According to a recent LinkedIn post from Bria, the company is drawing attention to research from MIT indicating that only about 5% of custom-built enterprise AI solutions reportedly deliver meaningful returns on investment. The post suggests that many enterprises struggle because they attempt to build specialized AI capabilities on top of general-purpose infrastructure, creating an “architecture gap” that limits real-world adoption.
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The company’s LinkedIn post highlights a new white paper that outlines why custom AI builds may fail, what prevents internal teams from using deployed tools, and how organizations might join the minority of projects that successfully scale enterprise AI. The post also emphasizes governance, alignment with EU AI Act compliance, and scalability as key design principles of Bria’s platform, which may position the firm to capture spending from enterprises seeking more reliable ROI from AI initiatives.
For investors, this focus suggests Bria is targeting a pain point in enterprise AI deployment—conversion of pilot projects into scalable, ROI-positive systems—which could support demand for its offerings if customers validate the claimed benefits. By aligning its platform messaging with regulatory readiness and adoption challenges, Bria may be aiming to differentiate itself in a crowded generative AI and MarTech landscape and potentially strengthen its competitive position as enterprise AI budgets expand.