Using AI to Support Decision Confidence
This hypothetical, illustrative scenario for regulated growth environments reflects how I approach leadership decisions.
Engagement begins with understanding the client’s team, constraints, and priorities, then translating that perspective into a practical, right-sized execution plan.
This scenario reflects patterns observed across 20+ years in financial services leadership, including SVP-level experience at credit unions managing $4B+ in assets.
Primary Focus:
Metrics & Roles
Roles: CXO, CTO
Metric Focus: Customer Experience, Growth & Acquisition, Risk & Compliance, Operational Efficiency
Scenario Value:
As AI becomes embedded in marketing platforms, institutions must distinguish between novelty and value. This scenario illustrates how senior marketing leadership might use AI to support decision confidence rather than surface-level personalization.
Context:
AI-driven personalization capabilities are readily available, and expectations are high; however, leadership questions whether these efforts are genuinely improving member understanding and outcomes. Marketing activity risks becoming impressive without being impactful.
The Leadership Consideration
Personalization that lacks relevance or clarity can erode trust. AI must enhance confidence, not distract from it.
Marketing leaders must decide where AI meaningfully belongs.
The Leadership Question
- How can AI be applied in marketing to improve decision confidence rather than create noise?
- What decisions does personalization actually support?
- Where does relevance outweigh sophistication?
- How should success be evaluated beyond engagement metrics?
Hypothetical Operating Approach
If engaged, a senior marketing leader would re-anchor AI use to member decision contexts.
Start with moments of uncertainty.
AI would be applied where members commonly hesitate, seek reassurance, or compare options.
Favor clarity over cleverness.
Personalization would emphasize explanation, framing, and guidance rather than novelty.
Measure confidence, not just interaction.
Success indicators would reflect completion, follow-through, and satisfaction—not only clicks or opens.
Operational Impact
Operating Considerations
- Data quality and consent
- Internal expectations around personalization
- Measurement limitations
- Brand voice consistency
Representative Impact Areas
Applied effectively, this approach could reasonably support:
- More meaningful personalization outcomes
- Reduced fatigue from over-targeted messaging
- Stronger alignment between AI use and brand values
- Improved confidence in marketing’s role in decision support
Testimonials
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Eric is a passionate marketer and digital expert who shines in financial services. He’s a natural collaborator full of smart, innovative ideas—a combination of creativity and execution that’s hard to find. He’s the strategic partner who can execute effectively and elevate the people around him.
Chief Experience Officer
What sets Eric apart is his ability to connect the dots between technology, user experience, and business impact. He makes innovation happen by optimizing workflows, championing a customer-first mindset, and leading high-performing teams.
Senior Digital Marketing Manager
What truly stands out about Eric is his exceptional leadership in guiding [a] team through forward-thinking initiatives that drive impactful results. He is a respectful and visionary thought leader who consistently identifies opportunities for immediate success and long-term growth and sustainability.
Senior Product Marketing Director