How companies are trying to leverage AI

It sure feels like we’re on the verge of an artificial intelligence revolution in many workplaces. New tools like chatbots and image generators have taken the tech world by storm, but many businesses across the economy are still figuring out what exactly it means for them.

That’s often where firms like Accenture come in. It offers business services and consulting. Last month, Accenture surveyed more than 2,300 C-suite leaders across industries and around the world for their thoughts on integrating generative tools into their workflows.

Marketplace’s Meghan McCarty Carino spoke with Lan Guan, the global lead for data and AI at Accenture, who said the survey found almost universal enthusiasm. The following is an edited transcript of their conversation.

Lan Guan: Ninety-seven percent of the survey leaders were telling us they strongly believe that this technology will be worthy of long-term investment. We also have survey leaders who are telling us they are not there yet. That’s why, in fact, a lot of the conversations that we have been driving from [the] Center of Excellence over the last couple of months is actually demystifying for clients, to say, “OK, these are the 10 things that you need to be preconditioning your systems, your data, so that you actually are getting more prepared.”

Meghan McCarty Carino: Can you give me some examples of how business leaders are actually looking to integrate this technology? What are some of the, the use cases that are the most prominent?

Guan: If we look at the existing use cases that are top of mind for cross industry clients, there are five of them. A lot of kinds are looking at how generative AI is impacting the software development space. They want to know, “How do I use the generative power of this artificial intelligence to autogenerate system documentation, to write code, to automate testing, to come up with test cases?” I think the second thing is customer service, so using generative AI to handle simple support requests, to do call summarization to help agents become more productive. That’s also another overwhelming thing. I would say the third area is actually in finance and accounting. We’re seeing business leaders are getting more interested [in using] generative AI combined with some other quantitative plug-ins; basically, plug-ins are able to do quantitative analysis for forecasting, for example, of the market trends, to also do some simple data analysis using generative AI. So I just found those three things happening today … quite interesting.

So if I look forward a little bit in two years, two other things that I think could become a new trend is actually in the marketing and content space. So the impact of generative AI on creative is pretty profound. So obviously, there are a lot of creative talents today who are playing with generative AI tools. It could be text tools, writing tools, image tools. But we predict that in two years, more and more of them will be using this across the entire content supply chain, not only generating copies, but also using generative AI to produce visuals and personalized ads that are tailored to customers’ specific needs. So I think there’s a lot of potential there.

McCarty Carino: I think a lot of workers hear about these plans for rolling out this technology with some amount of trepidation about what it might mean for their jobs. I mean, do you have a sense of how companies are thinking about how their human workforces fit into this picture?

Guan: This is top of mind for many of my clients. The role of generative AI to bring more augmentation to everything we do is so profound. I will say the second part is actually training. So as part of our training curriculum, we also focus on this persona to bring different kinds of courses. Maybe for the technical track, you have to take 40 hours of training a week, but then for business track we focus on application, we focus on ethics issues of AI. So something that I think has been resonating very, very well with our business leaders.

McCarty Carino: When it comes to ethics and potential for bias or other issues with the outputs of generative AI, how are you thinking about that?

Guan: First of all, right, the topic of ethics and bias is absolutely in every single client conversation we’re having. More guardrails need to be put in place because of the generative nature of this type of AI. That’s why in Accenture, we are approaching this using a very holistic, responsible AI framework, going beyond ethics and fairness. Now we’re adding things like accuracy, so making sure that there’s no toxicity, there’s no cultural biases where you’re taking care of all these cultural nuances in the language outputs, in your video outputs, is something that we are addressing using responsible AI.