Discover the untapped potential and key considerations of
deploying generative AI in the thriving Swedish manufacturing industry.
Deep dive into Triathlon's research which has summarized the advantages of,
as well as the risks associated with, this groundbreaking technology.
Through interviews with industry leaders, the report uncovers notable results
on the utilization and governance of generative AI. Explore the findings that
highlight the benefits of leveraging these innovative tools, while emphasizing
the critical importance of responsible and mindful implementation. After
reading this report, you will gain insight into the present-day landscape, the
vast potential of generative AI adoption, its accompanying risks and
actionable steps to ensure your organization is well-prepared for its
transformative impact.

Emerging and disruptive technologies such as AI, Cloud Computing, Big Data Analytics, and Autonomous Vehicles have unlocked untapped potential for Transportation Management Systems (TMS), creating new opportunities to reshape the transport industry. This article elaborates on the enablers and features of next-generation TMS, enhancements compared to traditional TMS, how to succeed in implementing next-generation TMS, and future trends.

Enablers and features of next-generation TMS
TMS are logistics platforms streamlining processes of goods movement by connecting various data flows being analyzed and validated to make strategic and tactical changes. The immense increase of computing power and disruptive technology have enabled next-generation TMS to become remarkably fast and accurate compared to traditional TMS.  Key enablers and features commonly associated with next-generation TMS are:

• Artificial Intelligence and Machine Learning – automating tasks by utilizing predictive analytics and dynamic routing
• Cloud Computing – offering the necessary infrastructure and scalability to enable real-time tracking and data sharing
• Big Data Analytics – processing GPS and telematics data to enhance route optimization and predictive maintenance
• Autonomous vehicles – optimizing transport by integrating and leveraging above listed enablers to improve resource utilization, minimizing downtime and delays