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~ Spring GDS ~

and carbon emissions, making logistics operations more . The challenges of AI
sustainable. While AI offers many advantages and new
3opportunities, it also presents limitations and
Forecasting and optimisation of routes challenges that need to be addressed.
AI tools can forecast demand and traffic spikes based on
historical data, seasonal trends, and weather conditions. For retailers and logistics carriers
Thanks to technology, carriers can adjust their routes The customisation of products and user experience fully
according to traffic conditions and unforeseen events. This managed by AI can lead to homogenisation, limiting the
allows drivers to dodge traffic, reduce fuel costs, and avoid offer and the discovery of other products/solutions for
delays. customers and retailers. It would be beneficial to feed and
set up AI tools with different strategies. Also, as AI can
Customer relationship management analyse historical data and market trends to recommend
Just like for retailers, AI can optimise customer support products and adjust pricing, if all the companies use
and relationship management for logistics carriers by AI-driven tools, none of them will have a competitive
analysing feedback, contact frequency, and satisfaction rates advantage over the others. Besides, the massive collection
to identify the risk of customer loss. This enables logistics of data raises ethical and equitable concerns. For example,
carriers to focus and improve specific steps in their applying higher or lower pricing based on customers’
supply chain and customer lifecycle to prevent negative purchases might mean that a person/company A can pay
experiences. more or less for the same product than a person/company
B depending on their financial means. Hence dynamic
pricing can create a sense of inequality and decrease
customers and retailers’ trust.

AI AT SPRING GDS - POSTNL For the environment
Spring GDS - PostNL is a logistics company that is always striving to be The development of AI models requires a considerable
up to date and innovate. So jumping on the AI revolution to seize all the amount of energy. Training an advanced AI model can
opportunities it has to offer was obvious. Jeroen Verboom, Product Owner generate over 500 tons of CO2, equivalent to the annual
and AI Lead, explains how Spring GDS - PostNL is positioning itself on the emissions of 100 cars (MIT Technology Review). The
topic. demand for energy in data centers is expected to double
by 2027 (Bain & Company). Artificial intelligence thus
“We are employing AI in our Customer Service (CS) domain (both contributes directly to greenhouse gas emissions.
domestically via an upgraded chatbot and internationally across many
Spring GDS countries and PostNL International) to assist customer service Data centers also require large quantities of water to cool
agents in swiftly processing item-status inquiries from our partners. servers. Microsoft, Google and Amazon have announced
Feedback from CS teams has been positive, and we are now performing the an increase of almost 30% in their water consumption,
final tests. equivalent to 14 billion liters per year. In view of these
figures, it seems essential to implement strategies and
We use logistical systems (XBS and Tracy), CRM systems (Creatio and regulations to limit the environmental impact of AI.
Salesforce), and custom knowledge from the teams to generate a suggested
output for the agent in just a few seconds, keeping the human in the loop. Conclusion
Artificial intelligence can profoundly transform
More than 300 colleagues at Spring GDS and PostNL have completed basic e-commerce and logistics by offering exceptional
AI prompt training, learning how to leverage AI tools like ChatGPT, Microsoft opportunities to optimise performance. However, this
Copilot, and PostNL’s internal chat in their daily work… and still counting! progress comes with economic, social, and environmental
challenges. Companies need to adopt a balanced approach
We are actively working on applying AI to accelerate our sales and in order to integrate AI effectively, ethically, and
marketing efforts at Spring GDS. Moreover, we use AI in our supply chain sustainably. While AI offers a multitude of advantages in
to generate forecasts across thousands of time series and predict missing performing both operational and strategic tasks, human
HS codes based on content descriptions, preventing parcels from being supervision remains essential. All this leads to an inevitable
bounced by customs. transformation of the world of work. It is crucial for
Finally, we use smart mathematical algorithms to tackle complex network companies and employees to adapt to this transformation
challenges with too many variables for a human to compute. For example, as soon as possible. Education and training are needed to
optimising linehaul network configurations for various volume scenarios maximise the benefits of AI and limit its negative effects.
or finding the best last-mile partner combination based on our volumes, ••
weight splits, and rates.”

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