Reporting and Analytics Augmentation: Faster Insight and Self-Service Analytics
The business value belongs to the analytics function and the business users it serves,
Predictive Maintenance and Asset Intelligence: Downtime Reduction and Capital Efficiency
The business value belongs to operations and reliability, with finance as a co-owner, and
Operational Process Automation with AI Routing: Cost Reduction and Throughput
The business value belongs to operations, and it should be stated by operations before
HR Platform AI for Attrition Prediction and Skills Matching: Retention and Workforce Planning
The business value belongs to HR, and it should be defined by HR before
Conversational AI and Internal Chatbots: Employee Productivity and Knowledge Access
The business value belongs to the operating functions that field repetitive questions, HR, IT,
Risk Scoring and Credit Decisioning: Loss Reduction and Regulatory Defensibility
The business value belongs to the risk and lending functions, and it has two
Customer 360 and Personalization at Scale: Revenue Growth and Retention
The business value belongs to the functions that own the customer relationship, marketing, digital,
ERP-Embedded Financial Anomaly Detection: Audit Readiness and Cost Control
The business value belongs to finance, and the controller or CFO should define it
Generative AI for Content and Communications: Content Velocity and Personalization at Scale
The business value here is owned by marketing and communications, and it is worth
Demand Forecasting and Supply Chain Optimization: Margin and Inventory Efficiency
The business value belongs to operations and finance, and they should define it before
CRM-Embedded Lead Scoring and Next-Best-Action: Sales Efficiency and Pipeline Conversion
The business value here is owned by sales, and it should be stated by
Where to Start with AI Use Cases: Business Value First, Then the Honest Cost of Delivery
The question organizations ask most often about AI is some version of this: which
Why Many Organizations Think They Are Scaling When They Are Still Stabilizing
Part of the Data and AI Journey series. In the cornerstone article, the journey
What Mature Looks Like When the Swimlanes Are Uneven
Part of the Data and AI Journey series. In the cornerstone article, the journey
How to Tell Which Phase You Are Actually In
Part of the Data and AI Journey series. In the cornerstone article, the journey
You Cannot Navigate What You Cannot See: Enterprise Architecture and the Data & AI Journey
I have watched the same pattern show up enough times that it feels worth
The Data and AI Journey Is Whitewater, Not a Roadmap
The data and AI journey rarely feels like a roadmap. It feels more like whitewater, where data, systems, workflows, vendors, regulation, and risk all shape how cleanly an organization can move.
Sequencing the Data Function Development
As a data function becomes more central to the business, the conversation usually changes.
A Data Function Has to Be Designed to Deliver
There is a point in a lot of organizations where the data conversation starts
What Emerging Guardrails Mean for the Data and AI Journey
The Data and AI journey hasn’t had a clear rulebook. Most organizations had
Claude Fable 5 is making the next stage of the Data and AI journey harder to ignore
What caught my attention with Claude Fable 5 was not just the model itself.
Quantum may not be mainstream yet, but the data risk is here
Quantum is one of those topics that is easy to put in the wrong
Keeping the Data and AI Journey on Course
One of the things I appreciate about working in Data and AI right now
Seeing the Journey Clearly Is One Thing. Moving Through It Is Another.
After five articles on this Data and AI journey, I do not think the
When Good Strategy Still Does Not Move
May 28, 2026 A lot of organizations are having the right conversations right now.
Before You Argue About KPIs and OKRs, Be Honest About the Journey
May 27, 2026 If your leadership team is already arguing about KPIs versus OKRs
KPIs and OKRs Both Matter. Timing Is the Harder Question.
May 26, 2026 Most organizations have heard both terms. KPIs. OKRs. They come up
The Signals are Starting to Stack
May 21, 2026 Wow, the developments keep coming, and what is starting to matter
Who Owns Building Business Value KPIs When You Are Still Early in the Journey?
One of the harder conversations in an early-stage data and AI journey is not
What If Your Data and AI Work Was One Coherent Journey?
May 18, 2026 Last week featured another good discussion, and it helped me see
AI Does Not Fix Broken Work on Its Own
May 14, 2026 A lot of the excitement around AI is understandable. A new
Human in the Loop Is Not Enough
May 13, 2026 A lot of the AI conversation right now is about speed.
What AI Changes First
May 12, 2026 What I keep noticing in the current AI conversation is how
Embracing the Benefits of AI while Addressing the Risks
May 8, 2023 Disclaimer: This article was generated with the assistance of ChatGPT, an
Are Your Research Teams Already Using GenAI?
I'm going to switch up topics for this Friday. Normally I focus
Two Rule Changes That Look Like Simplification but Require More Thinking, Not Less
Two major rule changes came out of April, and both are getting a lot
The Shadow AI Problem Credit Unions Cannot Afford to Ignore
There is the AI program most institutions can describe pretty clearly. The approved tools.
