The full agenda — with receipts

Sets the frame for two days of technical and commercial debate — worth watching for which tensions (grid capacity, reimbursement, uptime, standards) the organisers flag as this year's priorities. No content to assess yet; the value is in what gets named as urgent.

URSSAF's reclassification of home charging reimbursements as a taxable benefit-in-kind is a live compliance risk for every French fleet operator with EV drivers charging at home. Fleet managers and mobility leads need the exact four-criteria test now, not after an audit — this is operational risk, not a policy footnote.

France's fleet home-charging reimbursement rules sit at the intersection of tax law, employer liability, and metering accuracy — get them wrong and fleets face compliance exposure or drivers face under/over-payment. Anyone running or supplying home-charging programs for French fleets should want clarity here on what documentation and metering standards actually satisfy regulators. Watch for whether this session gives concrete compliance thresholds or just restates the ambiguity operators already face.

Charger sizing and software choices still get made on spec-sheet power ratings rather than grid connection reality, driving unnecessary OPEX and stranded capacity. Relevant to anyone specifying depot, fleet or public hardware who wants a European cross-market view rather than a single-vendor case study.

A chance to pressure-test Siemens' framework against attendees' own site constraints — grid connection limits, mixed-use depots, and where software-defined power management actually pays back.

Structured deal-flow time — useful for BD, procurement and partnership leads to map who's building depot, public and grid-services capacity this cycle rather than cold-emailing after the event.

Placeholder slot — content and speaker unconfirmed, so no basis yet to assess relevance.

Grid interconnection delays remain one of the biggest bottlenecks to charger deployment timelines, so autonomous solar-powered charging is a direct bet against utility lead times rather than a sustainability add-on. Relevant to site hosts and planners in grid-constrained or disaster-prone regions weighing capex against deployment speed.

Expect scrutiny on the numbers that matter for off-grid claims — actual kWh throughput versus grid-tied DC fast charging, uptime in low-sun conditions, and total cost versus a standard grid connection.

Freight electrification hinges on whether depot and destination charging can support 500-700km routes without eroding the CO₂ and cost case versus diesel — a real operator's numbers from DSV matter more than vendor projections here. Core audience: logistics fleet operators and infrastructure planners weighing MW-scale grid connections against subsidy timelines.

Where the incentive math and energy-cost assumptions get tested — expect questions on grid connection lead times and whether public destination charging is actually available at scale yet.

Charging network uptime remains a persistent complaint from EV drivers and fleets, and vendor protocol fragmentation is a root cause AI-based predictive maintenance can't patch over. Relevant to CPOs and network operators under pressure to fix reliability metrics before adding AI features on top of unresolved hardware and standards debt.

Charger uptime remains the single biggest lever on CPO revenue and driver trust, yet AI-driven diagnostics are only as good as the hardware and telemetry discipline behind them. This Q&A should clarify where AI genuinely reduces truck rolls today versus where it's still marketing, and what data hygiene operators need before deploying it.

As charging networks scale and payment methods diversify (RFID, app, ad-hoc, roaming), they inherit the fraud patterns already seen in telecom and fintech—but most CPOs lack dedicated fraud tooling. Anyone running a public network should care about the self-check framework here: exposure often hides in roaming settlement and free-vending edge cases, not just card fraud.

Follow-up to assess how fraud detection frameworks translate into concrete network monitoring and roaming/settlement controls. Worth attending if you need to benchmark your own exposure against adjacent-industry practice.

OCPP fragmentation and inconsistent OEM implementations are the real reason predictive maintenance has been hard to scale across mixed hardware fleets. The claim to interrogate: can ingesting OEM manuals actually build usable protocol-translation dictionaries, and what OPEX reduction is realistic versus reactive maintenance baselines.

Key question for operators: what's the actual accuracy and false-positive rate of AI fault diagnosis in production networks, and how much human intervention still remains in the loop.

As charger density flattens in mature markets like France, competitive advantage shifts from coverage to driver loyalty—a metric CPOs have historically ignored in favor of utilization stats. Fleet and CPO strategy teams should care about how preference share is measured and whether it predicts churn better than pricing.

Worth pressing on methodology: how preference share is measured across driver segments and whether it's actionable for network planning versus just a marketing metric.

