Archive · 12 Nov 2025
Early Adopters See Value in AI Agents Amidst High Spending Concerns
Imagine companies are trying out new smart robots called AI agents.
Some people worry because these robots are expensive and don't always work perfectly yet.
However, some companies, like a bank called BNY and a store called Walmart, are showing that these AI agents are actually helpful.
BNY uses them to help fix computer code and make the bank run better, which saves them money.
Walmart uses them to make clothes faster, getting new styles to customers much quicker.
These early users say the AI agents are helping them get more work done and are good for business.
While others might wait to see if the robots get even better, these first users are already seeing good results from their 'smart robots.'
Concerns are growing over high AI spending, as few companies have widely deployed AI agents and seen value.
Early adopters like BNY and Walmart are reporting tangible positive outcomes and bottom-line impacts from AI agents.
BNY uses 'digital employees' for tasks like scanning code for vulnerabilities and implementing fixes, reporting increased capacity.
Walmart's AI agent for fashion significantly shortens the product development timeline, from six months to as little as 18 weeks.
Despite some studies showing pilot projects failing to generate returns, early adopters claim AI agents are proving effective and providing real value.
- Who
- Early adopting companies like BNY and Walmart, and AI providers like OpenAI and Salesforce.
- What
- Demonstrating tangible value and return on investment from AI agents, despite widespread concerns about high spending and mixed results from pilot projects.
- When
- Currently, with evidence emerging as more AI agents move out of pilot stages and into wider deployment.
- Where
- In various business operations globally, including financial services (BNY), retail/e-commerce (Walmart), and through SaaS platforms (Salesforce).
- Why
- To leverage AI as a 'force multiplier' for productivity, efficiency, and innovation, offsetting concerns about high investment costs by proving real-world benefits.
Skeptical Approach
First Mover Advantage
Adoption and Return on Investment
Skeptical Approach
Few companies have widely deployed AI agents and seen value, raising concerns about astronomical spending. Early studies indicate many pilot projects fail to generate meaningful returns.
First Mover Advantage
Early adopters are seeing tangible outcomes and positive impacts on the bottom line, with some experiencing significant improvements in capacity and efficiency.
Maturity of AI Agents
Skeptical Approach
The pack may appear prudent by waiting to see how AI agents mature before committing to widespread deployment.
First Mover Advantage
The vanguard crew, by embracing AI agents early, may gain a long-term, sustainable advantage as the technology develops.
- Companies Mentioned
- BNY, Walmart, Salesforce, OpenAI
- Key Technologies
- AI Agents, Agentic AI, Generative AI, Eliza AI platform
- Reported Benefits
- Growing capacity, scanning code for vulnerabilities, writing fixes, shortening product development timelines, increasing productivity, improving merchandising and risk handling.
- Challenges
- Building an agentic framework is difficult; adoption remains in early stages; potential for trial, error, and significant spending.
- Source of Disagreement
- Effectiveness and ROI of AI agents, citing MIT study vs. BNY's experience.