In the two decades since it was coined, “open innovation” has grown into a mainstream business strategy embraced by companies and policymakers alike. Yet many organisations still struggle to fully realise it, often internal barriers (corporate silos, culture) block knowledge-sharing more than a lack of external ideas (Chesbrough, 2023). Now, as technological and market shifts accelerate at unprecedented speed, tapping external innovation sources has become even more critical.
This article is based on a recent research initiative led by Timothy O’Connell. It distills the most current thinking and foundational research on open innovation. The work draws on years of practical experience supporting founders, deep ties to the entrepreneurial ecosystem, and direct insights from faculty, startup operators and innovation leaders across Europe.
The findings point to six cross-cutting trends that will shape how companies, especially large corporates, structure and scale their open innovation strategies over the next decade.
Drawing on the most current thinking and foundational research on open innovation, six cross-cutting trends will shape how organisations practice open innovation over the next decade:
Artificial intelligence is becoming a powerful enabler of open innovation that can “enhance, enable, or replace” traditional innovation practices by generating, filtering, and recombining ideas at a scale humans alone cannot (Stanisławski & SzymaniecMlicka, 2024). For example, AI-driven systems can rapidly scan vast datasets (patents, publications, startup databases) to spot emerging technologies and partners.
AI tools now produce thousands of idea variants in seconds, prompting companies to rethink their innovation process from problem identification to execution (Lane, 2025). The practical upside is faster idea pipelines and broader search scopes. However, executives must also institute robust governance around AI usage in innovation to manage issues of bias, data privacy, and intellectual property.
The research emphasizes blending AI’s speed with human creativity and oversight: the companies that win will train employees to work alongside AI and redesign their innovation workflows accordingly. In short, AI is a force multiplier for open innovation, if used responsibly, it allows corporate innovators to cast a much wider net for ideas and partners while focusing human talent on vetting and implementation.
As open innovation matures, leading companies are moving from one-to-one collaborations toward orchestrating whole ecosystems of partners. Henry Chesbrough observes that the next decade will see a shift to multi-directional knowledge flows across organizations, enabled by digital platforms and networked ecosystems (Chesbrough, 2023).
The role of the “ecosystem orchestrator”, whether a large company, public entity or neutral platform, is to coordinate a network of contributors in creating shared value (Heaton et al., 2025). Real-world examples show the power of an ecosystem strategy. Industrial giant Siemens, for instance, has positioned itself as an ecosystem orchestrator through its open digital platform Xcelerator, inviting a network of partners to co-develop solutions. Siemens shares data and co-innovation spaces, leveraging AI-driven insights to anticipate needs and drive collaborative product development. On the other hand, a Boston Consulting Group analysis found that over 85% of business ecosystems fail, with inadequate governance cited as the number one reason, more than half of ecosystem failures are due to core governance issues like poorly defined participant roles and decision-making right, often manifesting as conflicts over how to share the value created among partners (Daniel et al. 2023).
The lesson for corporate innovators is clear: treating partners merely as vendors or leaving multi-party collaboration to chance is a recipe for attrition. Instead, companies should invest in robust ecosystem governance and “adaptive” orchestration, adjusting the model as the network evolves.
Open innovation is increasingly intertwined with sustainability goals that demand collaboration well beyond company boundaries. In this context, the quadruple-helix model (Yun et al., 2020) has become a defining framework for how innovation ecosystems evolve. Building on the classic “triple helix” of industry–academia–government collaboration, the quadruple helix adds a fourth dimension, civil society, recognising that citizens, NGOs, and communities play a vital role in shaping, testing, and scaling sustainable solutions.
In practical terms, this model positions sustainability not as a side activity but as a shared operating system where multiple actors co-create solutions to societal challenges, from climate change to public health, by sharing knowledge, data, and infrastructure (Wilson et al., 2024).
A clear illustration came during the COVID-19 pandemic: unprecedented open collaboration among governments, corporations and universities accelerated the development of vaccines and therapeutics. These efforts showed that openness isn’t just altruistic, it can be a strategic response to systemic crises, yielding faster solutions when diverse players pool knowledge (Chesbrough, 2020). For corporates, the takeaway is that sustainability-focused innovation works best when they actively engage all four helices as equal partners. Whether it’s co-creating circular economy solutions or setting industry standards for ESG, companies should leverage open innovation platforms to combine their resources with the expertise of others. By doing so, they not only accelerate problem-solving but also build public trust and alignment, increasingly important as customers and regulators look for genuine, large-scale impact rather than isolated “optics.”
