optimize around.
Today’s maritime sector faces a similar problem. Nearly everyone agrees that ships—which account for 3% of global greenhouse gas emissions and impact the oceans’ fragile ecosystems—must decarbonize. But the rulebooks don’t match.
The EU’s Emissions Trading System (EU ETS) this year requires surrendering allowances for 70% of reported emissions (on 2025 emissions), with the figure rising to cover all output by 2027. Likewise, the bloc’s methane reporting guidelines are already available. Delays to the upcoming IMO Net-Zero Framework—a decision on which has been pushed to the end of this year—will strengthen the financial impact of regimes such as the EU ETS.
Meanwhile, conversations about similar frameworks are happening in California, Singapore and elsewhere. Industry-wide rules may currently be ambiguous, but emissions accounting is a matter of when, not if.
The uncertainty creates space for operators to prepare for future changes and model potential operational shifts. For marine operators, it’s an opportunity to strengthen current asset and energy management systems with verified emissions metrics. Shipping can’t wait for industry consensus. It needs vessels that fit into multiple systems simultaneously.
Creating an operational intelligence layer
Can maritime operators turn regulatory uncertainty to their advantage? They can and they are—using digital technologies such as the internet of things (IoT), real-time data infrastructures and artificial intelligence (AI). Together these technologies create an intelligence layer that puts the wind in their sales.
As Yinson knows, the path to cleaner operations lies in streamlining data management. The 1984-established Malaysian global floating production, storage and offtake vessel manufacturer wants to cut emissions by 30% over the next five years and achieve net-zero operations by 2050. With a large asset portfolio spread across the globe and multidisciplinary projects with varying timelines, Yinson deployed an asset information management platform to centralize engineering and operational data from different sources into one unified, searchable system, so teams can access accurate, real-time information more easily.
Simply put, operational intelligence supports more efficient operations. This sets the stage for connected ecosystems, where real-time data and vessel metrics are shared up and down the marine value chain. So far, digital systems have largely been siloed, leading to inefficiencies, rework and waste.
Connecting ships for scalability
Instead, as Zamil Marine discovered, pulling together asset data from its entire fleet into a single-window interface, called a unified control centre, lets operators see all their vessels a glance or drill down to ship specifics as required.
At any given moment, teams can view network-wide performance or zoom in on individual problems. In addition, proactive AI-infused insights provide advance warnings of asset health, minimizing breakdowns and promoting system uptime.
Similarly, the CSL Group has leveraged its digital investments for higher reliability, safety and continuous operational improvement. That has put them ahead of their Net-Zero targets, with a 29% reduction in carbon intensity thus far, as data optimizes speed and operations across its fleet.
Connected ecosystems enable these gains to be compounded. For example, when one vessel in a fleet optimizes fuel consumption through ballast adjustment or trim modification, the improvement should propagate to sister ships immediately. When maintenance reveals component wear patterns, the data should inform both operating vessels and new construction.
With the upcoming IMO Net-Zero Framework potentially leading to lost margins, such connected ecosystems will be essential to keeping maritime businesses on a steady keel.
Companies that unify their data flows will retrofit faster and cheaper than competitors still using outdated digital systems, email chains and spreadsheets. And when audits are needed, having every document searchable and every approval tracked speeds up compliance.
Unified data streams also enable stronger AI use cases. After years of small-scale testing, AI applications have now moved from concept to co-pilot and will soon drive the next era of maritime competitiveness. Companies now have enough data and use cases to drive a new generation of advanced AI technologies, including generative AI, agentic AI and real-time analytics.
Expect to see autonomous AI agents become operational, helping avoid collisions and scheduling port calls. We see task-specific AI agents as catalysts for safer and more sustainable operations, empowering shipyards and operators to optimize compliance and operations.
Making crews count
AI will also step into the breach when it comes to labour gaps, enabling maritime operators to do more with less. The industry needs more than 89,000 additional officers, but the gap isn’t being filled, not least because of the impact of geopolitical events.
Here, AI applications will serve as a force multiplier for overstretched crews and yard workers, giving them superhuman-like skills. This means AI will handle compliance documentation, automate retrofit planning and manage data handovers between design, build and operations.
Rather than replacing workers, IoT and AI—together with other knowledge management technologies—will be an enabler that supports skilled professionals in meeting growing industry complexity while creating safer and more resilient operations.
One Italian logistics company fed real-time operational data into an immersive training solution that simulated specific operating scenarios.
With navy rotations requiring crews to change every year, workers were able to get the training they needed as they set foot onto a ship. Such a solution means crew can operate vessels from day one. The next step could be extending such a program to cover emissions reduction and mitigation.
Operations data as a success unit
With shrinking crews and expanding regulatory requirements, the business case for data-driven digital systems becomes stronger. In McLean’s day, containers became a repeatable unit that logistics could optimize.
Now, the repeatable unit is data: Voyage plans linked to sensor streams or decision logs that survive audit and can be queried against multiple rule sets. Software that helps operators convert decisions into continuous improvement and defensible evidence will determine who sails comfortably through the upcoming compliance gauntlets and who faces penalties or operational delays.
