The sell-off in US tech stocks following the MIT report highlights a growing disconnect between hype and real-world impact. If 95% of generative AI pilots are failing to deliver measurable returns, it’s not a failure of AI as a concept but a failure of approach. The current race to deploy general-purpose, one-size-fits-all systems has left most organisations unable to extract real business value.
Why Sovereign and vertical AI are different
At Aveni, we believe the next phase of AI is not about scaling general models ever larger, but about sovereignty and specialisation:
- Sovereign AI means models built and deployed under the control of governments, institutions and enterprises, ensuring that data sovereignty, compliance, and alignment with national or sectoral priorities are hardwired into the system.
- Vertical AI means tailoring models to the specific challenges of highly regulated, complex industries like financial services, healthcare and energy, domains where accuracy, trust and explainability matter far more than sheer scale.
General-purpose AI struggles in these contexts because it can’t handle domain-specific nuance, regulatory alignment or the ethical standards required. Sovereign and vertical models, on the other hand, are designed for measurable outcomes, embedding compliance, risk management and productivity gains directly into the technology.
From hype to sustainable value
The current market correction is not the bursting of an “AI bubble” but rather the inevitable reset that shifts attention from speculative bets on general models to targeted, high-value applications. The future belongs to those who can prove ROI, not just generate headlines.
At Aveni, we are building FinLLM precisely for this reason: to bring the power of generative AI into financial services in a way that is safe, ethical and regulatorily aligned. The MIT study only underlines what we already know: the majority of organisations won’t see returns from AI until they adopt models that are designed for their industry and operate within their own governance frameworks.
The headlines about failure and hype shouldn’t spook investors or enterprises. They should accelerate the move away from general AI experiments towards sovereign, vertical AI that delivers real-world value. The winners of the next wave won’t be those chasing scale for its own sake, but those who can embed trust, compliance and measurable ROI into the heart of their AI strategy.
