We built a global ecosystem. Now we need a way to keep it moving
How collective intelligence will define the next era of the semiconductor industry.
By Thelma Onyeka, Co-CEO & Co-Founder of Beebolt
Globalization has been this steadily expanding pool of opportunity for decades. For the high-tech industry, trade growth meant that companies gained access to capabilities, materials, and markets that no single region could provide alone. It’s an interconnectedness that’s accelerated innovation and helped build the modern semiconductor ecosystem.
But the same networks that enabled this growth have also made the sector uniquely vulnerable. Supply chains, trade systems, and regional alliances are now so tightly linked that disruptions move through value chains, and if it impacts one, it impacts many.
A quick Google will prove the point, but there’s no shortage of disruptions and challenges semiconductor firms face.
The chip shortage of 2021/22 is the most obvious example of a recent - fairly cataclysmic - disruption specific to the high-tech industry. Its fallout resulted in the automotive industry halting operations altogether, not accounting for the long-term ripple effects.
But the reality is, this is only a single, well-known example within a pool of increasingly prevalent disruptions. Export controls, tariffs swings, rare earth bottlenecks, memory shortages, lead time challenges - I could go on, but this is an all-too familiar list of potential disruptions for firms and fabs and everyone in between.
Headline or no headline, industry-stopping or not, the level of impact doesn’t change the fact that in 2026, they’re near-daily occurrences. And it’s having a significant effect on our global structures.
To keep pace with the scale and complexity of this ecosystem, the industry needs a new model of intelligence - one built for the ecosystems that connect them.
Why isn’t there a solution?
To address the most obvious question first. It’s not that we don’t have one, per se, it’s that we don’t have a viable one.
The systems currently in place are designed to aid optimization within an organization - not within an entire ecosystem. They’re designed to close gaps and enhance decision-making across departments - not across firms and regions.
It’s less about a lack of intelligent technology, and more about a lack of collective intelligent technology. We face shared problems that don’t have shared solutions.
This is where AI applications alone fall down. AI models are designed to optimize for a single objective within a single organization. They can’t collate and analyze relevant data points from across a system which is inherently reliant on the actions and decision-makings of one another. AI can’t reconcile conflicting incentives across organizations, create shared situational awareness, or coordinate collective action.
A far more connected intelligence model is required to meet the needs and demands of a rapidly developing industry.
The solution is us
A mode of intelligence designed for groups, Co-Intelligence™ enables people, organizations, and systems to develop shared understanding and act in coordination across entire ecosystems.
Think of it as connective tissue. The model is a layer of intelligence which sits between industry players to close the gaps around strategy, market insight, collaboration, visibility and so on. Where most intelligence systems today are built for internal use, Co-Intelligence is a structural shift in how information is created, interpreted, and acted upon across complex systems.
It’s dynamic, not static; shared, not siloed; and critically, it’s ecosystem-wide, not organization-centric. And for an industry that’s historically struggled with these core principles, the potential is significant.
Here’s a scenario.
A specialty gas supplier in Japan detects an early production constraint that could reduce output by 10% in the coming weeks. On its own, it looks minor - but that gas is essential for lithography steps across fabs in Taiwan, South Korea, and the US. Traditionally, each company would only see its own slice of the issue, and by the time the shortage became visible downstream, fabs would already be adjusting schedules and OEMs searching for alternatives.
With Co‑Intelligence, that early signal becomes a coordinated response. The supplier’s alert is shared securely across the ecosystem, AI models map the impact on fab capacity, logistics, demand and so on, meaning partners can synchronize maintenance, inventory, and production plans. What would have become a multi‑quarter disruption could be resolved before it even reaches the market.
This is the practical potential - and huge real-life value - of Co‑Intelligence: a small upstream signal becomes collective action across the entire network. Minimal to no disruption. No headline news. No stock performance decline. BAU.
And this isn’t a vague concept. The model, in some form, is already taking shape in the industry.
Early adoption by early adopters
In an early form, yes, but Co-Intelligence is already making its way in the market.
TSMC has begun building shared intelligence layers with its supplier network, integrating readiness data, logistics signals, and customer forecasts into a common environment, meaning risks can be identified earlier and production schedules to be synchronized more tightly across partners.
Intel is taking a similar approach through its IDM 2.0 strategy, while Samsung is using AI‑enabled intelligence to harmonize demand signals and production planning across its semiconductor, mobile, and consumer electronics divisions.
Regions are moving in the same direction - the US CHIPS Act programmes and EU Chips Act being two examples. These emerging forms of Co-Intelligence demonstrate there’s a strong appetite for a shared intelligence infrastructure.
The long-term, far-reaching impact is revolutionary, much of which we can’t measure yet. Innovation cycles will shorten, recovery from disruptions will be exponentially faster, risk and associated costs will be reduced, and overall value will accelerate.
The high-tech industry will reap the rewards, but it’s just as valuable to see the potential in our wider systems. On a fundamental level, Co-Intelligence can speed up the end-to-end lifecycle of semiconductor manufacturing. But the resulting impact can shift how we view global ecosystems; it has the potential to boost economies, create more equitable societies, develop critical infrastructure, establish better healthcare and so much more.
Conclusion
The semiconductor industry has reached a point where its greatest strength is its greatest risk.
The systems that enable growth can no longer absorb the pace, scale, and complexity of modern disruption. We’ve built an ecosystem where every breakthrough depends on hundreds of interdependent actors, yet the intelligence guiding those actors remains fragmented, siloed, and fundamentally misaligned with how the industry actually operates.
We benefit together, we break together.
Co‑Intelligence turns that on its head. It doesn’t eliminate complexity, it makes complexity manageable, predictable, and strategically advantageous.
With collective intelligence, we can transform isolated signals into shared understanding, isolated decisions into coordinated action, and isolated optimizations into ecosystem‑wide resilience.
Faster recovery, shorter innovation cycles, reduced risk, and greater value creation are only the beginning. The future of the high‑tech industry - and the global systems it powers - depends on our ability to think, act, and adapt collectively.
It really is as simple as that. The 2026 Semiconductor Supply Chain Survey is currently live on Conductor™ to gather insights for collective action. Add your views anonymously for a stronger pulse on the semiconductor ecosystem.
