By Betsy Burton
You Need An AI Architect Now
I know…I know…. many of you have been thinking about the idea of designating an Artificial Intelligence (AI) architect for some time. I also know many of you have thought you could put it off for another time.
Well, you can’t. We need to stop procrastinating and take this on.
Why You Need An AI Architect Now
The primary reason you need an AI architect now, is because AI is quickly becoming a pervasive way for developing solutions. Almost every tool, application, app and solution have some AI capabilities, and this trend will only continue – and will be the same for on-prem and for cloud-based systems.
Think about if your technology provider is going to make any enhancements, to remain competitive in this market, changes are they are going to use some AI techniques and technologies.
The good news is your technology providers will potentially be adding some really interesting new features. The bad news is their implementations of AI could be all over the map; some could be using good solid technologies and techniques, and some could be just adopting technology because it is being hyped with no real plan or discipline.
And If your provider is cloud-based, it is even more complicated.
How Is An AI Architect Different?
In my mind, an AI architect is a specialized, uber solution architect. They need to be able to understand AI development, AI architectures, data sources, governance and quality, interoperability, cloud architectures, security, etc. And they need to be able to work across teams to bring in specialists as needed.
They need to be able to look across systems to understand how your business is leveraging AI in different areas, and especially what information/data sources they are using. An AI architect must be able to work with cloud and cloud application providers to understand exactly how they are using AI.
Where Do I Find An AI Architect?
Depending on the size, focus and industry, an AI architect is a person on your EA team either dedicated to AI or at least very focused on AI.
There are some people on the market who are claiming to be or called AI architects today. Some of these people are really AI developers or AI application architects rather than AI Enterprise Architects – a classic EA recruiting problem. So, be clear about what you are looking for – conceptual and logical level architecture or implementation level detail.
Your AI architect must also have a lot of business architecture skills, and be able to cross into business strategy, operations, people, capability and ecosystem opportunities and challenges.
You may need to raise your AI Architect by assigning a good solution architect or EA to take on this role. If that is your more likely path, you must start now, and make sure they have time dedicated to learn what they need to about AI technologies, solutions and architectures.
Bottom Line
You need an AI Architect now. No more putting this off or hoping you can ignore it. AI is quickly becoming pervasive –in reality and in perception.
Aragon Research will be delivering more research on this topic. So, watch this space. And, if you have any questions, please feel free to schedule an inquiry call by contacting us.
Learn more about AI LIVE in our upcoming webinar:
Prompt Engineering for the Enterprise: Accelerating Workflows with Generative AI
Prompt Engineering for the Enterprise: Accelerating Workflows with Generative AI
Join us for a webinar where Aragon’s analyst, Adam Pease, will explore the process of prompt engineering for large language models within an enterprise context. This session will not only introduce you to the fundamental principles of prompt engineering but also showcase how forward-thinking businesses are already leveraging generative AI to revolutionize their operational efficiency.
On Thursday, July 13th, Adam’s talk will cover:
- How businesses can deploy generative AI in a cost-effective way
- The critical importance of prompt engineering for successfully leveraging generative AI
- Actionable best practices for prompt engineering in different workplace use cases
