AI is a revolutionary business technology, but we've had enterprise revolutions before. Is the AI trend just the same as the cloud migration craze in the 2000s?
Artificial intelligence (AI) seems to be all anyone is talking about at the moment. It can be easy to think that this is a brand-new, unprecedented revolution in the way that we do business, particularly since that's what we're being told.
However, just 20 years ago, there was another buzzword going around that we all believed described a transitional epoch in enterprise technology. In the 2000s, the enterprise cloud was all we were talking about and it was believed that cloud computing would change business forever.
Yet, while the cloud is still part of our landscape, it isn't essential for success and it didn't mark a transition point in enterprise. The cloud, as it turned out, was just another kind of technology that can be leveraged to support your business.
While no-one knows the future, it's very likely that we will one day see AI as just another technology that can be leveraged in the right circumstances rather than a total game-changer. This means that IT leaders simply need to follow the same process for AI adoption that they do for any other technology.
What's the best way to adopt new enterprise technology? Enterprise architecture - the discipline of synergizing new technology with your business strategy.
Enterprise architecture is the key to harnessing the power of AI for your business. To find out more, download our guide to EA for AI:
Artificial intelligence (AI) is the current buzzword for enterprise, but it wasn't the first. Once, we were all focused on migration to the cloud.
The concept of cloud computing dates back to the 1980s, when computer pioneers first envisioned the capability to have a network of devices acting as one huge computer that can be accessed remotely from anywhere. In 1987, Steve Jobs himself famously told Apple developers that he wanted to:
"...look at that personal computer and take out every moving part except the keyboard and the mouse. I don't need a hard disk in my computer, if I can get to the server faster..."
David Hoffman of General Magic was credited with coining the term 'cloud computing', which was popularized by Compaq in 1996 when it began to promote cloud capabilities for its devices. It was the foundation of Amazon Web Services in the early 2000s, however, that heralded the arrival of functional cloud computing.
Soon, cloud computing was seen as the future of enterprise IT, and companies began frantically working to leverage the cloud. They were told that scalable cloud capabilities would be cheaper than on-premise options and, more-importantly, necessary to unlock future capabilities that would be vital for maintaining a competitive edge in the market.
Almost every company began working to migrate its IT landscape into the cloud, but those that did found themselves dissatisfied. Operating remotely added a lag time to processes, harming performance, while imperfect IT landscapes lifted and shifted into the cloud without adaptation remained imperfect.
By 2022, 451 Research found that 54% of companies had walked back some part of their IT landscape from the cloud. Does this mean that the cloud wasn't all it cracked up to be?
Artificial intelligence (AI) has incredible potential to drive enterprise innovation, but only if it's leveraged properly. The same is true for cloud computing.
The cloud is a revolutionary tool when used for the right parts of your estate, but not every application is better off there. Data and software under regulation may be restricted from the public cloud, while high-priority applications that need to work quickly may perform better on-premise.
On the other hand, applications that enable remote working, or unrestricted data that you need to be able to access from wherever you are, are ideal for cloud hosting. The value of the cloud can only be realized when you carefully assess what to host there and what to keep on-premise.
Likewise, when you migrate to the cloud, you need to also adapt your IT landscape for it. Your processes will only function in the cloud when they've been optimized for that environment.
Many organizations that were swept up in the cloud craze didn't realize this and so they migrated their entire landscape over without readying it first. Their migration never achieved the value it promised and more than half had to walk it back.
If we had known then what we know now about the cloud, companies could have made their migration smart and achieved the value they needed to, the first time. That's why it's so essential that we ensure we're leveraging AI in the right way now, or we may regret it in the future.
Artificial intelligence (AI) has incredible potential to drive your business forward, but only if it's adopted in the right way. Just like cloud computing, we need to be intelligent about artificial intelligence.
There are some use cases for AI that could lead you to regulatory difficulties, such as customer service. Last year, for example, Air Canada was successfully sued due to inaccurate information provided to a customer by its AI chatbot.
On the other hand, Ontada Health has used Azure OpenAI to automatically format 70% of its previously unstructured and unanalyzed data. Careful strategizing about where to use AI, and for what, is crucial at this early stage of the technology's adoption.
Likewise, and again just like cloud computing, ensuring your AI data is optimized for your use case will also be key to gaining a return on investment. Unlike the cloud, however, once enacted across your IT landscape, AI will be far more difficult to walk back than a cloud migration, should things go wrong.
This is why it's crucial for organizations to consider how they leverage AI and to do so carefully and strategically. That's where enterprise architects are vital as they're the experts on aligning the adoption of new technology with your strategic goals.
Artificial intelligence (AI) is just another new technology and it can be leveraged like any other innovation. Yet, to do so, you need to gain perfect clarity on your IT landscape and ensure everything is in alignment with your strategic business goals.
Enterprise architecture is a methodology for aligning your IT landscape with your business strategy, and just as your operations can be empowered by AI, enterprise architecture can be driven by the right toolset. That's why we've created the SAP LeanIX package of enterprise architecture solutions.
With SAP LeanIX, you can seamlessly adapt your business to leverage whatever best-of-breed technology innovations currently exist and may arise in the future. Whether it's generative AI, cloud computing, or whatever the next big enterprise technology revolution may be, SAP LeanIX will empower you to embrace it confidently.
Enterprise architecture is the key to harnessing the power of AI for your business. To find out more, download our guide to EA for AI: