Building an AI Strategy with Caroline Carruthers
Before jumping into AI, it’s important to have a strategy. You need to know what problem you are trying to solve, where you are now, and where you want to go. The CEO of global data consultancy Carruthers and Jackson explains what’s involved in building this strategy and where AI -- not just generative AI -- is headed.
- By Upside Staff
- April 10, 2024
In the latest podcast program, Caroline Carruthers, CEO of global data consultancy Carruthers and Jackson, discusses building an AI strategy. Carruthers will be a featured speaker at the TDWI Virtual Summit on April 17. [Editor’s note: Speaker quotations have been edited for length and clarity.]
“I don't think you can talk to any organization now and not mention AI. I can see the reason why -- it's an incredibly powerful tool. However, I think there's a lot of misinformation about what AI is, what it can currently do, and the potential it offers. It's important that we spend time now getting our head around what AI is and if it is the right thing for our enterprise. I think AI can be overwhelming for many organizations. It’s a brand-new technology offering many capabilities and you just want to rush to it.
“When I talk about strategy, I’m focusing on purpose. What is the purpose you're going to use this technology for? What are you hoping to get out of it? I don't think you need to overcomplicate strategies -- that's one of the things that we do.”
Does Carruthers think AI fits into an enterprise’s data strategy, or is it separate? “I'm not really a purist. When it comes to ‘we have to have a technology strategy, we have to have a data strategy, we have to have an AI strategy,’ all I genuinely care about is that we understand how everything fits together and how we're going to make it work. For some organizations, because of the way they work, it makes perfect sense to have a data strategy and an AI strategy because data is the fuel that's going into the AI, and you need to know how they work together. In other organizations, you might have a digital strategy that encompasses multiple things. I wouldn't argue that your strategy has to be a certain way; I’m more interested in what it's doing for you. It's important to build that flexibility into your thinking when you go through this process.”
When asked to share some high-level steps for getting started building an AI strategy, Carruthers explained that besides figuring out your purpose (what you want to get out of your data), you need to know what opportunities you are trying to take advantage of. “One important step we often miss is determining what we are <em>not</em> going to focus on, because often we think, ‘We have to do all of this!’ You don't quite know where the boundaries are. That's a good starting point. Then you must determine what metrics will demonstrate to you that it’s working.
“You must also determine where you are now. With any kind of strategy, when you're building it, you need to know your starting point and where you are trying to get to. The strategy is the interesting bit that gets you from one place to the other.”
When she consults with enterprises, Carruthers typically starts with a maturity assessment, specifically a data maturity assessment because data fuels AI. Many organizations have poor-quality data, and the idea of “garbage in, garbage out” is applicable to AI. “It's one of those perfect examples: if you have complete and utter garbage, you might want to fix it” before you begin the project. She doesn’t mean you can't start working with AI if you need to work on your data quality. In fact, you should “experiment a little bit with AI to understand how it fits in your organization.” Determine what types of AI will work. Identify a small problem for a proof of concept while you’re conducting the maturity assessment. “You can't boil the ocean, but you should be dipping your toe in the water to see what it's like for you.”
Generally speaking, who should be in charge of handling this AI strategy? Carruthers admits she has a slightly glib answer: “It’s the person who cares the most in most organizations. There is a level of excitement that goes with this -- which is fantastic -- but there's a level of tenacity and resilience needed if you're going to follow through, so you need a little bit of that passion to keep you going. I don't care if it's the CTO or the CIO or the CDO, as long as there is one clear owner to drive this through, someone who is going to make this happen.”
What pitfalls should an enterprise be aware of before building its strategy?
“One of the interesting challenges we're facing is that generative AI is the most popular hype that's going around. It's a bit like if you only have a hammer, you can't build a house because there are more tools needed. At the moment, we're falling a bit into, ‘everybody's got a generative-AI hammer so every problem looks like that is the solution you have to use.’ There are multiple types of AI out there, some of which are much more interesting to me. It's just that generative AI is the one that has caught the public interest. That’s one of the pitfalls: are you trying to talk about generative AI or about AI? Get that piece figured out first.
“Generative AI is solving simple, real-world problems. I find it fascinating because the really interesting stuff about generative AI isn't necessarily coming from the likes of data practitioners. It's people who've suddenly got a tool in their hands going, ‘Well, I can solve a personal problem with it.’ My son and his friends are all using it as almost a little personal assistant. They figured out how to use it in a way I wouldn't have.”
Carruthers thinks there is a tremendous amount of potential with copilots. However, she adds a note of caution for anyone who works in a regulatory industry or anything that has strict legislation. “Generative AI is not something I would really want on my plate if I had to describe how I'd made a decision. However, some copilots give you access at the right point in time to a specific piece of information; that could be a game changer for decision-making. That I could see being fascinating going forward.”
Carruthers likes to think about AI more as augmented intelligence because of what it can do for us. “I like to imagine AI as a giant mountain that we can stand on top of so we can see further. We can do more when we can see more capability around us. That's the way I'd like it to be, and that's what I think we should be focusing on when we're building these types of strategies. How do we enable that? It isn't about replacing the human decision-making process. We're quite good at a lot of things. I think we forget that. How do we just be us, but better?”