The past few years have been tough for logistics executives. Supply chain disruptions, excess inventory from the post-COVID boom, and rising inflation have all contributed to what’s been termed the “Freight Recession.” These factors, along with looming recession fears, have made long-term decision-making incredibly challenging. Even though 2024 has seen improvements with increased demand for freight and rail, the market remains below average, according to the Logistics Manager Index.
However, there is a silver lining. As the market begins to show signs of recovery, logistics executives are faced with a crucial question: How can they maintain low-cost structures while preparing their firms to seize opportunities when the market rebounds?
Many logistics companies are using this downturn as an opportunity to invest in AI. This strategic move aims to cut costs in the short term and enhance efficiency and capacity in the long run. This raises an intriguing question: Will the logistics leaders of tomorrow be shaped by the challenges of today’s down-market?
Bringing Processes Back In-House: The AI Advantage
Amid the economic downturn, logistics firms are turning to AI to trim costs and maintain margins. With advancements in AI and NLP-backed technologies, businesses can now automate a broader range of processes without needing large developer teams. Traditionally, many logistics companies outsourced labor-intensive tasks like keying and matching documents such as Bills of Lading, pack slips, and commercial invoices with TMS or ERP systems. However, AI now enables firms to handle these tasks in-house without increasing headcount.
AI systems can receive customer documentation, extract necessary information from even poor-quality documents, create appropriate records in applications, and match or verify this data against other sources. In-house billing teams are flagged to handle specific exceptions and train the AI to manage similar situations in the future.
Bringing these services in-house not only optimizes costs temporarily but also gives logistics firms greater control over process improvements and creates a scalable solution. Unlike outsourcing, where firms must anticipate and pay for additional offshore workers to meet demand, AI systems are serverless and dynamically scalable. They scale on demand as transactions occur, offering executives infinite capacity to handle spikes in demand without overcommitting.
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Hiring and Retaining Top Talent: The AI Advantage
In 2023, the American Trucking Association reported a shortage of over 80,000 drivers, creating an urgent need for trucking and logistics companies to hire and retain drivers and support staff throughout the value chain. A key to addressing this challenge is enhancing the driver and employee experience, making it positive and differentiated.
Traditionally, safety and quality teams spend significant time annually reviewing driver and warehouse team member certifications and documentation, including driver’s licenses, medical examiner’s certificates, training certificates, background checks, and motor vehicle records. This has been a major cost center, as the wide variety of document formats and unstructured data/images couldn’t be automated previously.
AI now enables these processes to be automated end-to-end, reducing the hours required to onboard or re-certify drivers. This decreases turnaround time, getting drivers on the road and driving revenue faster. Quality and safety improve as automation reduces errors and omissions.
In a down-market, the impact of faster onboarding is crucial. When market demand returns, improving the ability to scale quickly and avoiding bidding wars for talent by providing a positive company experience becomes essential.
Capturing Orders: The AI Advantage
Logistics executives are heavily investing in AI to prepare for capturing orders and new business when the market rebounds. In high-transaction sales, it’s crucial to maximize time spent hunting for new opportunities and minimize time on manual order entry or data searches. Traditionally, this required extensive sales support, contact centers, and order entry teams. As market demand increased, more support staff had to be hired. Errors, such as incorrectly typed information, could cause customer disruptions, damage relationships, and distract salespeople from their core responsibilities.
With AI, organizations can maintain a leaner staff and achieve faster cycle times in the order-to-cash (O2C) value chain. Manual entry steps in the sales process are automated, allowing sales reps to focus on new business and enhancing individual productivity. AI scales with sales, eliminating the need to hire additional support staff ahead of predicted sales volumes. Errors are reduced, leading to better customer and employee experiences.
Logistics Leaders of the Future: Powered by AI, Flexible, and Scalable
Companies investing in AI during the downturn will be better prepared than their rivals to capture demand when the market rebounds. These nimble companies have not only trimmed costs but also implemented dynamic systems that enable them to scale without a proportional increase in employee count. More productive employees, focused on higher-value activities, will improve retention rates and customer experiences, creating significant differentiation. Retaining processes in-house, rather than outsourcing, will further boost quality and give logistics firms greater control over their operations.
Forward-thinking logistics leaders are using this crisis, including layoffs and disruptions, to position themselves for future success. By leveraging AI to optimize hiring, retention, process management, and order capturing, they are building a foundation for scalability and efficiency. Those who fail to adopt AI will find themselves struggling to keep up. The logistics leaders of tomorrow are being forged in today’s challenging market, and their success will be powered by AI.
Discover the Power of Kognitos
Our clients achieved:
- 75%manual data entry eliminated
- 30 hourssaved on invoicing per week
- 2 millionreceipts analyzed per year
