# AI, Agents in Finance and io.Intelligence: Podcast with Bob Myers by WatersTechnology

**URL:** <https://community.interop.io/t/ai-agents-in-finance-and-io-intelligence-podcast-with-bob-myers-by-waterstechnology/341>\
**Category:** io.Intelligence\
**Created:** [November 7, 2025, 3:00pm UTC](https://community.interop.io/t/ai-agents-in-finance-and-io-intelligence-podcast-with-bob-myers-by-waterstechnology/341 "2025-11-07T15:00:07Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![toni.petrov](https://yyz2.discourse-cdn.com/flex028/user_avatar/community.interop.io/toni.petrov/32/17_2.png) [@toni.petrov](https://community.interop.io/u/toni.petrov)\
**Post date:** [November 7, 2025, 3:00pm UTC](https://community.interop.io/t/ai-agents-in-finance-and-io-intelligence-podcast-with-bob-myers-by-waterstechnology/341/1 "2025-11-07T15:00:07Z")

</div>

@robert.myers, Head of the io.Intelligence Unit, was the guest on the latest [Waters Wavelength Podcast](https://www.waterstechnology.com/emerging-technologies/7952778/waters-wavelength-ep-337-interopios-bob-myers) by WatersTechnology.

Listen from the [link](https://www.waterstechnology.com/emerging-technologies/7952778/waters-wavelength-ep-337-interopios-bob-myers) or below.

https://w.soundcloud.com/player/?visual=true&url=https%3A%2F%2Fapi.soundcloud.com%2Ftracks%2F2205795503&show_artwork=true

If you don’t have time to catch the full episode on a Friday, here are some key takeaways.

### **AI is Becoming Proficient in Finance-Related Tasks**

Frontier models can now pass rigorous financial exams like CFA Level 3 with high accuracy. This signals that AI is no longer just a novelty, it’s capable of performing entry-level analyst tasks, such as:

- Running discounted cash flow (DCF) models
- Reviewing earnings reports
- Finding comparable valuations

This means AI can augment junior roles in finance, freeing up human analysts for higher-level strategic work. However, Bob cautions that while models are impressive, they’re not perfect with some benchmarks still showing only ~55% accuracy, so **human oversight remains essential**.

### **Too Many Tools Can Overwhelm AI**

Giving AI access to hundreds of tools (via APIs or MCP) actually reduces its effectiveness.

- AI struggles to choose the right tool when options are too broad.
- Outcomes become non-deterministic - the same request might yield different results each time.

The solution? Human-curated tool bundles. By composing tools into logical, task-specific sets, AI can perform more reliably. There’s a “sweet spot” around **50 tools** =\> beyond that, performance drops.

### **Interoperability is Foundational for AI Success**

Organizations that have already invested in **interoperable systems** (e.g., using FDC3 standards) are ahead of the curve. These systems:

- Declare app capabilities in directories
- Pass context and intents between apps

This metadata is exactly what AI needs to function effectively. So, rather than starting from scratch, companies can **build on existing infrastructure** to integrate AI smoothly.

### **AI Should Enhance Existing Workflows, Not Replace Them Blindly**

Don’t view AI as a business process automation tool. Instead, it should:

- Accelerate validated workflows
- Help users navigate complex systems
- Provide assistive intelligence, not full autonomy (yet)

For example, AI can guide users to the right app or dataset, but humans should still validate outputs, especially in high-stakes environments like finance.

### **Centralized Copilots Are Better Than Fragmented Chat Experiences**

A major UX concern: if every app has its own AI chat window, users will be overwhelmed. Bob recommends:

- A single enterprise copilot that spans all apps
- Unified access to tools and data
- Controlled, permission-aware interactions

This mirrors how companies centralized alerts and notifications in the past. A centralized copilot improves **governance, usability, and trust**.

### **Visualization Still Matters**

Chat interfaces are not ideal for exploring large datasets. Often the better path is:

- Directing users to **trusted visual tools** (e.g., dashboards, charts)
- Using AI to **guide** (not replace) data exploration

Instead of summarizing a time series in text, AI should open a charting app with the relevant data. This preserves data integrity and improves decision-making.