4 Ways AI Is Improving Cloud Computing

Liz Alton

Artificial intelligence and cloud computing have merged to improve the lives of millions. Digital assistants like Siri, Google Home, and Amazon’s Alexa blend AI and cloud computing in our lives every day. With a quick verbal cue, users can make a purchase, adjust a smart home thermostat, or hear a song played over a connected speaker. A seamless flow of AI and cloud-based resources make those requests a reality. Most users never even realize that it’s a customized blend of these two technology spheres—artificial intelligence and cloud computing—that make these connected, intuitive experiences possible.

On a larger scale, AI capabilities are working in the business cloud computing environment to make organizations more efficient, strategic, and insight-driven. Cloud computing offers businesses more flexibility, agility, and cost savings by hosting data and applications in the cloud. Artificial intelligence capabilities are now layering with cloud computing and helping companies manage their data, look for patterns and insights in information, deliver customer experiences, and optimize workflows.

Here’s a closer look at what you need to know about the future of AI and cloud computing.

The Role of AI and Cloud Computing

According to Statista, the global value of the AI market will surpass more than an estimated $89 billion annually by 2025. A significant percentage of that value will occur as artificial intelligence powers cloud computing—and, in turn, as cloud computing acts as an engine to increase the scope and impact AI can have in the larger market.

McKinsey recently conducted a study to explore how AI could impact value creation in a range of industries. They estimate that across 19 business areas and more than 400 potential use cases, AI could create $3.5 trillion and $5.8 trillion per year in value. That number is actually conservative, because it reflects a specific sub-segment of AI techniques. More broadly, McKinsey estimates the impact could be as large as $15.4 trillion per year.

Deloitte, however, pointed out in an analysis that while AI has tremendous capabilities to benefit companies, the need for technical talent and massive infrastructure has made it less attainable for many organizations. That’s where the cloud comes in. Deloitte notes, “The upshot is that these innovators are making it easier for more companies to benefit from AI technology even if they lack top technical talent, access to huge data sets, and their own massive computing power. Through the cloud, they can access services that address these shortfalls—without having to make big upfront investments. In short, the cloud is democratizing access to AI by giving companies the ability to use it now.”

Let’s explore some of the most important and promising applications for AI and cloud computing.

Powering a Self-Managing Cloud with AI

Artificial intelligence is being embedded into IT infrastructure to help streamline workloads and automate repetitive tasks. Some have gone as far as predicting that as AI becomes more sophisticated, private and public cloud instances will rely on these AI tools to monitor, manage, and even self-heal when an issue occurs. Initially, AI can be used to automate core workflows and then, over time, analytical capabilities can create better processes that are largely independent. Routine processes can be managed by the system itself, further helping IT teams capture the efficiencies of cloud computing and allowing them to focus on higher-value strategic activities.

Related: You’re Already Supporting Multi-cloud–But what’s your Strategy?

Improving Data Management with AI

At the cloud level, artificial intelligence tools are also improving data management. Consider the vast repositories of data that today’s businesses generate and collect, as well as the process of simply managing that infrastructure—identifying data, ingesting it, cataloging it, and managing it over time. Cloud computing solutions are already using AI tools to help with specific aspects of the data process. In banking, for example, even the smallest financial organization may need to monitor thousands of transactions per day.

AI tools can help streamline the way data is ingested, updated, and managed, so financial institutions can more easily offer accurate real-time data to clients. The same process can also help flag fraudulent activity or identify other areas of risk. Similar improvements can have a major impact on areas such as marketing, customer service, and supply chain data management.

Getting More Done with AI–SaaS Integration

Artificial intelligence tools are also being rolled out as part of larger Software-as-a-Service (SaaS) platforms to deliver more value. Increasingly, SaaS providers are embedding AI tools into their larger software suites to offer greater functionality and value to end users. Let’s explore one popular example: the customer relationship management platform Salesforce and its Einstein AI tool. The value of a CRM is that it captures a significant amount of customer data and makes it easier to track customer relationships and personalize interactions. But the volume of data can be overwhelming.

Salesforce introduced Einstein to help turn data into actionable insights businesses can use to sell more, improve their sales strategies, and engage with customers. The tools can help a business look for patterns in customer interactions, for example, to help advise sales on what method–like phone, email, or an in-person meeting–is more likely to drive a conversion. It can also be used to make “next step” recommendations based on the buying signals the tool is perceiving.

Utilizing Dynamic Cloud Services

AI as a service is also changing the ways businesses rely on tools. Consider a cloud-based retail module that makes it easier for brands to sell their products. The module has a pricing feature that can automatically adjust the pricing on a given product to account for issues such as demand, inventory levels, competitor sales, and market trends. Sophisticated analysis that’s based on modeling–pulling on deep neural networks–can give businesses much better command of their data, with important real-time implications. An AI-powered pricing module such as this ensures that a company’s pricing will always be optimized. It’s not just about making better use of data; it’s conducting that analysis and then putting it into action without the need for human intervention.

AI and cloud computing are transforming business at every level. From deeper learning to near-compete automation of key processes, the potential is promising. While there are some examples of this in the market now, a look at the landscape suggests that this will only continue to grow in the years ahead. Begin to explore how AI and cloud computing together could help you deliver better experiences, work more efficiently, and capture the maximum value from the data and insights you collect in the market.

Liz Alton is a B2B technology and digital marketing writer and content strategist. She has worked with a variety of brands including Google, Twitter, Adobe, Oracle, and HP, and written for publications including Forbes. She is a regular contributor to Connected, Connection’s official blog.

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