Transport & logistics firms boost AI spend despite gaps

Sparq has published a survey on AI and technology investment in the transportation and logistics sector. It found that 90% of respondents said returns on those investments had met or exceeded expectations.

The survey covered 313 senior decision-makers at freight, trucking, parcel and courier companies with annual revenue of at least USD $500 million. It found that 87% expect their organisations' technology and AI budgets to rise in the next fiscal year, even as many still report gaps in operational readiness.

Demand forecasting emerged as the area where respondents felt least prepared. Some 53% ranked forecasting accuracy among their top three readiness gaps, although 61% said their organisations had already implemented demand forecasting technology.

That tension ran through the wider findings. While 92% said their organisations were fully or mostly prepared for the holiday peak shipping season, many still pointed to cybersecurity and data breaches, labour and driver shortages, and extreme weather disruptions as concerns.

Cybersecurity and data breaches were cited by 43% of respondents, the same share as labour and driver shortages. Extreme weather disruptions followed at 41%.

The results suggest transport and logistics groups are still willing to spend on new systems, but are applying tighter financial scrutiny. Some 62% said their organisations now require faster return on investment timelines from vendors, while 49% said they are consolidating vendor relationships.

Investment pressure

Even with that pressure, appetite for technology spending remained strong. The poll found broad use of tools intended to address operational weak points, including load and route optimisation at 70% of organisations and real-time visibility and tracking at 67%.

Those figures suggest adoption alone has not resolved some of the sector's longstanding difficulties. Companies may have deployed software in key functions, but many executives still do not feel fully in control of those functions.

Legacy systems and integration problems were the most commonly cited barrier to moving faster with AI or advanced data investment, identified by 24% of respondents. Data quality concerns followed at 19%, with unclear return on investment at 17% and budget constraints at 16%.

The methodology shows the survey focused on larger operators. Respondents worked at freight brokerage and forwarding, trucking, parcel, courier and last-mile businesses, with 78% employed at companies generating USD $1 billion or more in annual revenue.

Ninety per cent held director-level roles or above, and all were involved in technology and AI investment decisions. Almost half, 49%, described themselves as final decision-makers.

Readiness gaps

Ingrid Curtis, Chief Executive Officer of Sparq, said the industry's expectations for technology spending are shifting.

"Transportation and logistics companies aren't backing away from technology investment, but the expectations are changing," Curtis said.

"In 2027, it won't be enough to say you've deployed AI or saved employees a few hours a week. Leaders will want to know whether those investments actually improved margins, increased capacity or made operations more resilient. That's the next test for the industry."

Her comments reflect a broader pattern in transport and logistics, where investment cases increasingly rest on whether systems can improve planning, reduce disruption and protect margins in a business known for narrow profit spreads.

For operators, forecasting remains particularly important because errors can affect staffing, route planning, equipment use and customer service at the same time. The fact that forecasting ranked as the biggest readiness gap despite relatively wide adoption suggests companies are struggling to connect tools with day-to-day execution.

That challenge also appears in views on AI adoption more broadly. Rather than simply adding more software, many transport groups may now be trying to combine systems across operations, finance and planning in ways that produce clearer commercial results.

"The next phase of AI adoption will be less about adding more tools and more about making the technology companies already have work together effectively," Curtis said.

"For transportation and logistics businesses, that means connecting data, modernising critical systems and making sure technology investments translate into measurable operational improvements."

The survey was conducted in the US by InnovateMR for Sparq, with a margin of error of plus or minus 5.5 percentage points at a 95% confidence level.