As AI becomes an integral part of business processes and strategic planning, organizations have increasingly based their data strategies around its capabilities. Businesses are generating more data than ever from sources like IoT sensors, customer transactions, social media, and more; managing and extracting value from this explosion of big data has become a key priority. Rather than an add-on, novelty, or “next shiny thing” to explore, AI is shaping the core of how organizations approach and leverage data.

AI algorithms and apps couldn’t do their jobs without access to large volumes of data necessary for identifying patterns and insights. Enter cloud computing, whose scalability and flexibility provide the infrastructure needed to store the massive datasets AI requires. The on-demand access to computing power allows organizations to run complex AI algorithms and machine learning (ML) models rapidly on their data. The cloud also facilitates data sharing across organizations and with external partners.

While AI solutions remain incredibly important, the real revolution is happening behind the scenes in the cloud. In 2024, the cloud infrastructure – not the algorithms – becomes critical for widespread AI adoption.

AI Takes the Wheel

Forget incremental changes; AI’s revolutionizing businesses at warp speed. Enterprises have stopped dipping their toe in the AI pool in favor of diving in headfirst, deploying AI at scale and operationalizing their machine-learning strategies. This isn’t a tech upgrade – it’s a full-blown transformation.

Imagine: AI shifts through oceans of data, uncovering hidden patterns and making lightning-fast decisions humans simply aren’t capable of. That’s the power driving the shift. Empowered by AI, companies are streamlining operations, optimizing workflows and automating repetitive tasks, freeing humans for more strategic roles.

AI’s impact, however, goes beyond efficiency. It’s changing the game entirely with data-driven decision-making. Yes, gut feelings still count, but AI brings additional clarity and insights to every call. It can tailor interactions, anticipate needs, and create lasting connections. It’s sparking creative solutions, opening new markets and pushing the boundaries of what’s possible.

A Shift in Focus

Imagine a Lamborghini trying to navigate a one-lane gravel road. That’s traditional infrastructure when it comes to the demands of modern AI. Picture yourself trying to power a sleek, data-guzzling AI application on that. It’s not exactly a recipe for success. Traditional infrastructure can’t keep up with the demands of increasingly complex, data-hungry AI applications. 

Enter the cloud – like a limitless gas station for your AI engine. Need more power to crunch through massive data sets? The cloud scales up your resources instantly. Hit a roadblock with limited storage? The cloud expands your capacity at warp speed. 

Now imagine a BMW XM. A longer road trip requires mapping out charging stations along the way. The last thing you want is to run out of power before reaching your destination. Today’s cloud infrastructure keeps you running, with options like hybrid public/private cloud, multicloud – even serverless computing.   

But the cloud’s flexibility and elasticity are just the tip of the iceberg. What if you never had to worry about server maintenance or software updates? The cloud takes care of those tasks, freeing you to focus on what matters: building amazing AI solutions. And as companies struggle with data privacy concerns around AI, hybrid clouds may enable them to siphon off data that’s hidden from AI applications.

We can’t forget about the performance boost, either. The cloud provides access to cutting-edge hardware and software, ensuring AI applications run at peak efficiency. It’s like paving and widening the road into a superhighway.

The cloud provides many other benefits for AI development and deployment, including:

• Reduced costs: Owning and managing on-premises software often requires upfront investment in hardware, software and personnel. Cloud services offer a pay-as-you-go model, where you only pay for the resources you use.
• Faster time to market: Setting up and maintaining on-premises infrastructure for AI can become time-intensive. Cloud platforms come with pre-configured environments and readily available AI tools and services, enabling faster development and deployment of AI solutions. This capability allows organizations to capitalize on market opportunities and innovate more quickly.
• Improved collaboration: Cloud-based AI solutions are easily shared and accessed by teams across the organization, regardless of location.
• Enhanced security: Cloud providers offer a wide range of security features and compliance certifications to protect AI applications and data – especially crucial for organizations handling sensitive information and operating in regulated industries.
• Democratization of AI: Cloud computing makes AI technologies more accessible and affordable for businesses of all sizes, leading to a wider adoption of AI across various industries and use cases.

The road AI travels to reach the summit isn’t just technology but the cloud platforms and ecosystems – with their unparalleled scalability, performance, and ease of use – making it accessible and manageable. It’s no wonder companies are abandoning outdated infrastructure and embracing the cloud. AI strategies are synonymous with cloud strategies.