Artificial intelligence (AI) is a complex, revolutionary innovation, but it's also just another new technology that needs to be leveraged to support your business goals. Let's explore how enterprise architects can level-up their capabilities to aid in AI adoption.
Artificial intelligence (AI) is redefining the scalability of IT services across every industry and leaders are pushing to leverage this technology quickly to avoid being left behind. Yet, AI has arrived so rapidly that IT teams are concerned about whether they have the knowledge to enact AI properly.
There are suddenly a multitude of AI vendors out there making many incredible promises regarding their products. How can you know what AI tools you actually need, where to implement them in your IT landscape, and how to manage them?
With AI being such a new, innovative technology, figuring out how to best leverage it can feel like a monumental task. Enterprise architects, however, should keep in mind that they've dealt with new technology before, from micro-services to cloud infrastructure.
Finding the best way to leverage new technology is what enterprise architects do. When you view AI as just another new type of software, then implementing it seems like far less of a challenge.
All you need is to take advantage of enterprise architecture tools like the LeanIX platform to map your current architecture and road map an AI future. To find out more about using LeanIX to adopt AI, read our previous article:
READ: AI Governance Vs Adoption - Innovation Without Risk
In the meantime, let's look more closely at the challenge with AI and why it's not as new as it seems.
The Challenge Of AI Adoption
Artificial intelligence (AI) has been a dream for more than 50 years, but its final realization was so sudden that it took us all by surprise. Out of nowhere, we had large language models (LLM) that could take simple prompts and create text, images, and code in seconds.
The use cases are endless, from reading resumes to find the right candidates among hundreds of applications to dynamically monitoring carbon production. Yet, zero-day issues are rapidly emerging, and enterprise architects are working to understand the difference between essential tech and snake oil.
Even when it does work, however, understanding where in your tech stack AI will be useful and where it will be a hindrance will be vital to best leveraging it. This will mean having complete clarity regarding your IT landscape and also understanding the capabilities of AI systems.
The truth is that we don't yet fully understand what AI can do or what it's useful for, since this is still an emerging and rapidly evolving innovation. Nobody is yet an expert in AI, as the technology hasn't been available for long enough for anyone to develop deep experience in using it.
Enterprise architects are, as such, gambling on how AI technology will evolve and simply hoping they have guessed right when we eventually discover what the best practice will be. What they need is a clear picture of what their options are for AI adoption.
An AI Constellation, Not A North Star
Much of the common advice regarding artificial intelligence (AI) adoption advises you to align your adoption strategy with your business goals. This is often compared to following a north star to ensure you stay on the path.
This advice, however, equates to putting all of your eggs in one basket. If you align your AI adoption to just one use case, then the best case scenario is that you will only benefit from one use, and the worst is that you will miss out on the benefits completely.
A much better option is to simultaneously pursue multiple lines of AI development on an agile basis. By developing a minimum viable product within multiple use cases, you can test them and develop further in areas where you find success.
This is, of course, the same way that you would develop any other new technology within your IT landscape. Indeed, treating AI just like any other new technology is the key to success.
AI Is Nothing New
Artificial intelligence (AI) is an incredible technological innovation, but it is just a piece of technology. You should already have an enterprise architecture process in place for assessing, understanding, and implementing new tech, so use it.
AI may be a challenging, multi-faceted technology to implement, but it is still just software. If you find yourself struggling to implement the tech, then what you're missing is likely just a more-mature enterprise architecture practice.
Just as AI can empower your content creation and data analytics, having the right toolset will dramatically improve your enterprise architecture function. You need a platform that can map your entire application portfolio and provide complete clarity on how it's arranged and interconnects.
To find out whether your enterprise architecture capabilities are mature enough for AI adoption, take our EA Maturity Assessment:
TAKE THE TEST: LeanIX EA Maturity Assessment
How LeanIX Can Support AI Adoption
The LeanIX metamodel will offer you a template setup for your enterprise architecture, including where AI can fit in. Combining this with the current data on your application portfolio in the LeanIX Application Portfolio Management product, you can use our Architecture And Road Map Planning product to chart a course from your current state to where you want to be.
Using vendor lifecycle information automatically pulled into the LeanIX platform, you can track what parts of your landscape are resilient enough and suitable to adopt AI. The LeanIX Technology Risk And Compliance product will even tell you whether your IT components are up to the task.
Using the LeanIX platform, AI adoption becomes just another task for your enterprise architecture team. To find out more about what LeanIX can do for you, book a demo:
