Artificial Specialized Intelligence: The Key to Safe and Scalable Business AI

Recent and rapid developments in artificial intelligence have created a divide between two ideological approaches in Artificial General Intelligence (AGI) versus Artificial Specialized Intelligence (ASI).

Artificial Specialized Intelligence: The Key to Safe and Scalable Business AI


Recent and rapid developments in artificial intelligence have created a divide between two ideological approaches in Artificial General Intelligence (AGI) versus Artificial Specialized Intelligence (ASI). While the future may hold a place for both points of view, the question of which to prioritize in the enterprise is an active subject of debate. AGI aims to undertake any cognitive task comparable to a human, while ASI is specifically programmed to execute specialized or a more narrow scope of processes. 

Understanding ASI

ASI refers to AI systems programmed to perform specific tasks or solve particular problems with a high level of proficiency within a limited scope. These systems excel in tasks like language translation, image recognition, or driving cars, demonstrating specialized expertise but lacking the broader cognitive abilities and adaptability of human intelligence beyond the defined scope. ASI can be likened to an industrial innovation like the freight train, where it is incredibly safe (it runs on rails, after all), but it executes its function with tremendous power and with great predictability and precision.

The Risks and Challenges of AGI

On the other hand, AGI strives to develop AI systems capable of understanding, learning, and applying knowledge across various domains, resembling human-like intelligence. The pursuit of AGI raises questions regarding the potential risks of unleashing such powerful and autonomous systems into the world. It is regarded as a pursuit because most technologists and even top AGI vendors like OpenAI and Meta don’t claim to have achieved it yet as of 2024.

Inherently, AGI sacrifices safety because it prioritizes both power and generality. Things that possess these traits tend to pose too much risk to businesses that seek stability for longitudinal growth. Conversely, if AGI solutions providers pursue a safer version of AGI, then power will be sacrificed significantly undercutting the intended utility of the tool.


Kognitos advocates for prioritizing ASI over AGI due to its emphasis on safety while unleashing tremendous power on intended business process targets. Businesses looking to transform and integrate AI into their processes are feeling the same with fewer companies committing to AGI. In the Harvard Business Review piece, “Why adopting GenAI is so difficult”, the author suggests that corporates consider human control and data traceability, among other factors.

One vital aspect of the approach of many ASI powered solutions like Kognitos is designing AI systems to seek human guidance in exceptional circumstances and to rely on skills that humans have mastered over millennia. Instead of giving machines the power to make potentially unsafe or inaccurate autonomous decisions beyond their intelligence boundaries, Kognitos offers a structure where AI interacts with humans when encountering scenarios outside their expertise. This setup ensures that human judgment remains at the forefront of critical decision-making processes.

The Role of Humans in ASI

Accountability remains clear by placing humans in machine control, fostering a responsible approach to AI implementation. In this light, there is no human-in-the-loop to simply ensure that a process is functional; the human creates added value by being there to contribute to the process and help the AI learn for the next instance.

We deliberately limit our scope and capabilities by designing AI systems with narrow intelligence. This constraint empowers humans to retain control, mitigating the risks of unforeseen consequences or uncontrollable behavior in complex scenarios. In other words, ANI may power self-driving cars, but it grants the human the ability to always have an influence by taking control of the steering wheel.

Transparency and Ease of Use

ASI powered solutions provide greater data transparency and accountability when compared to AGI powered solutions. An example would be the option to view the System of Record for Business Processes in the Kognitos platform for example, a comprehensive record of all process runs, decisions made, approvals, and exceptions handled, providing access to all the data a business user would need.

While the appeal of AGI persists due to its potential to revolutionize various industries and solve deeper, more complex problems, it is advisable for enterprises to take a more calculated approach.

The trajectory of AI development is at a crossroads, with ASI and AGI representing divergent paths. The market will largely dictate which technological approach is most adopted and integrated into our collective future. Kognitos firmly supports ASI as the more prudent and responsible approach by placing humans in control and implementing mechanisms for humans to uniquely leverage human skills.

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