In the dynamic world of open innovation, the allure of AI tools is undeniable. They promise efficiency, vast data analysis, and scalable solutions. Yet, despite these capabilities, the startling statistic remains: a significant percentage of innovation projects fail. Why? Because at the heart of any successful project lies a foundational element that AI cannot replicate—human-centric communication and relationship building.
At yet2, we have long championed the belief that while AI tools have their place, they are not the panacea many hope for. In fact, relying solely on AI may lead organizations to overlook a critical truth: the best decisions in innovation are built on a foundation of high-quality, nuanced information that often resides beyond the reach of algorithms.
The Death of the Spoken Word?
One of the most profound challenges in today’s innovation ecosystem is the erosion of meaningful, human-driven communication. The convenience of digital tools and AI has, in many ways, replaced face-to-face conversations and phone calls with emails, texts, and automated interactions. In the rush to automate and optimize, we have witnessed a decline in the spoken word—the art of direct, human communication that builds trust, establishes rapport, and uncovers the subtleties of non-verbal cues.
When communication falters, projects are at risk of failing—not due to technical shortcomings, but because the teams involved lack alignment, shared understanding, and the trust necessary to overcome obstacles. The simple act of picking up the phone to clarify a detail or foster a relationship is irreplaceable in building a successful innovation project.
Why High-Quality Information Matters
Innovation projects thrive on access to quality information. But not all information is created equal. Publicly available, commoditized data is what AI tools excel at processing, but this information is often generic, outdated, or irrelevant to the unique needs of an innovation project.
The real value lies in non-confidential, non-publicly available information—the kind of insights that emerge from direct human interactions. Consider these examples:
- A supplier divulging a nuanced technical challenge they face in confidence, offering a unique opportunity to co-develop a solution.
- A university researcher explaining unpublished work and its potential real-world applications.
- A start-up CEO discussing market feedback and pivot strategies, revealing new paths for collaboration.
These types of insights aren’t available in online databases or patent filings—they are shared in conversations, in moments of trust, and through relationships built over time. AI cannot crawl this “hidden layer” of the innovation landscape, which is why human-centric scouting remains indispensable.
AI Tools: Not a Magic Bullet
This is not to say that AI tools have no place in open innovation. On the contrary, they are excellent at certain tasks:
- Data Processing: AI can analyze vast amounts of structured and unstructured data at lightning speed, uncovering trends, identifying patterns, and highlighting potential opportunities.
- Lead Identification: AI can help filter through large pools of potential partners, identifying those with publicly stated capabilities aligned to a project’s needs.
- Efficiency Gains: By automating repetitive tasks, AI frees up human experts to focus on strategic, high-value activities.
But herein lies the limitation. AI tools are only as good as the data they process and the algorithms they are built on. They struggle with nuance, lack contextual understanding, and, critically, are not equipped to foster relationships or build trust—both essential for successful innovation projects.
The Power of Human-Centric Scouting
Human-centric scouting fills the gaps AI cannot. It emphasizes the importance of relationship building, nuanced understanding, and uncovering insights that go beyond what is publicly available. For example:
- A yet2 scout having a conversation with a technology provider can uncover not just what the company offers but also their strategic priorities, challenges, and openness to collaboration—information that no AI tool can extract from a website or dataset.
- Through regular communication with innovators, human scouts can sense shifts in motivation or interest, adapting strategies in real time to keep projects on track.
This approach is particularly relevant in industries where trust is paramount, such as pharmaceuticals, advanced materials, and energy. In these fields, sensitive discussions about intellectual property, regulatory challenges, or partnership structures cannot happen without a strong foundation of trust—something only humans can build.
Bringing It All Together: The Future of Open Innovation
The future of open innovation isn’t about choosing between AI tools and human-centric scouting. It’s about leveraging the strengths of both. AI tools can handle the heavy lifting of data analysis and pattern recognition, providing a foundation for decision-making. But the ultimate success of innovation projects depends on human expertise—on individuals who can navigate the nuances of relationships, ask the right questions, and uncover the hidden insights that make all the difference.
At yet2, we believe that every successful innovation project begins with communication and relationship building. The first step isn’t logging into an AI platform or running an algorithm. It’s reaching out, speaking to people, and understanding their needs, challenges, and ambitions.
So, as we embrace the possibilities of AI, let’s not lose sight of the human touch. The future of open innovation will belong to those who can blend the efficiency of AI with the empathy, insight, and trust that only humans can provide. After all, innovation isn’t just about technology—it’s about people.
Words by Patrick Harris
