1. From your perspective, what are the main product challenges today in developing solutions for the Mobility & OEM ecosystem, within an increasingly data-driven and global context?
In 2026, the mobility and OEM ecosystem is awash in vehicle telemetry and behavioural data, but converting that data into scalable, profitable products remains difficult due to structural, regulatory, and technical constraints. The core challenge has shifted from vehicle connectivity to data availability for new products and services, resolving data ownership, interoperability and the economic viability of AI-driven features.
Data availability to replace the use of aftermarket devices as a data source continue to be a significant challenge to allow value added telematics services continue to be critical limiting factor improving the value of connected ecosystem. Although some leading OEMs are starting to drive
Data ownership and privacy are major product bottlenecks. It remains unclear who owns vehicle data—OEMs, fleet operators, drivers, or third parties—creating conflicts that slow product development. Fleet operators often see data as a competitive asset, while OEMs license it externally. Regulatory frameworks like GDPR further limit AI use cases, forcing companies to balance innovation against compliance risk. Despite industry rhetoric around open data ecosystems and “data fusion,” many customers—especially in government and law enforcement—resist data sharing, limiting adoption of products that depend on broad ecosystem participation. As a result, vehicle data remains siloed across stakeholders.
Software-defined vehicles and EVs introduce new complexity, and EV repair and maintenance are more expensive and slower due to vertical integration, parts shortages, and technician scarcity, requiring new approaches in claims and service management products. AI remains central to mobility strategies, but its ROI is uncertain: high data volumes, bias management, and the need for costly human-labelled data make AI features expensive to build and scale.
Overall, while data-rich vehicles promise transformative mobility products, unresolved data governance, limited data packages limiting AI economics, and infrastructure costs continue to limit scalability and profitability across the ecosystem to realize the full value and benefits to all of the ecosystem partners and players.
2.How does OCTO support OEMs and mobility operators in transforming connected vehicle data into actionable insights that improve products, services and the end-user experience?
OCTO transforms large-scale connected vehicle data into actionable insights for OEMs, insurers, and mobility operators by leveraging one of the world’s largest driving data repositories. Using a device-agnostic IoT platform, OCTO ingests real-time telemetry from factory-installed systems, smartphones, and aftermarket devices, enabling seamless integration across diverse hardware environments.
At the core of this capability is the OCTO Cloud Platform, a modular, multi-vehicle architecture that processes data from edge to cloud. The platform normalizes high-frequency telemetry across vehicle types, enriches it with contextual data such as weather, traffic, and road conditions, and applies machine learning models to generate operational insights, driver behavioural scoring, ability to detect and validate crash data with action and deliver unique fleet services and insights to improve overall TCO.
These insights are operationalized through several key product capabilities. OCTO’s DriveAbility® scoring system predicts driver risk based on behavioural patterns rather than mileage, supporting accurate pricing, portfolio segmentation, and fleet performance analysis. For fleets, lifecycle “scorecards” provide data-backed proof of vehicle condition, improving asset management and resale value.
OCTO also enables automated crash and claims management by acting as a “virtual witness.” Telematics data is used to reconstruct accidents, trigger automated First Notification of Loss (FNOL) within minutes, and support fraud detection through objective validation of claims.
Beyond risk and claims, the platform supports vehicle health monitoring through remote diagnostics and proactive asset protection, including AI-driven theft detection. For drivers, OCTO’s Digital Driver™ solution converts telemetry into personalized feedback, safety services, and coaching tools that promote safer driving behaviour.
Strategically, OCTO strengthens its ecosystem impact through direct OEM integrations, such as its partnership with Mobilisights/Stellantis, allowing access to native vehicle data across multiple brands. This shift toward embedded data strategies enhances scalability, improves data quality, and creates a continuous loop of product and service innovation across the mobility value chain.
3. What role do Artificial Intelligence and data intelligence play today in the development of OCTO’s mobility products, and how are they changing the way OEMs design and deliver their services?
OCTO has placed AI and advanced data intelligence at the center of its mobility solutions, enabling a shift from traditional, reactive telematics to predictive, software-driven services. By combining machine learning with IoT data from millions of connected vehicles, OCTO helps OEMs and mobility operators transition from static, hardware-focused models to proactive, service-oriented offerings.
At the platform level, OCTO’s device-agnostic cloud infrastructure ingests and normalizes billions of data points daily from factory-installed systems, third-party devices, and smartphones. AI models analyze this data to detect patterns that support dynamic, condition-based decision-making rather than scheduled or retrospective interventions—what OCTO defines as the “third era of telematics.”
A major application of this intelligence is predictive maintenance and vehicle health management. AI analyzes telemetry such as fault codes and vibration anomalies to anticipate component failures before breakdowns occur, reducing downtime, warranty costs, and service disruption. Continuous monitoring also feeds into vehicle “Scorecards,” digital records of usage and condition that preserve residual value and improve transparency across the vehicle lifecycle.
In risk profiling and safety, OCTO uses its extensive driving data to move beyond demographic-based assessments toward real-time, behaviour-driven risk scoring. The DriveAbility® Score enables precise portfolio segmentation and supports usage-based insurance models. AI-driven safety solutions also include predictive anti-theft systems and automated crash detection and reconstruction, significantly accelerating claims processing and fraud prevention.
OCTO further applies AI to personalize the driver experience through solutions like Digital Driver. These tools provide individualized coaching, gamified rewards for safe driving, and contextual trip insights, strengthening engagement, safety, and customer loyalty.
Finally, OCTO enhances its AI accuracy through strategic data partnerships, with strategic OEM partnerships developing and giving access to embedded vehicle data across multiple brands. This deep OEM integration improves predictive accuracy, strengthens risk prevention, and reinforces a continuous loop of data-driven product and service innovation across the mobility ecosystem.
4. Working from London, what are the main differences you observe between the UK and Italian mobility markets, particularly in terms of approach to innovation, data and business models?
The UK and Italian mobility markets represent contrasting stages of evolution shaped by different regulatory approaches, technology legacies, and consumer attitudes toward data. Italy is Europe’s most mature telematics market, while the UK is a fast-growing challenger driven by software-led innovation.
Italy has one of the highest telematics penetration rates globally, largely built on professionally installed black-box hardware initially adopted to combat vehicle theft. This maturity has slowed growth, shifting market focus from acquisition to retention. Italian regulation emphasizes data portability and competition, requiring insurers to make driving data transferable to reduce customer lock-in. Culturally, Italian consumers have been more willing to share vehicle data, viewing it as a trade-off for security and theft recovery. In mobility services, Italy follows a public-sector–led MaaS model, with centralized coordination and standardized integration across cities like Rome and Milan. Operationally, Italy has often served as a growth-focused market where scale is prioritized over short-term profitability.
The United Kingdom, by contrast, is characterized by rapid growth and technological flexibility. Telematics penetration is slightly lower but expanding quickly, driven by usage-based insurance, smartphone-based data collection, and app-first models favoured by younger consumers. Regulation under the Financial Conduct Authority actively pushes innovation and transparency through Consumer Duty and Fair Value requirements, encouraging data-driven pricing and new vehicle risk classifications. UK consumers are more cautious about data sharing, requiring clear financial value to drive adoption. MaaS in the UK is market-led and private-sector driven, resulting in faster innovation but greater fragmentation. Businesses tend to operate with a strong focus on unit economics and profitability, especially in dense urban hubs like London.
Strategically, solutions providers such as OCTO must adopt a dual approach: leveraging established hardware infrastructure and public partnerships in Italy, while focusing on agile, software-defined, and consumer-centric solutions to compete in the UK’s fast-moving, value-driven market.