Robotics businesses are increasingly adopting service led models, where hardware, embedded software and AI are deployed together to deliver a defined outcome. These “robot as a service” (RaaS) arrangements offer clear commercial advantages, including recurring revenue and closer customer relationships. However, they also introduce legal and commercial complexity that is not addressed by standard technology contracts.
A well structured legal framework is critical. It underpins how value is created, allocated and protected across the lifecycle of the product, and ensures that contracts support scaling rather than restrict it.
Intellectual Property, Software and Value Creation
At the core of any robotics offering is a combination of proprietary software, embedded systems and, increasingly, AI models. The key issue is not simply ownership, but how rights are allocated and exploited over time.
Businesses need to be clear on:
- what is licensed to the customer versus retained
- how updates, improvements and derivative works are treated
- who owns and can use data generated by the system
- how AI models are trained and refined over time
Without careful structuring, there is a risk of inadvertently granting rights that undermine long term value. For example, overly broad customer rights to data or outputs may limit the ability to improve products or develop new offerings.
Hardware Models: Leasing vs Sale
Unlike pure software offerings, robotics arrangements must also deal with the physical hardware. Whether the hardware is leased as part of a service or sold outright has important legal and commercial implications.
Where hardware is leased or retained by the provider:
- the provider typically remains responsible for maintenance, performance and replacement
- stronger service levels and support obligations are required
- ownership remains with the provider, supporting reuse and asset control
- contractual protections are needed around damage, misuse and return
Where hardware is sold to the customer:
- risk in the hardware often transfers earlier, subject to warranty protections
- ongoing obligations may be limited to support and software services
- it can be more difficult to control how the hardware is used or integrated
- alignment with software licensing terms becomes critical to avoid gaps
Each approach impacts liability, insurance, tax treatment and commercial scalability, and should be aligned with the overall delivery model.
Data, Learning and Control
Robotics systems are data rich by design. Sensors, usage data and AI driven insights can be as valuable as the underlying hardware itself. This creates both opportunity and regulatory pressure.
From a data protection perspective, businesses must:
- clearly determine whether they are acting as controller or processor
- ensure transparency around how personal data is collected and used
- implement appropriate governance where multiple parties access or share data
From a commercial perspective, it is equally important to address:
- rights to use operational data to improve services and train models
- whether data can be retained following termination
- restrictions on customer use of system generated data
Failing to address these issues can result in loss of control over a key asset or constraints on innovation.
Liability, Risk and Performance Frameworks
Robotics solutions combine physical and digital risk. Hardware failure, software defects and AI driven outputs can all give rise to liability, sometimes with real world consequences.
This requires a more nuanced approach than traditional software contracts, including:
- clearly defined service levels and performance metrics
- allocation of responsibility between provider, customer and third parties
- treatment of customer dependencies, including connectivity, information inputs and operating conditions
- appropriate limitations of liability reflecting the blended risk profile
- treatment of operational disruption and downstream loss
In particular, liability needs to align with who controls each element of the system, including hardware, software and data inputs.
Key Terms in RaaS Agreements
While structures will vary, several areas are consistently critical:
- Service scope and delivery model
Clear definition of whether the offering is licensed, managed or outcome based.
- Support, maintenance and service levels
Robust SLAs covering uptime, fault response, repair and replacement obligations.
- Exclusivity and usage restrictions
Whether customers receive exclusivity and how their use of the system is limited.
- Data rights and usage
Allocation of rights to access, use and exploit system generated data.
- IP ownership and licensing
Protecting core technology while enabling effective use by the customer.
- Change Management/ Control
Catering for updates, upgrades and evolving customer requirements
- Termination and exit
Including treatment of hardware, continuity of service and data access on exit.
Supply Chains and Integration
RaaS models often depend on complex, multi party supply chains, including hardware manufacturers, software providers and integration partners. Misalignment between these arrangements can create significant exposure.
RaaS models often depend on a network of hardware manufacturers, software providers, cloud service providers and integration partners. As a result, performance issues may stem from multiple sources, making it important to clearly allocate responsibility for defects, delays and service failures across the delivery chain.
Particular care should be taken to ensure that customer-facing obligations are supported by corresponding rights and protections in upstream supplier contracts. Service levels, warranties, indemnities and liability caps should be reviewed holistically to identify any gaps in responsibility or recovery. Failure to do so can leave businesses exposed to customer claims for issues that originate elsewhere in the supply chain.
A well-structured contractual framework helps ensure risk sits with the party best placed to manage it, reduces the likelihood of disputes and provides greater operational resilience as the business scales.
Funding, Procurement and Scalability
Legal structuring also plays a key role in enabling growth. Investors and customers expect clear, robust frameworks that demonstrate control over IP, data and risk.
As robotics businesses move from pilot projects to wider commercial deployment, the legal and commercial structure of the offering can become as important as the technology itself. Customers are often reluctant to incur significant upfront capital expenditure, creating opportunities for alternative funding models.
One approach that may become increasingly common is the use of third-party finance arrangements, where ownership of the hardware is transferred to a funder and the customer pays an ongoing fee for access to the equipment and associated services. Similar models are widely used for medical equipment and other high-value assets, and can make robotics solutions more accessible while providing providers with improved cash flow and greater revenue certainty.
Whatever model is adopted, contractual arrangements should clearly address ownership, maintenance responsibilities, termination rights and the treatment of assets at the end of the term. Well-structured legal frameworks can also simplify procurement processes, support investment readiness and help businesses scale more efficiently through repeatable commercial models.
How we Support Robotics Businesses
We advise robotics companies on implementing legal frameworks that reflect how their technology operates in practice and support long term growth. Our work includes:
- structuring and drafting RaaS and complex commercial agreements
- advising on IP ownership, licensing and protection strategies
- supporting data protection compliance and data governance models
- addressing AI related risks, including training data and outputs
- aligning contractual frameworks across supply chains and delivery models
- advising on equipment ownership, leasing and hire structures to support flexible deployment models
- supporting the implementation of funded and third-party finance arrangements.
Why it Matters
Early legal input helps avoid common issues such as unclear IP ownership, loss of control over data and gaps in liability between multiple parties. It also ensures that contracts are scalable, investor ready and aligned with the commercial model.
Our focus is on providing clear, practical advice tailored to technology led businesses. By combining expertise in IP, data protection, AI and commercial contracting, we support robotics businesses in deploying and scaling their solutions with confidence.
Amy Ralston is a Partner at Stephens Scown and leads the firm’s technology offering, advising clients on complex commercial, IP, data protection and AI related matters. Tim Lane is a Senior Associate with extensive experience in procurement, supply chain management and commercial law, supporting clients with practical and commercially focused advice across complex contractual arrangements.