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AI is no longer a pilot project in investment management
The Shift Brief | Week of November 10th
Ryan Erickson
November 11, 2025
AI Scaling Is the Next Competitive Divide in Investment Management
As we move into 2026, Deloitte's latest Investment Management Outlook makes one thing clear: the winners in this next cycle will not be the firms experimenting with AI, but the ones operationalizing it.
For most of the industry, the past two years have been about pilots: generative AI summaries of research, chatbots, or a few productivity gains in operations. But Deloitte's analysis shows a shift from "proof of concept" to "proof of scale." Firms with higher AI maturity are giving 40% of their workforce direct access to AI tools, compared to less than 20% at lagging peers. That's not a technology gap; it's a leadership one.
The real bottleneck isn't model performance; it's integration. AI's ROI has been elusive, not because the algorithms aren't good enough, but because the workflows around them haven't changed. The report highlights that without redesigning how people work with AI, most firms end up automating inefficiency. Analysts still spend hours searching, copying, and formatting data even while sitting next to a powerful model.
This is where the conversation moves from "tools" to "architecture." The firms pulling ahead are building structured data pipelines, governance frameworks, and feedback loops that make AI usable across departments. They're training "AI translators," professionals who can interpret outputs, apply judgment, and communicate risk. In other words, they're designing for human-in-the-loop scale, not proof-of-concept novelty.
Cost savings are table stakes. Differentiation is the real prize. Deloitte notes that many managers still frame AI as an efficiency play. But the emerging use cases (faster idea generation, client-facing analytics, automated compliance summaries) point to growth and differentiation, not just cost cuts. Firms that position AI as an amplifier of intellectual capital will pull ahead of those treating it as another back-office optimization project.
What this means for 2026: Mid-sized managers in the $5B to $250B AUM range face a decision point. Scaling AI isn't about adding more models; it's about re-platforming how research, data, and decisions flow through the firm. Governance, interoperability, and explainability will separate firms ready for enterprise adoption from those stuck in pilot mode.
For technology vendors and platform builders, the opportunity lies in enabling that transition. The market no longer needs AI features. It needs infrastructure that connects data to insight, insight to workflow, and workflow to accountability.
Our Take: Winning firms will be those that turn AI from a pilot into a platform.
Shift is Building the Foundation
This change from pilots to platforms is exactly what we're focused on at Shift. The foundation matters more than the model. Our approach centers on organizing internal data to make it AI-ready, building the infrastructure layer that allows AI to integrate into investment workflows rather than sit alongside them.
Watch this short video to see how we're laying the foundation for firms ready to scale.