Analytics, AI/ML

What It Really Takes To Scale Ai?

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Most businesses are still grappling with artificial intelligence's potential to transform their operations. 

 Implementing AI across the entire enterprise at once is far too difficult to be viable.

A study by Accenture shows that 86 percent of CEOs feel they won't fulfill their growth goals unless they can scale AI. What does it take to scale artificial intelligence? 

What does it take to scale AI?

AI is a distinct differentiation vital for growth since the coronavirus pandemic drove firms into the digital domain. According to Gartner, by 2022, firms will have an average of 35 AI initiatives in place. In principle, though, building a world-class AI firm is far easier than in practice. 

Traditional AI development is time-consuming, labor-intensive, and expensive, and there is no assurance of success.


Companies must make three changes to scale AI. Firstly, they must shift from segmented work toward collaborative work. Secondly, they must transition from a figurehead, perspective judgments to statistics judgment. Thirdly, they must adjust from a strict, risk-averse mindset to one that embraces the experimental attitude.

Data volume continues to increase:

The amount of data we generate is growing consistently. In the meantime, businesses are looking to adopt more models to comprehend and extract value from massive amounts of data. When dealing with a 100-fold increase in data volumes or models, the technical complexity increases dramatically.

Complex technology:

Heterogeneous computing is required to run AI to generate real-time predictions. Developing and running AI at scale necessitates a massive amount of costly computing power.

Different AI devices' performance trade-offs:

AI is migrating away from the cloud and toward the edge. Businesses may need to scale AI models to hundreds of thousands of different devices for a single-use case. You often pair the accuracy of AI with that of humans.


We're entering an era of intelligent Internet of Things (IoT), in which sharp, linked gadgets can take intuitive actions depending on situational awareness.  To read more articles like this, visit

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