The logistics industry is confronted with unprecedented challenges, including supply chain disruptions, delivery complexities, labour shortages, and pressure to embrace sustainability. Amidst this turbulence, Artificial Intelligence (AI) has emerged as an indispensable tool for logistics companies. According to DP World, 98% of executives rely on AI tools, which has revolutionised at least one aspect of their supply chain operations . Driven by its ability to optimise various aspects of the logistics value chain and unlock efficiency gains and cost savings.
The industry’s enthusiasm for AI is evident, with market research reports forecasting a 46% CAGR from 2022 to 2030, propelling the sector to a $65 billion valuation. However, the overall fundraising deal count for AI-powered logistics companies has shrunk to less than 33%+ of its 2021 peak. Several reasons for the decline in funding include high profile logistics start-ups imploding such as Convoy and Katerra, and others not living up to the expectations e.g. Deliverr. Amid the broader cooling off in the tech fundraising market, the logistics sector has also been grappling with a significant decline in global freight prices. According to Xeneta’s Shipping Index, global container freight rates in 2022-2023 plummeted to a fraction of their 2021 peak, further compounding the challenges faced by companies seeking to secure funding in an already competitive environment – somewhat going against the broad market interest in AI.
However, in terms of recent M&A, 2024 has already seen 50% of 2023’s total activity in the AI-powered logistics space, suggests that players are beginning to consolidate the industry, turning more attention towards AI powered solutions as they look to bolster their AI capabilities and willing to pay premiums in order to do so. The logistics industry is beyond the AI crossroads, and the path forward lies in fully integrating AI in the sector, beyond simple tools and single use case functions. The interplay between technological adoption, funding dynamics, and M&A activity will shape the future of logistics.
AI Optimised Inventory: Less Waste, More Profit
Inventory management is a critical component of supply chain operations, and AI is proving to be a powerful tool in this domain. Companies like ToolsGroup, Invent Analytics, and Vekia are leveraging AI-powered demand forecasting to help businesses better plan their inventory levels. By analysing historical data, market trends, and customer behaviour, these AI algorithms can accurately predict future demand, enabling companies to optimise their stock levels and avoid excess inventory or stockouts.
Streamlined Supply Chain – AI Boosts Production, Minimises Bottlenecks
Supply chain planning is another area where AI is making a significant impact. Companies like Adexa and Seeloz are using AI to enable integrated business planning across the entire supply chain. By considering factors such as customer changes, production capacities, resource availability, and order priorities, AI algorithms can help businesses optimise their production plans and schedules.
AI’s ability to analyse vast amounts of data and identify patterns allows it to predict potential bottlenecks and optimise resource allocation. This not only improves production efficiency but also helps companies adapt to changing market conditions and customer demands.
In a recent example of M&A activity in this space, Great Hill Partners acquired Blue Ridge Global, a provider of AI-powered supply chain management solutions. This acquisition highlights the growing interest in AI-driven supply chain planning and the potential for further consolidation in the industry.
AI-Enhanced Supply Chain Visibility
Supply chain visibility is crucial for logistics companies, and AI is transforming this domain as well. Start-ups like Everstream Analytics and Exiger are using AI and machine learning algorithms to predict disruptions and optimise estimated time of arrivals (ETAs). By analysing data from various sources, including weather patterns, traffic conditions, and historical data, these AI systems can provide real-time insights into potential disruptions, allowing companies to proactively mitigate risks and ensure smooth operations.
Poised for M&A Success: AI-Powered Logistics Companies
AI-powered logistics companies seeking to attract M&A interest must focus on three key areas: proven ROI and customer success stories, scalability and integration capabilities, and advanced AI/ML capabilities and proprietary algorithms.
Showcasing quantifiable benefits, such as Exiger’s solutions that have improved forecasting accuracy by 10-20% and helped manage over 80% of clients spend on key raw materials, is crucial. Companies like FourKites, which offers a platform that integrates with various transportation management systems and provides real-time visibility across the entire supply chain, demonstrate the importance of scalability and seamless integration. Finally, highlighting unique AI/ML capabilities, such as Blue Yonder’s Luminate platform that leverages advanced algorithms to optimise supply chain planning and execution, can set a company apart from its competitors and drive M&A interest.
Adapt, Innovate, or Risk Falling Behind
While fundraising activities in the space may have experienced a temporary slowdown, the M&A landscape is poised for a significant uptick. Large strategic players are recognising the immense potential of AI in logistics and are actively seeking opportunities to accelerate their AI capabilities through inorganic growth. This trend is driven by the understanding that AI is not merely a nice-to-have technology, but a critical component of long-term success and scalability.
By presenting tangible evidence of the cost savings, operational efficiencies, and revenue growth achieved through their AI solutions, companies can make a compelling case for investment or acquisition. Additionally, demonstrating the ability to seamlessly integrate with existing systems and scale solutions across multiple geographies and business units can set companies apart in the eyes of potential partners or acquirers.
Finally, emphasising the sophistication and uniqueness of their AI/ML capabilities can help logistics companies differentiate themselves in a crowded market. By showcasing cutting-edge algorithms, proprietary data sets, and a deep understanding of the specific challenges faced by the logistics industry, companies can attract the attention of strategic buyers looking to gain a competitive edge. As the AI/ML space matures and becomes more integral to the systems of these companies, M&A deals in AI solutions are likely to increase, similar to other technology driven trends.
