AI-driven pricing key to competitive edge for logistics firms: Report

Logistics companies can gain a competitive advantage by adopting AI-driven pricing strategies, which improve profitability beyond cost control and sales growth, a new McKinsey report finds. AI helps automate pricing and match it with customer demand.

Logistics companies that move quickly to adopt AI-driven pricing strategies are likely to gain a competitive advantage, as pricing becomes an increasingly important driver of profitability alongside cost control and sales growth, according to a McKinsey report.

The report said advances in artificial intelligence are making it easier for logistics operators to improve pricing decisions, automate pricing processes and better match prices with customer demand and network efficiency.

It noted that companies relying only on cost discipline and volume growth may struggle to keep pace as AI reshapes the sector. "For logistics companies, cost discipline and sales growth alone are not enough. Companies that can move quickly to reimagine their pricing are likely to find advantages in the AI era," the report said.

Four Key AI-Driven Pricing Strategies

According to the report, logistics companies should focus on four key pricing strategies: identifying customers' willingness to pay using advanced analytics, digitising contract and deal reviews, using pricing to optimise logistics networks, and automating price execution through AI-powered workflows.

The Role of Modern AI Capabilities

It said recent advances in generative AI and agentic AI have significantly reduced the barriers to implementing these capabilities.

Improving Decisions with Analytical Tools

The report noted that AI-powered analytical tools can process structured and unstructured data to improve pricing decisions, while digitised deal reviews can help companies use historical contract information more effectively during negotiations.

Optimising Networks with Digital Twins

It added that digital twins can help operators better understand network economics, enabling them to price freight more accurately based on cost, demand and operational risk.

Automating Execution with Agentic AI

On execution, the report said agentic AI can automate activities such as request-for-quote responses, order entry and rate updates, helping reduce administrative costs and revenue leakage while improving response times. In one example cited by McKinsey, an AI-powered solution reduced response time for non-standard customer requests from four hours to two minutes.

Analysis Shows Pricing is Key to Profitability

McKinsey's analysis of 21 logistics companies over the 2017-2022 period found that the top-performing companies increased prices 20 per cent faster annually than the median. It also found that most companies delivering top-quartile earnings before interest and taxes (EBIT) growth were also among the strongest performers in price growth, highlighting pricing as an important contributor to financial performance. (ANI)

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