At World Summit AI 2025, one theme surfaced repeatedly across keynotes, panels and enterprise case studies: while artificial intelligence is becoming ubiquitous, the way companies are deploying it is creating fundamentally different growth trajectories — and, increasingly, different capital requirements.
As explored in our recent 5 Key Takeaways from World Summit AI 2025 blog, a clear divide is emerging between organisations built around AI from inception and those integrating AI into existing business models. This distinction is shaping not just technology strategy, but how companies grow, invest and finance their next phase.
AI-native companies treat AI as the foundation of their product, not a feature layered on top. At World Summit AI, these businesses were often presenting entirely new use cases — from autonomous agents that orchestrate multi-step workflows to systems that interpret complex data inputs in real time.
These companies tend to move quickly once product-market fit is established. Growth often requires sustained investment in engineering talent, infrastructure and go-to-market execution. What often distinguishes successful AI-native companies is not the sophistication of the model, but how quickly they translate technical capability into repeatable commercial use cases. Importantly, many founders in this category are keen to scale without diluting ownership too early, particularly once recurring revenues or contracted customers are in place.
This creates a natural role for non-dilutive capital to support expansion — funding growth, infrastructure or working capital while allowing management teams to maintain strategic control.
By contrast, many established businesses at the summit were focused on applying AI to existing operations. Rather than launching new AI-first products, these organisations are using AI to improve forecasting, automate workflows and unlock efficiency across core functions.
In enterprise-focused sessions, speakers highlighted how AI adoption is often incremental but cumulative — improving margins, reducing friction and strengthening decision-making over time. These companies typically have predictable cash flows and proven customer bases, but face upfront costs tied to integration, talent and systems transformation. The challenge here is rarely ambition; it is execution — integrating AI into legacy systems without disrupting what already works.
For businesses in this category, debt capital can play a supporting role by funding AI implementation and operational upgrades without disrupting existing equity structures.
What became clear at World Summit AI is that AI-native and AI-adopting companies may be using similar technologies, but they face very different scaling challenges. In practice, the risk for many businesses is not choosing the wrong AI strategy — but funding the right strategy with the wrong type of capital.
AI-native businesses often need capital to accelerate growth once early traction is proven. AI-adopting businesses tend to invest to modernise and defend their market position. In both cases, access to flexible funding can determine how quickly companies move from strategy to execution.
At Fuse Capital, we work with both profiles — supporting businesses that are building AI-driven products from the ground up, as well as established companies using AI to strengthen and scale their operations. The common thread is a focus on growth that aligns capital structure with long-term strategy.
The takeaway from World Summit AI 2025 is not that one approach is better than the other. It’s that understanding how a company is using AI is critical to understanding how it should scale.
As AI continues to reshape business models, companies that align their technology strategy with the right growth capital will be best placed to move from adoption to impact — and from innovation to sustainable scale.