@ericyocam6Is Agentic AI Creating Real Business Value or Just More Automation?
Businesses are investing heavily in agentic AI, with the promise of autonomous systems that can manage workflows, interact with customers, execute transactions, and make operational decisions.
But an important question remains:
Are AI agents actually delivering measurable business value, or are organizations simply automating processes without improving business outcomes?
Traditional automation focuses on predefined tasks. Agentic AI introduces systems capable of planning, reasoning, and taking actions across multiple applications with varying degrees of autonomy.
That creates opportunities, but it also introduces additional costs and risks.
Consider a business deploying AI agents for customer service, sales, financial operations, or software development.
How should that organization measure success?
- Cost reduction: Are operating expenses actually declining after accounting for AI infrastructure, maintenance, and oversight?
- Revenue growth: Are AI agents generating measurable increases in sales or customer retention?
- Productivity: Are employees accomplishing more, or simply spending time reviewing AI-generated work?
- Risk: Are efficiency gains being offset by security vulnerabilities, hallucinations, or unauthorized actions?
I believe the real measure of agentic AI success shouldn't be how many tasks an agent can perform autonomously, but whether those activities produce measurable business outcomes.
My question for the Lounge.ai community:
Are businesses measuring the actual return on investment from agentic AI, or are we still in a phase where experimentation and adoption matter more than demonstrated financial value?
I'd be particularly interested in hearing from founders and business leaders who have deployed AI agents in production.
Comments2
Employees spending their day checking the agent's work is the cost that usually gets left out when a company claims savings. Are you planning to turn these four measures into a simple scorecard, and which kind of company would you test it with first?
Great point, Ryan! The human oversight cost is often overlooked when organizations calculate the ROI of agentic AI. If employees spend significant time reviewing, correcting, or redoing an agent's work, the actual savings may be considerably smaller than reported.
I like your suggestion of a simple scorecard built around cost reduction, revenue impact, productivity, and risk, with human intervention and oversight costs explicitly included.
For an initial evaluation, I'd lean toward a small or mid-sized business using AI agents for customer support, where metrics such as cost per ticket, resolution time, escalation rates, and customer satisfaction are already measurable.
The key would be comparing total operating costs and business outcomes before and after deployment, rather than simply counting automated tasks. That could provide a much more realistic picture of agentic AI's business value. Appreciate the suggestion!
2 comments
Employees spending their day checking the agent's work is the cost that usually gets left out when a company claims savings. Are you planning to turn these four measures into a simple scorecard, and which kind of company would you test it with first?
Great point, Ryan! The human oversight cost is often overlooked when organizations calculate the ROI of agentic AI. If employees spend significant time reviewing, correcting, or redoing an agent's work, the actual savings may be considerably smaller than reported.
I like your suggestion of a simple scorecard built around cost reduction, revenue impact, productivity, and risk, with human intervention and oversight costs explicitly included.
For an initial evaluation, I'd lean toward a small or mid-sized business using AI agents for customer support, where metrics such as cost per ticket, resolution time, escalation rates, and customer satisfaction are already measurable.
The key would be comparing total operating costs and business outcomes before and after deployment, rather than simply counting automated tasks. That could provide a much more realistic picture of agentic AI's business value. Appreciate the suggestion!