AI Adoption for FIs: From Awareness to Infrastructure
Financial institutions are adopting artificial intelligence in three common stages. Allied Solutions CEO Pete Hilger emphasizes that AI improves efficiency and reduces human error but does not replace human judgment.
2025 may be behind us, but the challenges financial institutions faced continue to reverberate. Inverted portfolios, stubborn interest rates, record fraud losses, regulatory pressure, and declining consumer confidence created a demanding operating environment that tested both strategy and resilience.
Amid these conditions, artificial intelligence has emerged as a powerful enabler, but not a cure-all. On the latest The Allied Angle podcast, Allied Solutions CEO Pete Hilger emphasized that while AI can drive efficiency and scale, it cannot replace human judgment.
“Our greatest asset is still the human factor… but the human factor comes with errors. AI can support teams and improve the experience long term.”
Three Stages of AI Adoption
As Allied has invested in market-specific AI, three clear adoption patterns have emerged.
1. AI Awareness, Zero Impact
There’s no hiding under a rock, AI is here. Its potential sparks both curiosity and skepticism. Fear of a poor experience, limited budgets, or unresolved compliance concerns can block adoption, even when education and awareness are high.
This stage typically shows up as strong webinar engagement while legacy systems remain unchanged, or limited experimentation with generative AI tools that wouldn’t withstand compliance scrutiny. Institutions may feel informed, but without action, they continue to fall behind. Avoiding risk also means missing opportunity. At some point, awareness must give way to intentional implementation.
2. Adoption Abyss: Fatigue by Fragmentation
Another common stage is burnout, when AI’s promise doesn’t match reality.
Shiny new tools quickly lose appeal as poor integration, alert overload, and unclear ownership surface. Incomplete connections between the core and surrounding systems can lead to inconsistent communications and board-level questions about ROI.
Fragmented adoption without an enterprise strategy delivers diminishing returns. AI should simplify decision-making, not complicate it. The path forward is AI embedded into workflows, not layered on top of legacy processes. Measurable outcomes are essential to overcoming adoption fatigue.
3. AI as Infrastructure, Not Experiment
During the discussion, Pete encouraged financial institutions to rethink AI not as a collection of tools, but as enterprise infrastructure.
“Imagine a world where you can set up all the data points, give your core processor permission, and it can handle all quantitative data to maximize returns while minimizing risk.”
The critical shift is enabling data to communicate across systems. Integration, not additional tools, breaks down silos and reduces human intervention.
When AI is done right, financial institutions can:
- Separate high-quality data from peripheral data
- Reduce soft costs
- Protect brand reputation
- Support smoother M&As
- Quantitatively grow relationships across generations
- Reduce churn
- Block fraud faster
Each step forward contributes to transformation. For banks, this often means untangling complexity at scale. For smaller institutions, it means achieving enterprise-grade capability without enterprise-sized teams.
The difference between short-term gains and lasting transformation comes down to one shift: treating AI as infrastructure, not an experiment.
An AI-Powered Integration & Data Platform: The Foundation AI Depends On
Moving from experimentation to infrastructure requires a foundation built for connection, not complexity. As discussed on the podcast, AI cannot deliver meaningful results without strong integration and clean, connected data.
Allied’s new strategic partnership and investment in PortX brings an AI-powered Integration & Data Platform that unifies data across the core, third-party providers, and internal systems, creating a reliable foundation for analytics, automation, and decision-making. With seamless data movement, AI becomes more accurate, more explainable, and more effective across risk, fraud, lending, and operations.
By eliminating data silos and reducing integration complexity, the platform enables financial institutions to move beyond fragmented pilots toward AI that is embedded, scalable, and trusted, supporting AI not as a novelty, but as true enterprise infrastructure.
Adoption + Trust = Sustainable Transformation
“Within the last year, we’ve come to realize the many use cases for AI and invested more than ever into it.”
Looking toward 2026 and beyond, Allied Solutions is investing in AI with greater strategic intentionality, providing both our teams and our clients with tools that drive efficiency, clarity, and confidence.
The future of AI is bright, not because it’s effortless, but because it’s capable of reshaping what’s possible for growth, retention, and risk management. Financial institutions don’t just need that momentum, they deserve it.
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