Generative AI is the most talked‑about technology in financial services, surrounded by bold promises, inflated expectations, and a fair amount of anxiety. But according to Dr. Anna Slodka‑Turner, Global Leader of Risk & Quant Solutions at Evalueserve, cutting through the noise requires a clear understanding of both what AI can do and what it should do. Her message from her article, “Generative AI Reality Check with Dr. Anna Slodka-Turner”, in Vol.3 of Elevate Magazine is simple: real impact comes not from hype, but from grounded, end‑to‑end solutions that solve actual business problems.
1. Real Innovation Starts with a Problem—Not a Cool Technology
The hype cycle pushes organizations to adopt generative AI simply because it’s trending. Anna warns against this “tech‑first” mindset. Instead, she emphasizes that every AI initiative must begin by asking: What problem are we actually trying to solve?
In her article, she shares a formative early-career experience: questioning an inefficient legacy process that didn’t make sense and expecting resistance but receiving encouragement from her boss instead. That moment shaped her leadership and innovation philosophy. True innovation, she argues, begins when someone feels empowered to challenge the status quo, and when leaders respond with, “How can I help?
2. Gen AI Isn’t a Magic Wand—It’s One Layer in a Multi‑Layered Solution
Hype suggests gen AI can replace entire workflows or operate autonomously at scale. Reality? It’s powerful, but only when combined with workflow design, data integration, automation, quantitative models, and strong governance.
In one example, Anna describes a credit staging project where the client asked if gen AI alone could handle the process. The answer: partly, but only when embedded thoughtfully into a broader solution.
3. Human Judgment Still Sits at the Center
One of the strongest myths is that AI will eliminate expert roles, but Anna stresses the opposite: gen AI amplifies expertise rather than replacing it.
For example, for an insurance client, we launched a gen AI-powered underwriting platform that automated the extraction of more than 100 data points. Underwriters, however, still made the decisions, bringing nuance and expertise that models can’t replicate.
4. Data Sovereignty and Compliance Matter More Than Speed
When organizations get swept up in generative AI hype, speed often becomes an obsession: How fast can we deploy? How quickly can we scale? How soon can we automate everything? But Anna reminds us that in regulated industries—especially banking, insurance, and risk functions—speed without control is a risk, not a strategy.
In the article, she outlines a core reality: financial data cannot simply be handed over to any external AI engine. Solutions must run inside the client’s infrastructure to maintain privacy and compliance. This is where data sovereignty becomes a defining factor separating real‑world AI adoption from the hype.
The Bottom Line: AI’s Power Lies in Pragmatism, Not Hype
Dr. Anna Slodka‑Turner’s perspective brings the conversation back to earth. Generative AI is transformative—when it’s aligned with business goals, governed responsibly, and embedded into real processes. It’s not about replacing people, chasing trends, or assuming models will run themselves.
To separate hype from reality, organizations must anchor AI in:
- Clear problem statements
- Multi‑layered solutions
- Strong governance
- Human judgment
- Practical, measurable ROI
These principles ensure that generative AI becomes what it should be: a tool for meaningful progress, not a passing wave of excitement.
