Fleet Management maintains a single authoritative registry of every vehicle and item of equipment in the organisation: make, model, year, vehicle identification or serial number, registration, acquisition details, current status and the person or cost centre it is assigned to. Around that registry it runs the full operational programme a fleet requires. It schedules and records inspections, whether pre-trip driver checks, periodic safety examinations or statutory roadworthiness tests, against configurable checklists. It manages repair orders from fault report through diagnosis, parts, labour and completion, for work carried out in house or by external garages. It operates preventive maintenance programmes triggered on mileage, engine hours or elapsed time, raising due and overdue alerts before a service window is missed.

Beyond the workshop, the module tracks fuel transactions and odometer or hour readings to derive consumption and utilisation, manages driver assignment and licence validity, and ingests telematics so that position, usage and diagnostic signals feed the same record. Every cost that touches an asset, parts, labour, fuel, external invoices and downtime, accumulates against it to produce a live total cost of ownership per vehicle. The result is one place where the condition, compliance, availability and economics of the fleet are always current.

At the centre of the module sits the asset: the specific vehicle or piece of equipment, uniquely identified and carrying its own history for as long as it is owned. Every other concept in the module either describes that asset or records something that happened to it. An asset is assigned, over time, to the people who operate it and to the cost centre that carries its expense, so the same machine can pass through several drivers and departments while keeping one continuous record.

The second organising idea is the service event: any dated activity performed on an asset. Inspections, repair orders and preventive maintenance jobs are all species of service event, each with its own detail, a checklist and outcome for an inspection, parts and labour lines for a repair, a triggering rule and completion for a scheduled service, but all sharing a common spine of when it happened, who did it, what it cost and what condition it left the asset in. This is why a single asset timeline can present roadworthiness, workshop history and routine servicing together.

Running underneath both is the usage record: the stream of fuel fills, distance and hour readings, and telematics signals that quantify how hard an asset is worked. Usage is what makes preventive schedules fire, what turns fuel spend into a consumption figure, and what converts raw expenditure into a meaningful cost per kilometre or per hour. Finally, the driver is modelled as an accountable operator with a licence class and expiry, so the right to operate an asset is a fact the system holds and validates rather than an assumption. These four ideas, the asset, the service event, the usage record and the driver, relate simply and predictably, which keeps the operational picture legible even for a large mixed fleet.

The daily rhythm of the module runs through a small number of well defined workflows. A driver or supervisor completes a pre-trip inspection against the checklist for that asset class; a failed item can hold the vehicle out of service and open a fault automatically. When something needs fixing, a repair order captures the symptom, is assigned internally or dispatched to an external provider, accrues parts and labour as work proceeds, and closes with the asset returned to available status and its cost history updated.

Preventive maintenance runs continuously in the background. The module watches accumulated mileage, hours and elapsed time against each programme and raises the next due service in advance, so planners schedule work into quiet windows rather than reacting to breakdowns. Fuel and odometer entries, whether keyed, imported from a fuel card feed or received from telematics, reconcile against expected consumption and flag outliers. Driver assignment and licence renewal follow their own cycle, with expiry warnings raised before a driver falls out of validity. Across all of these, controlled activities such as approving a costly external repair, writing off an asset or overriding an inspection hold pass through approval steps before they take effect.

Total cost of ownership is treated as a first-class calculation, not a report bolted on afterwards. For each asset the module accumulates acquisition, financing, fuel, maintenance, parts, labour, external service, insurance-related and downtime costs, and expresses them both as a lifetime figure and as normalised rates per kilometre, per hour and per period. Because usage and cost share the same record, these figures are always reconcilable to their underlying transactions, which is what makes them defensible in a replacement or leasing decision.

Compliance depth is equally deliberate. Inspection regimes are configurable to the regulatory obligations of each asset class and jurisdiction, retaining the completed checklist, the inspector, the result and any defects as an auditable record suitable for a safety authority. Preventive maintenance intervals follow manufacturer schedules, and service history is retained in full so warranty and duty-of-care positions can be evidenced. Licence class and medical or certification expiry are validated so that operating an asset without the correct entitlement is prevented rather than merely discouraged. On the accounting side the module carries the cost dimension of each asset cleanly: operating costs are coded to the correct cost centre and account for allocation, while the capital value and its depreciation remain the responsibility of the fixed asset register, with which this module stays consistent. Segregation of duties, full change history and status controls around going out of service, returning to service and disposal give the module the internal controls expected of an audited enterprise.

Fleet Management is deliberately narrow about ownership and generous about integration, so it never duplicates what another module already governs. It works most closely with Fixed Assets: each vehicle and item of equipment corresponds to a capitalised asset there, and the two modules stay aligned on identity, acquisition and disposal while depreciation and net book value remain the fixed asset register's concern and operational history remains this module's. Every operating cost the fleet incurs flows into Accounting and Control, coded to the right cost centre and account so that fuel, maintenance and external service land correctly in the ledger and in departmental cost analysis, and so that per-asset cost of ownership reconciles to the financial records.

Telematics and connected hardware arrive through Device Management, which owns the IoT estate and streams position, usage and diagnostic data into the asset record without Fleet Management having to manage devices itself. Repair orders draw approved external providers and their invoices from the procurement and payables side of the suite, driver identity aligns with the people and access modules, and every controlled action routes through the suite-wide workflow and approvals engine. The effect is a module that feels native rather than bolted on: one identity for each asset, one ledger for its costs, one directory for its people and one automation fabric for its decisions.

AI Workers are first-class users of Fleet Management, holding the same permissions and acting through the same controls as their human colleagues. They answer questions against live fleet data in plain language, so a manager can ask which vehicles are overdue for service, which drivers hold a licence expiring this quarter, or how cost per kilometre has moved across a depot, and receive an answer grounded in the current record. They also execute actions within their granted authority: opening a repair order from a reported fault, scheduling a preventive service into an available window, reassigning an asset, or recording a fuel or usage entry.

Much of their value is watchful. AI Workers monitor inspection results, consumption, telematics diagnostics and maintenance schedules, and raise anomalies and exceptions early: a fuel figure inconsistent with distance travelled, an asset accumulating hours faster than its programme assumes, a missed statutory inspection, or a fault pattern that suggests a developing failure. They extract structure from documents, reading external repair invoices, inspection sheets and registration paperwork into clean lines against the correct asset. And they support decisions, comparing repair-versus-replace economics from an asset's own cost history or highlighting the vehicles driving disproportionate cost. Where a workflow requires judgement, an AI Worker can stand as a review or approval node, checking an external repair estimate against history and policy before it proceeds or escalating it to a person, so automation and accountability move together.