V2G has been technically proven but commercially marginal in France due to grid tariff structures and aggregation costs eating into dispatch value. Fleet operators and aggregators should want hard numbers here on what margin actually survives after wholesale, capacity, and battery degradation costs.

The real test: do the predictive analytics models discussed hold up against French grid signal volatility, or do they only work in backtested conditions.

Home charging access remains the biggest EV adoption blocker for apartment dwellers, and robotic/autonomous connectors are pitched as the fix for both this and autonomous fleets—but the economics of rail-based systems versus simple cable management are unproven at scale. Anyone planning depot or MDU charging should ask what utilization gains are backed by deployed data versus projections.

Central question: what's the installed base and real-world reliability of robotic charging systems today, not just the utilization theory.

E-trucking economics hinge on charging uptime and TCO parity with diesel, both still fragile given megawatt-charging infrastructure gaps across European corridors. Fleet operators and investors should want clarity on which business models—CPO-owned, OEM-bundled, or fleet-operated—actually pencil out by segment, not just aggregate market-size projections.

European e-trucking is the segment where charging economics get brutal fast: MW-level dispensing, tight dwell times, and depot-vs-corridor infrastructure debates that will decide which CPOs survive. Fleet operators and grid planners should listen for concrete answers on standardisation (MCS rollout pace), cost-per-kWh at scale, and whether public corridor charging can actually support long-haul freight by regulatory deadlines.

Sets the frame for where the EV charging industry actually stands versus the roadmap—useful as a gauge of whether the agenda leans toward hardware reliability, grid integration or business-model survival this year.

Charging networks are becoming a real attack surface as chargers, backends and vehicles converge into one connected system—TARA/SBOM/CVE correlation and PKI-based identity are the practical mechanics of defending it, not theoretical security. CPOs and OEMs exposed to remote-command vulnerabilities in charging protocols should care about how attack chains actually get reconstructed across multi-stage incidents.

Follow-up on concrete implementation questions: who owns PKI certificate lifecycle across a multi-vendor charging network, and how fast can AI-driven detection actually flag a live multi-stage attack versus a false positive.

Placeholder slot—content undisclosed, so the value here depends entirely on what gets announced live.

Home charging remains the highest-volume, lowest-margin-visibility segment of the EV ecosystem, and bidirectional V2X is the lever vendors are betting on to change that math. Anyone modeling residential TCO or grid-service revenue streams should scrutinize whether the claimed household energy-readiness holds up against actual grid tariff and hardware constraints.

Key unresolved question for the room: does V2X pay for itself on realistic residential utilization rates, or is it still a subsidy-dependent proposition.

Points at a structural problem many CPOs don't want to admit: the driver-facing app—and therefore the customer relationship and data—often belongs to an OEM or aggregator, not the CPO installing the hardware. With Belgian dynamic pricing cited as a maturity benchmark, this session matters to any CPO trying to build recurring revenue rather than just hardware margin.

The real question for CPOs in the audience: what contractual or technical lever actually wins back app ownership and customer data once an OEM has it.

Logistics real estate is an underused asset for fleet electrification—turning warehouse land and grid connections into third-party charging infrastructure changes the capital allocation question from 'who builds charging' to 'who already owns the site.' Fleet operators, CPOs and property investors should listen for how phased grid capacity investment actually gets sequenced against uncertain fleet electrification timelines.

Expect pressure-testing of the phasing claims: what grid capacity thresholds trigger the next investment stage, and how property owners share risk with CPOs and fleet customers.

Uptime is the metric that determines whether public charging trust survives past the early-adopter phase, and reactive maintenance economics don't scale to national networks. CPOs and investors modeling TCO should want specifics on what ML diagnostics catch that traditional telemetry monitoring doesn't, and which O&M compliance benchmarks are actually being used across markets.

Uptime is the metric that determines whether a charging network actually generates revenue, and unplanned downtime remains one of the industry's most expensive unsolved problems. The open question for this Q&A: which AI-driven diagnostics and O&M workflows actually move the needle on fleet availability versus which are vendor hype. Operators, CPOs, and asset managers weighing predictive maintenance investments should be listening for concrete uptime figures and integration lessons, not generic AI claims.

Standard closing-day logistics with no technical content for attendees to extract.

Wrap-up segment; any value lies in synthesis of the two days' recurring themes rather than new information.