Introduction
The rise of agentic AI is transforming how enterprises operate. Early adopters are exploring these solutions to eliminate bottlenecks, cut FTE costs, and automate repetitive, low-ROI tasks. For investors and tech leaders, this is more than a trend—it’s a structural shift in enterprise operations and productivity.
Massive Cost Reductions in Action
Consider identity management in complex enterprises. Traditionally, a simple password change across applications, AD, and integrated systems cost $20–25 per action. With converged agentic solutions, this drops to less than $0.50—a dramatic efficiency gain.
This isn’t just a cost-saving story. It challenges the traditional IT services model of large teams for maintenance, change management, and process oversight. Once stabilized, agentic deployments require minimal, highly specialized human intervention, making them scalable and sustainable.
The Current Phase: Discovery Marathons
Today, most IT companies, consultants, and clients are engaged in use case discovery and experimentation:
- Identifying inefficiencies
- Building agentic skills and frameworks
- Testing prototypes
While repetitive, this is typical for an early-stage paradigm, where duplication of effort is part of learning and standardization.
The Future: Agentic Skill Marketplaces
In 3–5 years, I anticipate a shift towards reusable agentic skills that any platform agent can adopt. Think of it as the app marketplaces of enterprise software:
- SAP, Oracle, Microsoft—all have ecosystems where partners release reusable solutions.
- Similarly, agentic skill marketplaces will allow consultants and developers to build, sell, and integrate agent skills across platforms.
This will create new opportunities for enterprise efficiency and investors alike.
Key Challenges in Agentic AI Adoption
- Uncertainty around models and stability of outcomes
- Data privacy and compliance boundaries
- Risk of hallucinations, requiring RAG and fine-tuning
- Interoperability with existing systems
- Matching the right tool to the right business process
- Measuring ROI and business value
- Token inefficiency from poor prompting or context gaps
- Building self-healing agents with evaluation flows
- Agents’ ability to select the correct tool at the right time
Investor Takeaway
From an investment perspective, tracking companies innovating in agentic AI and skill marketplaces is essential. The combination of cost reduction, process automation, and reusable agentic skills creates a compelling growth story.
In upcoming posts, I’ll explore the critical role of high-quality and synthetic training data, which is emerging as a high-value segment of the AI value chain—and yes, India is a player to watch 😉
To summarize
Agentic AI is more than a trend—it’s reshaping enterprise productivity. Investors, technologists, and consultants who understand its potential today will be the winners tomorrow.
Follow me on X @finstor85 for insights, analysis, and updates from the frontlines of tech-driven business transformation.
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