AI Agents in 2025: Navigating Hype, Reality, and Governance
In the world of AI agents, we’re seeing a fascinating split: some leaders hail them as transformative, while others call them overhyped or prone to failure in real-world scenarios. Let’s break it down.
The Contradictory Landscape
On the one hand, we have enthusiastic reports from the likes of IBM, Nvidia, Reuters, and Forbes. Industry voices are echoing that 2025 is the year of AI Agents, and in some use cases, they are functioning like virtual employees and successfully handling tasks, with more on the way. On the other hand, reports and quotes from industry insiders and research publications suggest that many AI agents are struggling or delivering what Andrej Karpathy calls ‘slop’. These are lower-quality AI Agents layered on top of existing tools rather than true innovation.
Why the Disparity Exists
So why do we have these gaps in performance and perception? For one, not all AI agents are created equally. Some companies are simply slapping AI chatbot interfaces onto existing software and calling them agents. Others are building ground-up solutions with more sophisticated AI that truly understands and adapts to business contexts. Naturally, the latter tends to perform better. Specific use cases are also more mature; tasks such as customer service triage, basic sales prospecting, or campaign analytics may yield better results. Meanwhile, complex decision-making or highly regulated tasks often reveal limitations in the current tech.
The Role of Organisational Factors
There’s also a human side to this. Organisational structures and behaviours can make or break AI adoption. If a company isn’t ready to integrate AI thoughtfully and if it lacks transparent processes, data quality, or a culture of collaboration, even the best AI agent can stumble. Classic Digital transformation failures we have seen in the past.
A Case for Augmented Approaches
Finally, let’s talk about governance. In highly regulated industries, the safest bet is to keep AI agents in an augmented role, treating them as intelligent assistants with checks and balances in place, rather than as fully automated decision-makers. This approach ensures that human oversight remains, reducing risks and building trust.
In my view, the Augmented approach should be the central philosophy for using AI, given its economic and people-related implications. A topic for another post.
Avoid hype, avoid vendors offering half-baked solutions with no proof points, and adopt an augmented approach. The formula for choosing a solution is on
1. Enterprise Scale
2. Security and Privacy
3. Innovative Road Map
4. Proof points and feedback loop.
5. Modular with opportunities for Augmentation built into the workflow
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