AI reality check: Here's what three companies learned building wallets, homes, and games

2026-04-27 · Source: The Register: Enterprise Technology News and Analysis · Field: Business & Management — Corporate Strategy & Leadership, Operations & Process Management, Project & Product Management · Depth: Intermediate, medium

Summary

Executives from Citi, Depot, and Capcom shared their experiences deploying AI agents in customer-facing and internal operations at Google Cloud Next. Citi introduced "Citi Sky," a client-facing agent for wealth management, aiming to capture more of its clients' $5 trillion held at other banks by providing auditable, consistent portfolio reviews and interactions. Depot extended its "Magic Apron" agent from its website to in-store and phone systems, using Google's BigQuery, Gemini Enterprise, and ADK framework to ensure consistent customer guidance across channels, resulting in higher conversion rates and faster call resolution. Capcom deployed AI agents to automate repetitive game testing, saving 30,000 hours per month per project and allowing human developers to focus on creative tasks.

Key takeaway

For CTOs and VPs of Engineering evaluating AI agent deployments, prioritize robust governance and auditable systems from day one. Your teams should integrate compliance controls and treat agents as employees to manage risks, especially when agents handle financial transactions or critical customer interactions. Focus on building portable agent frameworks to ensure consistent customer experiences and maximize efficiency across all your business channels.

Key insights

AI agents are moving into critical business functions, demanding robust governance and system design for reliability.

Principles

• Treat AI agents as employees for compliance.
• Consistency across channels drives customer trust.
• Automate repetitive tasks to free human creativity.

Method

Citi layered safeguards and compliance over Google's stack, treating its agent as an employee. Depot used BigQuery, Gemini Enterprise, and ADK framework for consistent agent deployment across channels.

In practice

• Implement auditable digital records for agent interactions.
• Design systems for agent portability across customer touchpoints.
• Utilize AI agents for high-volume, repetitive testing.

Topics

• AI Agents
• Wealth Management AI
• Retail Customer Experience
• Game Development Automation
• AI Governance

Best for: CTO, VP of Engineering/Data, Executive, Director of AI/ML, AI Architect, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by The Register: Enterprise Technology News and Analysis.