The power of strategic partnerships in AI: Key IP considerations

Catherine Bonner

Brett Landon

Recently, we have seen a growing number of companies in the AI and technology space launch products and platforms forged from deep collaboration and co-development.
Strategic partnerships of this kind can be the result of years of discussion, alignment, and learning to work together for a common launch, but the results are often an impressive and rapid series of announcements.
Strategic partnerships shaping AI development
One such collaboration has been the Arm AGI CPU, co-developed with Meta: a physical server chip built to address the heavy energy and computing demands of large-scale AI.
The two companies are also working on a software and developer ecosystem, with Meta’s AI software working on Arm architecture, as well as its search and ranking software transitioning to the Arm Neoverse platform.
Other names announced earlier this year for projects with Arm include IBM, combining the experience and established position of IBM in system design with the AI and intensive data that comes with Arm’s core business.
Hardware such as the Telum II processor at IBM is the focus of this new investment and collaboration with the aim of bringing AI deeper within the mainframe and operating platforms. The collaboration expands the Arm virtualisation technologies to enable Arm-based software environments to operate in IBM’s enterprise-level computing platforms.
This dual-architecture approach is designed to support the evolution of AI and data–intensive applications within a flexible software ecosystem, without jarring against Telum II processor and Spyre Accelerator platforms.
These examples form part of a much wider picture of collaboration across the AI and technology sector. Arm itself has an extensive partner network, with recent activity involving companies such as Verda, AWS, MediaTek and Xiaomi, demonstrating the breadth of businesses and technologies involved.
The growing focus on strategic partnerships extends well beyond Arm, with these relationships becoming an increasingly prominent feature of announcements across the AI and technology sector.
Why strategic partnerships matter for AI infrastructure
Taken together, these examples illustrate a broader shift towards closer strategic partnerships to deliver AI technology at scale. Bringing together complementary expertise from partners operating in different areas of the technology stack can drive improvements in the performance and efficiency of hardware, software, and overall infrastructure.
The demand for this type of cooperation arises from the increasingly interconnected nature of AI infrastructure, in which different technologies must operate as parts of an integrated system. Individual components can no longer be designed in isolation, because decisions made in one part of the stack can impose requirements or constraints elsewhere.
As a result of this interdependence, conventional supplier-customer relationships are increasingly evolving towards co-design arrangements.
For example, a technology provider may contribute processor architecture and implementation expertise, while a “hyperscaler” may contribute expertise in workloads and deployment at scale. Sharing such knowledge throughout project development allows parties to optimise the system as a whole, so that workload requirements can shape the hardware roadmap while emerging hardware capabilities can inform software and infrastructure optimisation.
Intellectual property in AI collaborations
Close technical collaborations fostered between partnering companies can involve the use of pre-existing technology and know-how, as well as the creation of new intellectual property through their joint work. Furthermore, successful projects may combine proprietary architectures and confidential technical concepts with software intended for open-source release or specifications intended for wider publication. The intellectual property framework must therefore balance the protection of commercially valuable technology against the benefits of openness, while providing the clear ownership and use rights discussed below.
Against this backdrop, IP issues should be addressed at the outset, not left until value has already been created and ownership of rights is uncertain. A collaboration can produce patentable inventions, registrable designs, copyright works, and know-how. If ownership, use rights and filing strategy are unclear, disputes can arise quickly and can undermine the commercial purpose of the arrangement.
Key IP considerations
What IP already exists before the collaboration begins
Each party should identify its background IP, specifically the patents, patent applications, know-how and other rights it brings into the project. The agreement should state clearly that pre-existing IP remains owned by the original owner, and should define exactly what rights the other party has to use it.
What new IP may be created, and who will own it
Collaborative projects often generate foreground IP. The parties should consider what forms of protection are appropriate for the expected outputs. That may include patents for technical inventions, registered designs for product appearance, copyright for software and documentation, and trade secrets for confidential know-how.
It is important for both collaborating parties to be aware of the intended filings of each other, so that public disclosure before filing is avoided. The parties should agree in advance who will own new inventions, who will bear the cost of obtaining IP rights, and who is responsible for enforcing any such rights. Joint ownership and shared costs may appear fair, but it can be difficult to manage in practice because the rules on use, licensing and enforcement vary by jurisdiction. Sole ownership with a defined licence back to the collaborator is often easier to administrate.
Freedom to operate
It is important to consider whether any pre-existing rights may be infringed by the commercialisation of any product developed through the collaboration. The collaboration may develop a valuable product but still infringe third-party patents, design rights or copyright when commercialising it. The parties should therefore consider whether freedom to operate searches or other clearance work is needed, and who will bear the cost and risk.
Confidentiality and trade secret protection
Collaborations often require extensive information sharing. Confidential information should be identified, access should be limited to those who need it, and the agreement should include robust confidentiality obligations. Practical controls also matter, such as data segregation, secure systems, marking confidential material, and exit procedures when the project ends.
Exit and post-collaboration arrangements
The parties should plan for termination at the beginning, not the end. The agreement should address what happens to jointly developed IP, continuing licences, return or destruction of confidential information, handling of ongoing filings, and rights to complete or exploit work already underway.
In practice, the most effective collaboration agreements distinguish clearly between background IP, foreground IP, and use rights, then align those provisions with the commercial objective of the project. If those points are dealt with early, the collaboration is much more likely to produce usable and protectable value rather than avoidable disputes.
Strategic technology partnerships can create significant IP value, but protecting that value starts well before a new product or platform reaches the market.
Our team can help you consider the IP implications of a collaboration from the outset, from existing and newly created rights to freedom to operate and protection strategy.
Get in touch to discuss how we can support your IP strategy.
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