AI Ethics Is Not a Values Statement. It’s an Operational Requirement
April 29, 2026 Most credit unions do not need to be convinced that AI
What AI Actually Costs: The Budget Conversation Most Boards Are Not Having
April 28, 2026 The invoice answers one question about AI. The operating budget answers
When Mergers Meet Data: The Governance Challenge
April 23, 2026 Credit union mergers get announced with language about shared mission, expanded
Before Signing an AI Vendor Contract: The Questions That Build Better AI Partnerships
April 22, 2026 The Questions That Build Better AI Partnerships AI is now woven
AI Exam Readiness: What Happens When There Is No AI Examination Playbook Yet
April 21, 2026 There is a version of exam prep that a lot of
Fraud, Risk & Financial Crime: Both Sides of the Transaction Now Have a Job
April 15, 2026 For most of banking history, the fraud problem was essentially unauthorized
AI Adoption in Practice: The Gap Between Enthusiasm and Execution
April 14, 2026 The conversation about AI has shifted, and I keep noticing it
How GenAI Helps Me Turn Techno-Speak into Strategy Without Losing My Voice
March 20, 2026 I will admit it: I am a true techno-geek at heart.
Enough Theory: How to Make AI Actually Work on a Monday Morning
March 19, 2026 One thing I always appreciate about events like Gartner and CULytics
The Uncomfortable Question: Who Actually Owns AI in Your Credit Union?
March 18, 2026 One of the more interesting conversations I keep hearing this week
Trust is Our Only Real Currency: How to Innovate with AI Without Breaking Things
March 17, 2026 Innovation moves fast. In our world, though, trust moves everything. As
Stop Building Dashboards. Start Building Actions.
March 16, 2026 We have more dashboards today than at any point in credit
What If We Measured AI by Members, Decisions, and Trust?
March 15, 2026 We've been asking the wrong question. Not entirely wrong
Digital Trust Is Quiet Until It Isn’t
March 6, 2026 Here’s the thing about security and resilience: when they’re
Mergers Are One of the Best Opportunities We Get
March 5, 2026 Mergers get evaluated like math, and I get why. Assets, market
How We Talk About Technology Investment Matters as Much as What We Invest In
March 4, 2026 In yesterday’s post, I talked about using journey mapping and
Getting Full Value From the Technology We Already Have
March 3, 2026 Something I’ve been thinking about lately: a lot of credit
Collaboration as Competitive Advantage
March 2, 2026 We can’t outspend megabanks on AI infrastructure. We can’t
Keeping the Momentum: What You Can Do Next
March 2, 2026 Over the last couple of weeks, we have covered governance, data
Your Data Strategy Should Enable Your Business Strategy
February 27, 2026 Early in most organizations’ data journeys, data strategy lives in its
When to Build Comprehensive Governance
February 26, 2026 At the start of this series, I opened with a simple
Three Governance Controls You Can Implement Regardless of Team Size
February 25, 2026 Across credit unions and other regulated financial institutions, a consistent pattern
What ‘Premier Member Service Through Responsible AI’ Actually Looks Like
February 25, 2026 Everyone agrees AI should be "responsible." Fewer organizations can
Build, Buy, or Partner?
February 24, 2026 Build, Buy or Partner is a question all organizations wrestle with.
Purposeful Personalization
February 23, 2026 In financial services, it feels like personalization has become a default
Treasury’s AI RMF Is a Milestone. The Next Step Is How We Turn It Into Practice
February 22, 2026 This week's release of the U.S. Treasury'
Right-Sizing Your Data Team
February 20, 2026 Most executives eventually ask: “How big should our data and AI
Why Data Transformations Stall (And It’s Rarely Just the Technology)
February 19, 2026 Here’s a stat that should make every executive pause: roughly
The Shared Responsibility Model
February 18, 2026 Yesterday we explored why AI governance still matters even if your
AI Governance Isn’t Just for Organizations Building AI In-House
February 17, 2026 Most AI governance advice assumes you’re building models in-house. If
Beyond the AI Flavors: A Closer Look at AI Agents and Agentic AI
February 15, 2026 Hopefully, most now have a working picture of “AI tools”—fraud
AI Without Ethics Isn’t Innovation—It’s a Liability
February 14, 2026 There’s an uncomfortable truth the AI hype cycle tends to
A Non-Technical Guide to AI: What Credit Union Leaders Actually Need to Know
February 13, 2026 If you feel like AI terminology is multiplying faster than your
The Data Quality Standard That Actually Matters: “Fit for Purpose”
February 12, 2026 Most credit unions quietly apply a “gold-plated” standard to all data
Know Your Data Maturity Level (And Be Honest About It)
February 11, 2026 There’s a meaningful difference between being data-aware and being data-driven.
Three Questions to Right-Size Your Data Strategy
February 10, 2026 The best data strategy is the one you can actually execute.
Why Your Data Governance Should Match Your Organization’s Reality (Not Someone Else’s)
February 9, 2026 We’re starting with governance intentionally. The NCUA is increasingly asking
Data & AI Leadership for Credit Unions: Pragmatic Strategy in a Regulated World
February 6, 2026 Recently I have been having numerous discussions revolving around data, AI,