In the past year, Artificial Intelligence (AI) has become the hottest, most-discussed topic in the business and high-tech worlds. Every day, we read stories in the news and in trade journals about the potential of AI to transform the way we live, work and communicate. 

 Companies in every sector are investing in AI initiatives, some even developing their own AI platforms. Experts predict that AI will revolutionize our world more than even the rise of Internet access in the 1990s. In the first half of 2023, the NASDAQ 100 (NDX) was up 39%, and the S&P 500 was up 16%. Currently, 28% of S&P 500 companies are technology-driven, while 8% are in consumer services or communications with ties to AI. 

 What’s driving this skyrocketing investment in artificial intelligence? Here are seven market-based factors that are influencing the AI boom: 

Advancements in New Technologies- 

Increased computing power, storage capabilities and new algorithms are enabling programmers to grow AI applications exponentially. Industries are utilizing these advancements to automate business processes, gain insight into product behavior and customer actions and improve decision-making. 

Ongoing Growth of Cloud Computing-

The major cloud providers continue to invest in building out their cloud infrastructure, even when it has been economically risky to do so (think rising interest rates). The AI wave wouldn’t have happened without the continued growth of the cloud, which supplies massive computing power for processing and data storage. 

 Also, the major cloud providers have made it easier and more cost-effective for other companies to jump on the AI train. Cloud giants like AWS, Azure and Google provide infrastructure, scalability and tools that allow organizations to develop, deploy and manage their own set of AI applications. 

Big Data and Data Availability- 

Until recently, data storage was limited to what could be put on a local magnetic disk or cartridge. Now cloud-based storage gives companies easy access to huge amounts of structured and unstructured data. This access provides significant opportunities for AI-powered data analysis to detect patterns, identify trends and make predictions. 

Also, Machine Learning (ML), a subset of AI, benefits from data availability. In ML, machines and systems learn and improve from their experiences, without being purposely programmed to do so. Since ML requires large amounts of data for precise accuracy and efficiency, having open access to data makes it easier/possible for research organizations to teach ML models how to solve complex problems. 

A Competitive Edge- 

Companies are constantly seeking new technologies that will give them advantages over their competitors. AI/ML technologies enhance product development, optimize operations and enable strategic, data-inspired decisions, providing many businesses with improved outcomes, better efficiency and cost savings.  

Improving Customer Experiences- 

Using AI/ML, companies can analyze data to gain insight into customer preferences, needs and behaviors. From this analysis, they can provide more personalized customer experiences, improve marketing campaign targeting and make more precise recommendations for customer products or solutions, leading to better customer satisfaction and increased loyalty. 

Insights and Predictive Analytics- 

In analyzing large data sets, AI/ML algorithms can gain valuable insights that help companies to make data-inspired decisions and predictions. These insights are particularly valuable in the healthcare, marketing, finance and cybersecurity industries, where accurate predictions and proactive measures can help to identify potential opportunities, prevent problems and improve outcomes. 

Automation of Routine Tasks- 

Automation improves productivity, increases efficiency and reduces mistakes in industries such as manufacturing, finance and healthcare. AI/ML can help to automate repetitive, everyday tasks, allowing people in these industries to focus their attention and resources on more creative and complex endeavors. 

Applications for Specific Industries- 

AI/ML is being used to create new industry-focused applications. In manufacturing, for example, AI can help to optimize processes and anticipate maintenance schedules. In healthcare, AI can analyze medical images, making it easier for physicians to diagnose patient ailments and suggest treatments. 

Data Centers 

The Home Base of the AI Revolution 

Artificial Intelligence and Machine Learning don’t exist in a cyberspace vacuum. Creating AI and ML applications requires immense compute capacity. Furthermore, the enormous volumes of data analyzed by AI and used by ML models require large amounts of storage capacity. 

AI and ML exist on High-Performance Computing deployments, which require the essential mission-critical elements of space, power, cooling and connectivity. That’s why the home base for today’s HPC footprints is the data center. 

With the AI revolution in full swing, data centers are in such high demand that many companies are now pre-leasing space and power in facilities that are still in the planning stages. If you’re planning an AI deployment even a few years down the road, now is the time to begin the procurement process. Call Sabey Data Centers today to ask about our pre-leasing agreements.