Israel's military has dramatically accelerated its operational decision-making through integrated artificial intelligence and data systems, according to Col. Rotem Beshi, commander of Matzpen, the IDF unit responsible for coordinating AI and intelligence across the armed forces.
The transformation represents a significant shift in how modern militaries process information and execute strategy. Tasks that previously required days to complete—from identifying targets to planning coordinated attacks—can now be accomplished in hours or minutes, Beshi told The Jerusalem Post in an exclusive interview.
The IDF announced a brigade-sized unit less than one year ago to address the spread of artificial intelligence use across the military, including the Matzpen unit, which operates under the Communications and Cyber Defense Command, headed by Maj.-Gen. Aviad Dagan. Beshi, 38, holds two degrees in computer science, a master's degree in technology and systems management, and a certification as a chief data officer from MIT.
How the System Works
Matzpen's LOCHEM system managed all planning for attacks during the recent war with Iran, working closely with the air force's Iran unit. The system helps decide operational priorities and integrates the planning of entire waves of attacks by gathering and processing data that connects intelligence, operations, and field commanders.
"The goal is for IDF field commanders to feel they are dealing with a familiar, user-friendly technological world that empowers them to better carry out the war's strategy and tactics, rather than technologies that are confusing to use and slow them down," Beshi explained.
Data is transmitted across all major IDF commands—northern, southern, and central—significantly altering how military planning occurs. The tight integration allows intelligence processes to identify a target, move to operational processes, then to concrete planning, approval, and actual attack, followed by battle damage assessment.
Civilian Protection and Warning Systems
One of the most significant applications involves civilian safety. During the recent conflict, Matzpen's data processing helped the IDF Home Front Command issue faster warnings to the civilian population. Between the June 2025 Iran war and the 2026 war, the IDF Home Front, working with Matzpen, overhauled processes for establishing coordinates of Iranian attacks and getting that data to police, Magen David Adom, and the broader civilian population.
Matzpen's joint big data AI research with IDF Intelligence, the air force, and home front district units made it possible to reduce the size of warning areas. Initial warnings at the start of the war for potential Iranian ballistic missile hits covered a polygon of two million people, but this was eventually reduced to 900,000 people, and in some cases even fewer. This reduction means warnings and responses are more focused, reducing disruption to everyday life routines from receiving missile warnings to more specific residential areas.
Another application, referred to as "Binah" (insight), coordinated the positioning and capacities of all local village security teams and their commanding security coordinators.
Operational Speed and Precision
Beshi described a concrete example of the system's effectiveness: in late March, when a Hezbollah fighter fired an anti-tank missile toward IDF troops in southern Lebanon, those forces received a warning within two seconds via a Matzpen application, giving them enough time to reach a protected stance and resulting in no harm.
In southern Lebanon, Matzpen works with ground force sensors to provide a detailed real-time threat picture for the Northern Command. The system uses highly complex algorithms to issue targeted warnings only to clearly threatened IDF forces in specific localities, avoiding disruption to other military operations.
Matzpen's MAPIT program works with satellites, including IDF Unit 9900, which handles satellite information. MAPIT takes incoming reports about threats to cities like Beersheba or Haifa, categorizes the data or video footage, and pulls it onto a digital map with huge data capacities that multiply the use of big data power.
Reducing Friendly Fire Incidents
Beshi noted that Matzpen's applications have helped reduce friendly fire incidents by mapping friendly forces with precision. While accidents still occur, they typically happen not because soldiers lacked information about other units' locations, but because soldiers were pinned down so severely they lacked the time and space to physically interface with available data.
The IDF is undergoing what Beshi described as a major revitalization of its management of AI, data, and media for operations. The military receives and absorbs operational reports from around the world on every front, including open source data, to build a platform serving as a mosaic of information.
"The IDF understood, like any large business or entity, what the value is of its data," Beshi said. "The value of AI and big data, if the data is closed off and inaccessible to groups of people who might need it, compared to different kinds of data storage clouds, can change and directly impact the real-world military front lines."
Beshi, selected by Forbes magazine for its 30 Under 30 list in the ninth year ago, has spent around 20 years in various roles in the Communications Command, including what was once known as the LOTEM Brigade, now absorbed into the new AI-focused brigade.
Why This Matters:
The acceleration of military decision-making from days to minutes raises significant questions about institutional oversight, proportionality, and civilian protection in modern conflicts. While faster warnings to civilians and reduced warning zones represent potential improvements in civilian safety, the dramatic speed of operational decisions—from target identification to attack execution—compresses the time available for human judgment and institutional review. The system's effectiveness in reducing civilian warning zones demonstrates how data systems can theoretically minimize disruption, yet the underlying capacity to execute coordinated attacks at unprecedented speed reflects a fundamental shift in the balance between technological capability and deliberative decision-making processes. The integration of AI across all military commands, the reliance on algorithmic decision-making for targeting, and the compression of human oversight into minutes rather than hours represent structural changes that merit sustained public scrutiny regarding accountability, transparency, and adherence to international humanitarian law—particularly as similar systems proliferate across militaries worldwide.