AI and Cloud Computing: A Match Made In Heaven

70% of businesses get their AI capabilities through cloud-based software, highlighting the mantra that AI and cloud computing are the two pillars propelling businesses into the future. 

But why? What is it about the union of AI and cloud computing that gives businesses the heart-eyes and makes them bust a move?

To answer that question, we must first ask ourselves what AI and cloud computing are.

The machine and the cloud

Artificial intelligence (AI) refers to the ability of machines to simulate human intelligence and perform tasks that would normally require human intelligence to do. AI is usually categorised in two ways: narrow AI and general AI. 

Narrow AI refers to AI that is designed to perform specific tasks such as image recognition. General AI on the other hand refers to AI systems that perform any intellectual task a human can do.  Both categories are powered by algorithms and machine learning models (MLM) that are trained on large amounts of data enabling the system to learn and improve over time.

Cloud computing refers to the delivery of computing services, including servers, storage and databases over the internet. It enables organisations to access computing resources on-demand and pay only for what they use, rather than needing to invest in their own IT infrastructure. 

Bringing them together

Together, AI and cloud computing are being used in automating processes such as data analysis, data management, security and decision-making. With its ability to exercise machine learning and deliver impartial interpretations of data-driven insights, AI is able to bring about efficiency in these processes. Leading to significant cost savings on numerous fronts.

Furthermore, the use of AI within cloud environments can deliver intuitive and connected experiences for customers, with Amazon’s Alexa and Apple’s Siri being just two examples of this seamless combination delivering a variety of operations from conducting a search for a song to making a purchase.

Within the domain of cloud computing—especially public cloud services such as Amazon Web Services (AWS)—developers do not need to build and manage a separate infrastructure for hosting AI platforms. Instead, they can use ready configurations and models to test and deploy applications.

This enables the use of generic services such as speech-to-text, analytics and visualisation which are based on AI, to be improved by running them from the cloud using first-party data generated by the organisation.

Such example include:

1. Chatbots, an AI based software that use natural language processing to carry out conversations with users. Cloud platforms store and process the data captured by chatbots and cloud services connect them to the appropriate applications for further processing.
2. Business Intelligence, another mainstream application where AI cloud computing can gather data on the market, target audience, and competitors of customers. The cloud again facilitates the storage and transfer of data while AI runs it through predictive analytics models.
3. Cognitive Cloud Computing, which is the use of AI models to replicate and simulate human thought processes in complex situations. 

The good

The key benefit in using AI with cloud computing for any business is the cost saving that it brings.  Gone are the days of companies having to run expensive machines in expensive data centres, instead, businesses can simply use online cloud services and pay for them with a credit card.

Without the need for excessive maintenance, the IT team can focus on other tasks, significantly increasing their productivity and ensuring that the company can operate as intended.

On the more technical side, the use of AI and cloud computing makes it far easier to mine the data collected and stored within the cloud, ensuring that businesses can get insights quickly. At the same time, AI helps boost cloud workloads by processing and generating data in real time, thus enabling things like fraud prevention, threat detection and personalised shopping recommendations.

The bad

Of course, nothing good ever comes without a few drawbacks and the heady mixture of AI and cloud computing is no different.

The main concern focuses on data privacy, as the public cloud, though great for being able to run a lot of data, contains some security risks. When AI processes data into a tool in the public cloud environment, it amplifies these risks on an exponential scale. Sensitive data could be exposed to a security breach or unauthorised access when the processes and perimeters for the AI cloud computing algorithms are not clearly defined.

On top of this, having a poor internet connection can slow down the process of data storage and analysis, leaving the business high and dry and the customer annoyed.

The future

Companies are betting big on AI in all forms of work, but particularly when it comes to cloud computing. The possibilities are endless, from enhancing operational efficiency, improving security and unlocking advanced capabilities to driving innovation through data-driven decisions. 

AI combined with cloud computing has the possibility to change the game for businesses everywhere. As the technologies continue to develop, this is surely going to continue growing.