Discover expert insights from Drew Firment, chief cloud strategist at Pluralsight, on optimizing cloud and AI integration for transformative business innovation. Learn essential strategies for success in the ever evolving tech landscape.
I recently came across an Insider article lamenting “tech’s broken promises”: streaming bundles are just as expensive as cable, Uber and Lyft cost as much as taxis, and, notably, the cloud is no longer cost effective. I’ve been hearing this opinion about the cloud for some time now, and in the past year, I have seen large companies like Dropbox and HEY repatriate most (if not all) of their IT workflows back to on premise solutions.
While cloud computing is an easy scapegoat for tech’s ‘empty promises’, services like Uber and Netflix wouldn’t be possible without it. Cloud computing allows me to call an Uber to pick me up at a predetermined location anywhere in the world at the click of a button. Netflix prevents me from walking to my local Blockbuster to rent a movie for a similar cost. How is that not delivering on its value proposition? And yes, big organizations like Dropbox and HEY are moving back to on prem largely due to massive economies of scale when it comes to storage costs—but the irony is that they would’ve never gotten so large without leveraging cloud computing to get through the early stages of scaling in the first place.
The cause of higher cloud cost is often related to operational inefficiencies tied to supply chain or human capital. When it comes to the cloud, much of the value isn’t realized simply because people aren’t trained to use it efficiently, hence the growing trend of cloud cost optimization, or FinOps.
These same challenges with economies of scale and operational inefficiencies will arise as companies adopt AI. If organizations think cloud computing is expensive, wait until they try running many machine learning algorithms at scale! Most enterprises go through standard cloud adoption patterns, which will be mirrored in AI adoption. So, what can we learn from cloud computing adoption that can help us accelerate the adoption of AI more quickly, with less pain and less cost?
A Guide for Driving Cloud and AI Success
Many companies need help with cloud adoption because they need the foundational purpose, practices, and skill sets to do cloud computing effectively. Without these fundamentals, organizations do the same things with new tools and expect magic. Plus, as companies adopt AI, they’ll first need to have mastered the basics of cloud computing and data before seeing AI’s actual value. Below are four questions technology leaders should consider when making decisions about their cloud infrastructure and AI adoption.