Glia and Alloy Labs have released a joint 2026-2027 Banking AI Strategic Annual Planning Kit, a cross-functional blueprint that gives leadership teams governance templates, an enterprise-wide roadmap, and banking-specific AI deployment strategies. The release targets a documented problem: 80% of financial institutions report that early AI adoption has failed to improve their bottom line.
Alloy Labs CEO Jason Henrichs framed the timing. "This is the first planning cycle where AI strategy and bank strategy are in the same conversation," he said. "Boards are approving budgets for technology that moves faster than any planning process built to contain it-and institutions treating that as a line item rather than a set of strategic choices will spend 2027 explaining why the spend never reached the bottom line."
The gap between pilots and production
The kit arrives as regional and community banks struggle to convert AI investments into measurable returns. AI now tops the technology budget for most banks and credit unions, yet the operational payoff remains elusive. Glia and Alloy Labs designed the resource to help leadership teams redirect that spending toward lower operating costs, higher loan and deposit growth, and stronger account holder retention.
Henrichs described the silence he encounters when asking bank technology leaders about production deployments. "We've sat in rooms full of bank technology leaders and asked how many have a single AI agent in production. Silence. These aren't laggards. They have board mandates and completed pilots. What's missing is the bridge from experiment to strategy, and that's a planning problem, not a technology one. We built this kit with Glia to close that gap."
For executives navigating this shift, resources like the AI for Executives & Strategy discipline have become central to turning board-level mandates into operational reality. The planning kit itself functions as a practical workbook rather than a theoretical document, reflecting the production experience Glia brings to the partnership.
What the planning kit contains
The workbook covers several core areas: using conversational, automated, outbound voice and SMS outreach to increase loan and deposit volumes, and evaluating cybersecurity architectures and regulatory compliance factors to defend against hallucinations, data leaks, and vendor sprawl. It also lays out a Centralized Product Ownership Model for C-suite leadership and a Three-Phase Roadmap designed to scale AI without disrupting existing workflows.
A Universal Banker model framework is included to support workforce development alongside technology deployment. The kit frames AI adoption as a cross-functional effort that requires coordination across compliance, technology, and business lines-not a siloed IT project.
Why this matters for Executives and Strategy
Glia CEO and Co-Founder Dan Michaeli described the pressures converging on the 2027 planning cycle. "Financial institutions are trying to protect their core deposits, keep the next generation from moving their inheritance away, and somehow find growth in a flat market. Throw in talent shortages, compliance headaches, and rising fraud, and the old strategic planning playbook just won't cut it. We built this resource because executives don't need more AI hype. They need a practical blueprint to prioritize their efforts to handle all these pressures at once."
For banking leaders, the kit signals a shift in how AI investments must be managed. Treating AI as a line item rather than a set of strategic choices creates a gap between spending and results. The workbook provides the governance templates and sequencing logic that boards increasingly expect alongside budget approvals. In the AI for Finance context, the planning kit offers a concrete answer to the question of why AI spending has not reached the bottom line-and a path to change that.
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