A conversation with experts from Accenture on making the most of LLMs.
Generative artificial intelligence is here to stay, and that means employees and managers need to think even more carefully about how to make the most effective use of it. Accenture’schief technology and innovation officer, argue that we all need to build what they call “fusion skills.” They include intelligent interrogation , judgment integration , and reciprocal apprenticing . They offer advice on how to hone all three.
ALISON BEARD: This might seem obvious, but why does Gen AI as opposed to the AI that’s been around for years promise to be so revolutionary for all kinds of workplaces? H. JAMES WILSON: Yeah, absolutely. I think it’s important to not look at AI as a zero-sum game, as human versus machine. When workers use it effectively, they see that it’s really about collaboration. Collaboration with an intelligent new colleague in a lot of ways. It’s about the advertising writer using AI to augment her research, her brainstorming and so on. It’s really about amplifying that writer’s work in two or three of her jobs, maybe 10 or 15 tasks. It’s not about wholesale replacement.
PAUL R. DAUGHERTY: Well, there’s three that we’ve really singled out that we think are particularly important for all of us to focus on. The first is intelligent interrogation, and this is how you use different techniques in terms of how you work with these generative AI models to get better results out of them, so it’s how you interact, how you work with the models.
H. JAMES WILSON: You know, one of the really interesting features of generative AI is that natural language is the new programming language in a sense, so you don’t need to be a data scientist or a software engineer to get these systems to run really complex tasks. This is really opening up all sorts of new ways that AI can be brought into your knowledge work routines, your creative work routines, like market analysis or brainstorming.
ALISON BEARD: That was cool to me that you could just say something as simple as that, like do this in a step-by-step fashion, and the AI would come back at you with answer that was more clearly thought through or more transparently thought through. There does seem to be this common theme intelligent interrogation of breaking down your work.
PAUL R. DAUGHERTY: One of the areas where we see it being applied a lot really foundational is in the area that’s getting a lot of focus right now, which is software development and coding itself. It is a very stepwise process. If you’re writing software, you’re gathering data, you’re analyzing it a certain way, you’re writing code to do certain things and you’re testing the code.
H. JAMES WILSON: A lot of the tacit parts of our work, a lot of that tacit dimension is about context. Your company wants to grow its product line in say, Southeast Asia, but there’s also this other context in the back of your head that your company also wants to streamline its product portfolio in Northern Europe. Your company is going to be very culturally and strategically and operationally different than its industry peers.
ALISON BEARD: Okay, so let’s get to judgment integration. This given concerns about AI seems to be maybe the most critical, the whole human in the loop idea, but what does it look like in practice? Is it setting up good parameters to start, recognizing when it’s time to interrupt and correct work? Where are those touch points where human judgment comes in and works effectively?
One company that we’ve talked to in our research right now is aiming to launch 15 new products over the next five years. They’re really aiming to turn the whole company into a product innovation lab from marketing to sales to service and so on. They’ve really invested in giving their non-technical experts the right training to make effective judgment calls, and also, the time to learn through experimenting with these tools in their roles.
Historically, at a lot of companies, the underwriters have only had time to read about 10% of the inputs coming in because they just didn’t have time to get through it all. Now with generative AI, you can process 100% of it to still the key facts for the underwriters that they could make better decisions and they could ultimately then make the right judgment. Because in this case, generative AI alone wouldn’t be able to do it.
I think the second leadership quality that’s important is learning with humility and continuing to learn the new techniques and new ways that you apply the technology. Finally, there’s a culture and learning element of it where the more you can help the people, all the people in the organization understand, embrace the technology, the more you’ll be successful in applying it to transform the business.
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