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#38: 80% of Finance Teams Want AI Agents - But They Don’t Trust Them Yet

#38: 80% of Finance Teams Want AI Agents - But They Don’t Trust Them Yet

AgentPulse: Your Weekly Dose of AI Agents News.

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July 30, 2025

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In today’s Agent Pulse:

📢 Top Headlines
⚔️ Agent Arena
✨ Featured Agents
📡 Agent Signals
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🗺️ Landscape Map

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📢 TOP Headlines

Deloitte Survey: 80% of Finance Pros Are Ready for AI Agents, but Trust Is the Barrier

A new Deloitte poll (July 29, 2025) reveals that 80.5% of finance and accounting professionals expect AI agents to become standard tools within five years. But only 13.5% of organizations are already using them, and 21.3% say trust remains the key blocker to adoption.

What Deloitte Found:

Most respondents see efficiency gains (42.7%), better reliability (12.4%), and sharper insights (26.3%) as major benefits.
However, trust in agent-generated output, especially around financial data, compliance, and accuracy, is the dominant concern.
Other hurdles include systems integration (20.1%) and lack of skilled operators (13.5%).

Why This Matters for Agent Builders:

The finance function is one of the most conservative environments. If agentic AI can win trust there, it can win trust anywhere.

But winning trust won’t come from building bigger models - it comes from designing for explainability, auditability, and governance from Day 0.

Google ADK + AMD Instinct: The New Agent Stack

Google’s Agent Development Kit (ADK) now runs natively on AMD Instinct MI300-series GPUs, marking a key shift: scalable, agentic workloads no longer require cloud lock-in.

Why it matters:

Open agent infra is here: ADK + AMD offers a flexible, model-agnostic, Python-native way to build multi-agent systems that run on your own hardware.
Massive throughput: MI350X GPUs bring 288 GB HBM3E and up to 8 TB/s memory bandwidth, ideal for concurrent agent execution and long-context reasoning.
Cost-effective scaling: Running fleets of agents locally (or via AMD’s dev cloud) drastically lowers costs vs. cloud LLM APIs.

The big shift:

Agent infra is maturing. We’re moving from toy demos to production pipelines - and this combo opens the door to:

On-prem agents for compliance-first orgs
Custom, multi-agent systems beyond LangChain/CrewAI
Edge inference for verticalized use cases

Bottom line: ADK + Instinct forms a real alternative to closed stacks. Open hardware + open agents could define the next wave of AI-native software.

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⚔️ AArena: All-in-One AI Workspace

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👉 Battleboard

✨ Featured Agents

TeammatesAI: Autonomous AI Teammates
OraczenAI: Build agentic systems
TensorStax: Autonomous AI Agents for Data Engineering
TheLibrarian.io: WhatsApp AI Personal Assistant
Agentverse: Search and Discover AI Agents

📡 Agent Signals

Microsoft introduces Copilot Mode in Edge browser, turning it into a task-oriented AI agent for web interaction. Source
Rechat launches 'Lucy', an AI agent assistant for real estate agents, offering 24/7 support, transaction insights, and automated marketing. Source
Anthropic has deployed autonomous AI agents to audit models like Claude for safety, acting as a digital immune system to identify and neutralize potential problems. Source
StackGen launched its Autonomous Infrastructure Platform, featuring AI agents (StackBuilder, StackGuard, StackHealer, StackOptimizer) to build and manage cloud infrastructure autonomously. Source
Netcore Cloud's 'State of MarTech 2025' report highlights that Agentic AI is leading to 2X conversions and up to 23% higher campaign performance for early adopters. Source
Writer Inc. launched Action Agent, an autonomous AI 'super agent' for enterprise users, integrating tool use, knowledge work, and deep research capabilities with enterprise-grade control and transparency. Source
LexisNexis launched Lexis+ AI with Protégé in Hong Kong, introducing an agentic AI assistant for legal professionals that can autonomously analyze large documents, draft legal briefs, and suggest workflow actions, leveraging built-in “Protégé” agentic capabilities to accelerate legal work. Source
ONAR Holding Corp. and IQSTEL announced an expanded strategic partnership to develop an AI-driven multi-agent operating infrastructure for marketing agencies, giving each employee and client account dedicated AI agents to automate and optimize agency operations. Source
GPTBots unveiled at the 2025 World AI Conference its new Multi-Agent Collaboration Platform, enabling businesses to build custom “teams” of AI agents for tasks (e.g. finance, real estate, manufacturing) and overcome data silos and rigid workflows. Source

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