How Zhipster Works with AI
Surely no one has missed that AI is on the wallpaper right now. It is undeniably exciting and it has already revolutionized several industries. But what does it look like for the logistics industry? And are we working on Zhipster anything with AI? Below, our numbers star, statistics hero and data analyst Janne Häggström answers questions about AI.
Janne, how has AI changed the industry?
In my opinion, AI has already had a significant impact on the logistics industry by, among other things, optimizing route planning, forecasting demand and improving vehicle maintenance. In addition, automation and machine learning help increase efficiency and reduce costs by optimizing various processes.
Going forward, I believe AI will continue to optimize the logistics industry by offering advanced analytics tools, improving real-time monitoring, and enabling driverless vehicles. In addition, predictive analytics can be used to minimize delays and optimize the entire logistics chain. This will mean safer and cleaner transport.
How will Zhipster work with AI in the future?
Zhipster is already working with AI within the company today. Partly to speed up the work, and partly to minimize repetitive tasks that need to be done. I myself use ChatGPT in my work to find smart future areas where we can use machine learning to give our customers business benefits from their data. I also see that we can use machine learning to offer our customers smart solutions.
What are the biggest benefits of AI in our industry, do you think?
AI will in the long run improve and optimise routes, which will mean less transport, which is of course good for both the economy and the environment. It will also be easier to know how many trucks are needed in each depot. I believe AI will help us tackle complex logistics challenges with greater accuracy and speed.
How should I, as a customer, think about data collection?
Something important about data collection is to not only collect it, but to use what you collect. It is therefore important to have a clear plan with which data is collected, and why. At a later stage, the data should also be structured according to the plan.
One tip is to find someone who is passionate about data and data collection, who can help ensure data quality, structure and usage. Today, Zhipster is actively working on quality assurance, structuring and planning data so that we can use it to provide our customers with business benefits in our Transport Managment System (TMS).
As a customer, can I already prepare my organization to work more with AI?
I think it's important to have a process for how AI should be used in the organization. An exercise can be to ask the questions: what do we use A.I to and how? It is also important to keep track of new laws and regulations being discussed. One thing to follow is the new AI regulation that is underway in the EU. I also believe that AI should be used to solve problems, then if you don't have a problem that AI is supposed to solve, you don't really have any benefit from it.
