How is SCA using technology in forestry?

Mainly through a digital twin of its forest built with AI, according to its own news pages. SCA combines laser scanning of selected forests with data from its harvesters, and uses AI to interpret them. Its planners now do "a large part of the harvest planning at the office" and visit the field where it matters. SCA is also a partner in SingleTree, a four-year EU research project on using data about individual trees with AI and remote sensing. At one sawmill, a CT scanner uses AI to monitor each product. Its annual report describes a different, slower cycle for valuing the forest: a sample-plot inventory roughly every ten years.

What the usual answer says

The top results are SCA's own news items and innovation pages, which describe the planning tool and the research project. General descriptions list laser scanning, remote sensing, GPS-equipped harvesters and digital forest plans. The annual report, where investors look, mentions AI once.

The planning twin

SCA's September 2024 news item announced "a new tool with AI functionality for digital forestry planning". Small tests ran in 2023 and larger ones in 2024. "By utilizing information from forest laser scanning and harvester data in combination with AI, SCA has created a digital twin of the forest using automated data interpretation." The goal was that "by 2025, all forest planners at SCA" would use it. The aim was "higher and more consistent quality of our forest data".

By August 2025, SCA described the tool as in use. Its planners "can now perform a large part of the harvest planning at the office". That lets them plan more during winter and visit "only the areas that truly need field inspections". The project page adds that SCA shares single-tree data from "SCA's own yearly scanning of chosen forests" with the research consortium.

The research and the mill

SingleTree, which began in autumn 2024, asks how "the forest's value chains be optimized using information about individual trees in combination with AI and remote sensing". Its work runs from remote sensing through harvesting machines to wood quality, which is the forest-to-mill link.

At the other end, the 2024 annual report describes a CT scanner at one sawmill. It can "use digital measurement, computed tomography, image analysis and artificial intelligence to monitor each product as it passes through the sawmill". Its Forest Business Accelerator also backed start-ups working on "AI-based measurement methodologies for field inventory", per the 2025 annual report.

The valuation cycle

The 2025 annual report describes a different kind of forest data in its valuation notes. A forest inventory "is carried out roughly every ten years", and between inventories "the annual growth of the forest is simulated on the basis of the inventory". The simulation is done "by an external party that is independent of SCA, and is then fixed until the next inventory", adjusted for actual harvest. That inventory, most recently in 2019, underpins the long-term harvest level of "over 5 million solid cubic meters under bark".

The scale is large. About 200 harvesting teams work for SCA, and its nursery produced 119 million seedlings in 2025, so the harvester data feeding the twin comes from a big, continuous operation. Each harvest adds measured stems to the same forest the twin describes, which is what makes it more current than a sample-plot survey.

The two cycles serve different purposes. An audited valuation needs a slow, independent figure that doesn't move with every new model. Planning needs current, detailed data. Neither SCA source says how far the twin's view of standing volume and the valuation figure differ on the same stands.

What it means for other forest owners

In our view, the useful lesson is to keep the two uses apart and know how old each is. Where an owner has rich planning data from scanning and machines, comparing it with the audited inventory on the same stands shows how far the slower figure has drifted. That comparison is something an AI twin makes cheap and a ten-year cycle leaves undone.

When it doesn't apply

Owners who use one inventory for both planning and valuation, or whose holdings are small enough to cruise often, don't face this split. SCA's pages describe the tool and its purpose; they give no measured accuracy for the twin.

Quarri for forest management is built around how a forest operation runs, from the cruise to the settled account.

Quarri is an AI-native data platform for the timber supply chain. It connects buying, production, sales and inventory for forest management, sawmill, wood products and pulp, paper and packaging operators.