Enable AI and Digital Transformation with the Cloud

October 19, 2021
Cloud

Enable AI and Digital Transformation with the Cloud

You’ve heard and read it before. To deliver value to your customers and remain competitive in an ever-changing business environment, you should embrace digital transformation.

With artificial intelligence (AI) technologies among the key enablers of digital transformation, there’s a good chance you’re also going to want to leverage those technologies ─ things like machine learning (ML), image recognition, marketing automation, etc.  

But how do you do that? While the answer will depend on numerous factors, there are two key elements that will come into play: data and the cloud.

 

Know Your Data

Data is what feeds AI technologies. Chances are you have a lot of it. But do you know the different kinds of data you have? Is it mostly structured, unstructured or a combination of both?

Do you know you could leverage the insights your data could deliver to create better customer experiences or optimize business processes? Is your data in a form that makes it easy to analyze?

Where does your data come from and where does it go? How is it being used? Is it being used? How are you collecting it? Are you collecting it? Where and how are you storing it? Are you using data lakes or data warehouses? Are your databases cloud-based? Are you collecting and storing your data economically and efficiently?

Is your data safe? Is it easily and quickly accessible when you need it? If your data was corrupted or stolen, how would that affect your business operations? Do you have a plan in place to protect and/or recover your data in the event of a manmade or natural disaster?

There are many questions regarding your data and what you are and can be doing with it. That leads to the next element that is a key to making use of AI technologies and facilitating digital transformation: the cloud.

 

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Embrace the Cloud

While you can run manage and process the data integral to AI technologies on your own hardware, the cloud makes it easier and much more cost-effective. For example, if you want to build a ML solution on your on-premises hardware, there are several open-source ML frameworks to help you do so, such as CNTK and TensorFlow. But developing and training ML models requires considerable compute resources. The same applies to data analyses and other aspects of AI.

Those resources aren’t cheap. As you experiment with various ML models and architecting workflows for data collection and analyses, the costs can rise quickly. Not all organizations are able to invest in the infrastructure required to support resource-intensive processes.

Most cloud services use a pay-as-you-go model. You only pay for the resources used when they’re used. There’s no need to overprovision resources to make sure you can handle bursty workloads. Resources are available on-demand, so it’s also easy to scale up and down as required. As is the case with US Signal’s cloud services, those resources are also available around the clock courtesy of 24/7/365 technical support and SLA-backed uptime.

  

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The cloud also offers affordable, flexible storage. As data volumes grow, it’s often less expensive for organizations to store data in the cloud rather than continuing to house it in their own data centers. Businesses can also take advantage of things like tiered storage plans that enable them to move data to lower-cost object storage for data archival, compliance requirements, and other reasons.

In addition, most cloud services are highly secure, making them ideal for businesses that need to protect vast volumes of data. Cloud service providers (CSPs) want their customers’ business, so they incorporate high-level security technologies and protocols to keep customers’ data safe – and their peace of mind high.


The Future of AI and the Cloud

The cloud is quickly becoming the go-to model for the underlying infrastructure to enable digital transformation and AI technologies, and for harnessing the business value of data. As the statistics indicate, this is not just a passing fad.

Gartner predicts that through 2023, AI will be among the top workloads that drive IT infrastructure decisions. According to forecasts by Omdia (formerly Tractica), by 2025 AI will account for as much as 50% of total public cloud services revenue.

As noted in a TierPoint blog, “…outside of corporate data centers, only public cloud infrastructure can support massive data storage as well as the scalable computing capability needed to crunch large amounts of data and AI algorithms. Even companies that have private data centers often opt to avoid ramping up the hardware, networking, and data storage required to host big data and AI applications.” 

 

Talk to US Signal

If you’re interested in learning how to use the cloud to support your digital transformation and/or leverage AI technologies, call 866.2.SIGNAL or email [email protected].