Predictive maintenance is one of the best examples and applications of AI in the last-mile delivery sector . Utilizing performance data from telematics gives you the ability to see the maintenance needs of your fleet vehicles . This allows you to plan for preventative maintenance to keep vehicles mechanically safe and efficient . But what happens when the maintenance timeline doesn ’ t jive with the operational timeline ? What happens when we can ’ t afford to pull a truck off the road this week to maintain it because we can ’ t get a replacement vehicle from the leasing company ? You can imagine your increased risk and liability in this delayed maintenance scenario . Should you have a claim or incident , and the data is called into question , it will be difficult to argue why you aren ’ t liable when AI tells you that the vehicle needs maintenance . When adopting predictive maintenance tools , be prepared to follow through on maintenance recommendations or risk paying the price in the courtroom .
As a consumer , the AI tools powering communication and transparent delivery expectations are my favorite . Automated updates and projections of when items will be delivered enhance the buying experience . As AI communication grows , delivery expectations could increase risk . Take , for instance , lab work , medical specimens , or critical care medicine / equipment . The healthcare industry expects that , based on communication and timelines , items will be delivered within a set time . What happens if that timeline cannot be kept , and a life hangs in the balance ? While contractual liability with your customer is important , it will not keep the deceased ’ s family or estate from suing you if your delivery does not make it in time despite what was communicated . It isn ’ t that you mismanaged the AI , but the AI has set an expectation that must now be met . I ’ m not suggesting that you completely disregard safety to hit established delivery timelines . Still , it is important to recognize that either way , you are potentially increasing your liability exposure while attempting to provide a more positive customer service experience for your clients .
There is no arguing that the growth and application of AI in the last-mile delivery sector can help to improve many facets of your operation . However , we also must realize that the human factor still looms large in all organizations . The actions or inaction of the people in your organization , including you , will determine whether AI is successful in enhancing your operation and reducing risk or making it riskier . CLDA
Brian Jungeberg is Vice President at Risk Strategies , a specialty national brokerage and risk management firm with a dedicated team servicing the customized delivery & logistics industry . He has specialized in insurance and risk management products for the customized delivery and logistics industry his entire career . For more information , go to risk-strategies . com .
“ There is no arguing that the growth and application of AI in the last-mile delivery sector can help to improve many facets of your operation .”
winter 2024 I customized logistics & delivery Magazine 29