Indian Truck Demand Forecast

ACG has released the Indian Fuel and payload-based Truck Demand Forecast Analytics Data and Report 2035 — and it’s built on a methodology we believe changes how truck demand should be measured in India. Fleet Owners pay for payload, not GVW.

Truck demand depends on far more than just GDP and Key economic indicators. This report is the result of that belief, backed by deep, application-level analysis most forecasts simply don’t attempt.

Why GDP and Macro Indicators Alone Fall Short

Traditionally, truck demand forecasts lean on GDP growth or degrowth and broad macroeconomic indicators. It’s an easy, simple shortcut — but it’s also imprecise.

Looking only at GDP tells you the general direction and overview of the economy. It doesn’t tell you how many trucks are actually needed to move the freight that economy generates. That’s a very different question, and it needs a very different methodology.

Our Methodology: Forecasting by Payload and Application, Not GVW

Here’s the core insight behind our Indian truck demand forecast: demand for trucks depends on the payload and Truck Applications available in the market — not on Gross Vehicle Weight (GVW) alone.

We’ve measured the expected payload available each year, and calculated how many trucks are actually needed to carry that payload. This payload-first approach is a highly precise methodology. ACG has been developed specifically to gauge truck demand — both year by year and application by application.

This is where the real difference lies. A GVW-based view tells you what trucks exist in the market. A payload-based view tells you what the market actually needs to move — and that’s what drives real demand.

ICE Truck Demand: What’s Really Shaping It

In heavy-duty trucks, nearly every sub-segment showed growth in FY 2026 — with only two sub-segments as exceptions. High-payload trucks are now increasingly available in the market, and this shift will directly influence future truck demand.

Beyond payload availability, our forecast accounts for a wide set of ground-level factors that most models overlook:

• Truck utilization, Payload pattern, and idle time
• Policy framework and its impact on various applications
• Payback period
• Truck age and replacement cycle
• Technology adoption rate and its real-time impact
• Availability of finance
• Freight rates
• Load-providers’ app penetration
• Profit margin per trip

Recently, heavy-duty truck sales grew by 10.3% in FY 2026. The real question our forecast answers isn’t just whether growth happened — it’s whether that pace is sustainable, and our application-wise methodology is what makes that answer credible.

Electric Truck Demand: A More Complex Picture

Forecasting electric truck demand is meaningfully harder than diesel, CNG, or LNG. Total Cost of Ownership (TCO) and payback period alone aren’t enough to reach a reliable conclusion.

Electric trucks sit inside a much larger ecosystem, and each part of that ecosystem plays a different role depending on the truck and application:

• For some trucks, duty cycle is the deciding factor
• For others, it’s range
• For others, it’s charging cost and charging infrastructure
• For others, it’s route
• For some, all of the above matter together

Route flexibility is a particularly important — and often ignored — factor. In India, 35% of trucks run on zigzag routes, moving freely from the loading point rather than following a fixed path. Answering how electric trucks can realistically support this kind of route flexibility is central to forecasting EV truck demand accurately — and it’s exactly the kind of ground-level question a GDP-based model can’t answer.

Application-Wise Truck Demand Mapping: Different Truck Types and various routes

A single application can require several different truck types. Mini trucks, pickups, rigid haulage, tippers, tractor-trailers, and specialized trucks are often all needed just to transport the material for one industry.

Take the cement industry as an example. It uses nearly every truck class, from 2-tonne to 55-tonne:

• Plant-to-distributor or plant-to-customer movement relies on bulkers, tractor-trailers, and rigid haulage
• Distributor-to-final-destination movement relies on medium- and light-duty trucks, minis, and pickups — the exact mix depending on payload and distance

Cement is a growing industry, and its truck requirements are as varied as its supply chain. We analyzed more than 100 truck applications to measure truck demand in India this precisely — and in total, we’ve analyzed all 120 applications and sub-applications that make up the Indian Truck Demand Forecast 2035.

Why This Methodology Is Unique

Most truck demand forecasts stop at GDP and macro trends because that data is easy to access. ACG’s approach goes further, on purpose:

• Payload-based, not GVW-based — measuring what the market actually needs to move, not just what vehicles exist
• Ground-factor driven — utilization, idle time, financing, freight rates, and technology adoption, not just economic headlines
• Ecosystem-aware for EVs — treating electric truck demand as a multi-factor system, not a simple TCO calculation
• Application-wise depth — 120 applications and sub-applications analyzed individually, not lumped into one national number

That depth is what makes this report genuinely different — a truck demand forecast built from the ground up, not from the top down.