Thinking of using AI Agents? You would be better off taking the help of specialists

Author
Rantej Singh
Published
September 27, 2024
Rantej talks about how Generative AI is transforming marketing and sales, enabling hyper-personalized content and optimizing customer journeys for higher conversions. Read more to know how GenAI is driving growth at scale.

“Reality is that developing AI agents is far more complex and resource-intensive than many anticipate. “

Introduction:

As AI adoption continues to skyrocket, many organizations may feel the urge to build their own AI agents in-house. After all, it sounds like a cutting-edge way to stay competitive, right? However, as AI technologies like agentic AI—designed to operate without human intervention—become more prevalent, experts are advising companies to proceed with caution.

While the allure of automation and streamlined workflows is undeniable, the reality is that developing AI agents is far more complex and resource-intensive than many anticipate. According to Forrester, three-quarters of companies attempting to build AI agents in-house will fail by 2025. 

The intricate architecture, specialized expertise, and evolving technology often make partnering with AI specialists or using vendor-provided solutions a more viable path to success.

Key Challenges of making your own AI Agents:

1. Resource Intensive:

Developing AI agents from scratch requires significant investment—not just in terms of technology, but also expertise. From data scientists to machine learning engineers, the specialized skills required can quickly drain resources, both human and financial.

2. Complexity:

AI agents are sophisticated systems. Without the right infrastructure, data pipelines, and maintenance plans, you risk creating a system that is unreliable, difficult to scale, or worse, prone to errors. AI is not just about the initial build; it’s about constant refinement and updates.

3. Security Risks:

In-house AI agents could introduce vulnerabilities if not properly managed. AI systems deal with massive amounts of sensitive data, and any mismanagement could lead to security breaches or compliance issues.

4. Existing AI systems:

AI systems like Agentic AI can act as autonomous agents are still in their infancy. It could be a couple of years before they meet the lofty automation hopes of many companies.

Bottom Line

While building AI agents may sound appealing, the risks and challenges are substantial. Instead of reinventing the wheel, leveraging proven AI solutions may offer a more efficient, cost-effective, and secure path to innovation. Let’s focus on smart strategies, not just cutting-edge tech.

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Rantej Singh
Rantej Singh is the founder of eligere.ai. Rantej has 20 years of experience working with MNCs like Bank of America Merrill Lynch, Thomson Reuters and ICICI Bank in Trade Finance, Product and Innovation roles. Rantej is a serial entrepreneur with deep understanding of the digital product lifecycle ecosystem. Rantej is a co-author of a finance book and a triple medal winner at US Open Karate Championship. Rantej has a Bachelor of Technology degree and is an MBA from IMD - Switzerland.

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