The research underscores that digital transformation and a company’s absorptive capacity (its ability to recognize and integrate external knowledge) act as twin engines powering open innovation performance. Investing in advanced digital technologies can significantly enhance a firm’s capability to sense external ideas and collaborate at speed (Kim et al., 2024). For instance, digital transformation boosts open innovation outcomes primarily by building dynamic digital capabilities which in turn improves the ability to source and implement outside ideas (Qiu & Chang, 2025). Crucially, the benefits are greatest in volatile, high-tech environments where agility is at a premium. Firms that heavily adopt Industry 4.0 technologies (like IoT, automation) and cultivate strong absorptive capacity see far greater returns from open innovation projects.
In other words, digital investments need to go hand-in-hand with organizational learning processes, training talent, knowledge management, R&D partnerships, to effectively absorb and apply new knowledge (D’Angelo et al., 2024). Digital infrastructure (from secure cloud workspaces to blockchain IP tracking) also helps democratize access to innovation by enabling smaller or geographically distant partners to participate on equal footing (Xie et al., 2023). The lesson for innovation leaders is two-fold: double down on digital capabilities that help your team discover, share and develop ideas faster, and invest in your people’s capacity to absorb and apply new external knowledge.
Another prominent trend is the rise of internal venture building and corporate entrepreneurship as a way to turn open innovation into tangible new businesses. Rather than relying on traditional R&D alone, large companies are increasingly adopting startup-like approaches, forming internal venture teams, incubators, or spin-off ventures, to capitalize on external ideas and emerging technologies. Henry Chesbrough and others note that while big firms can’t behave exactly like lean startups, they can import entrepreneurial methods (rapid experimentation, MVPs, hypothesis testing) and give internal teams more autonomy to explore novel opportunities uncovered via open innovation (Chesbrough, 2020).
Companies are also embracing models like accelerators, venture client programs, and corporate venture capital to feed their internal innovation funnel. For innovation executives, the message is to treat internal entrepreneurship as a disciplined capability. That means providing budget, C-level support, and appropriate governance to venture teams. In sum, open innovation should not remain a buzzword or a siloed scouting activity, it needs to feed into a robust corporate entrepreneurship pipeline.
Those firms that build this capability will be able to incubate the “next big things” in-house (or in partnership), ensuring that external ideas translate into concrete growth opportunities and not just PowerPoint presentations.
Finally, companies are learning that to fully profit from open innovation, they often must reinvent their business models. Research encourages firms to experiment with models like platforms, subscriptions, or data monetization that align with open knowledge flows (Lu & Tucci, 2024). In practice, we see this in some of the most successful companies today.
A classic example is Rolls-Royce’s “Power by the Hour” model for jet engines: instead of selling engines outright, Rolls-Royce leases them and charges airlines by hours of operation, essentially turning a product into a service. This kind of servitization is a form of open innovation in itself, as it “externalizes” what used to be internal assets and relies on ongoing knowledge exchange and collaboration between the company and its customer. For corporate managers, the takeaway is to always consider the business model implications of open innovation initiatives. Ask: if we source this technology externally or co-create with partners, do we need a new way to capture value? Perhaps the innovation should be delivered “as a service”, or maybe intellectual property could be openly licensed to spawn an ecosystem (as Tesla did by opening some of its patents).
Open innovation often expands the pie, but you need a strategy for your slice of that larger pie. Firms that innovate not only the product but also the business model can better monetize collaborative innovation. The next decade will reward organizations that are as creative in designing business models as they are in designing new products and technologies.
In an era defined by exponential technological progress and AI-driven acceleration, innovation leaders must look beyond their internal R&D to harness the full potential of external ideas, partners, and ecosystems.
The research and practice reviewed here point to six imperatives shaping the next generation of open innovation:
The companies that thrive in this new landscape will be those that see openness not as a trend, but as a core operating principle, embedding collaboration, experimentation, and ecosystem thinking into every layer of their innovation strategy.
Timothy O’Connel
