#74 Integrating ChatGPT into your Business Processes and plenty of Use Case
12 Mar 2023 · 22 min
In this episode of the Process and Automation Podcast, hosts Sascha Cutura and Arno discuss ChatGPT (powered by OpenAI's GPT‑4) and its rapid rise as a versatile AI tool. They begin with a brief overview of what ChatGPT is, how it works, and why it has captured massive attention. The conversation then shifts to a comprehensive tour of business‑focused use cases, organized by functional area. They explore how ChatGPT can automate and augment customer service, content creation, marketing personalization, data analysis, language translation, HR processes, finance and risk management, legal document work, healthcare diagnostics, education and training, investment management, fraud detection, and sales enablement (lead scoring, personalization, forecasting, coaching). Throughout, they stress the importance of human oversight, the role of APIs for integration, and the potential to combine ChatGPT with robotic process automation (RPA) to turn unstructured data into structured workflows. The hosts also touch on adoption challenges, the beta nature of the technology, and the fast‑moving competitive landscape, concluding with a call to listeners to experiment with AI‑driven automation and to follow the podcast for more insights.
Chapters
Hallo und willkommen back to another episode of the Process and Automation Podcast with the Automation Guys. Yeah, and today we have another ChatGPT episode. So as you know, ChatGPT is the latest AI tool. To take the internet by storm. I think pretty much everyone is using it out there, so I fiddle around with it myself a lot. So yeah, and it's an intelligent chatbot from OpenAI created, yeah, using the company's existing technology GPT-4. So the bot is also the best language processing AI model available online today. And yeah, So, so what is ChatGPT? Well, we asked ChatGPT about itself and this is what its response. ChatGPT is a conversational AI language model developed by OpenAI. It was trained on a large corpus of text data to generate human-like text based on the input provided. It can be used for various NLP. NLP stands for natural language processing. Yeah. Can be used for various NLP tasks such as question answering, text completion, and conversation generation. So yeah, that's what, what the system says about itself. But in simple terms, ChatGPT, yeah, is a chatbot designed to understand human language, generated human-like, yeah, generates human-like responses and engages in that conversation. So Yeah, it is. It's a tool really that anyone can utilize. And yeah, users can input hundreds of questions or requests from a basic query to, yeah, to, to ask, to asking the bots to write a social media post or an article. Yeah, and it can even act as a recruitment consultant to help with interview preparation or plan your holiday itinerary. Yeah, so that's, that's quite, quite cool. And there's so many, so many cool problems out there. I guess when you go through whatever feed on social media, you will find that, find something about ChatGPT and the right questions to ask. Yeah, so it's, it's still in beta phase, although it's already really cool. Can you imagine how, how good it might be if it's out of beta? Probably it will always be a beta, but it's already a really compelling tool. OpenAI plans to launch GPT-4 to the wider audience. So currently, was GPT-4 available? This is only for the, for the paying customers of ChatGPT. So yeah, yeah, it definitely will be even more powerful. And there's some really good comparisons out there, how compare how powerful it is. You see a little dot and how powerful ChatGPT or GPT-4 is, and you see like a huge, huge circle. So that just, yeah, just visualizes the capabilities, I think, quite well.
So, Arno, so the big question is, why is this thing gaining a lot of traction out there? You know, ChatGPT has taken, like you said, Sascha Cutura, the world by storm, as users can apply the technology for several use cases that weren't previously available. You know, obviously using its natural language processing and machine learning capabilities, ChatGPT can understand effectively hundreds of user requests and provide very, very useful responses. It's also been designed to provide more structured and reliable answers rather than just one-word responses. And again, this ability is part due to the dramatic improvement of AI in general. So users can use the bot to help them write content. The output should obviously not be directly copied and published without review. You have to check these things, but you know, it does provide a very, very strong starting point by summarizing complex information or, you know, highlighting new ideas. And, you know, what we're seeing is ChatGPT is gaining popularity due to its potential scalability. So, for example, a user could ask for a shopping list, prompting the bot to, you know, to do for cuisine requirements and a budget. I've even seen people putting ingredients together and asking ChatGPT to come up with a recipe. It did come with a health warning to say not all of the recipes ChatGPT produces is edible, which is quite funny. But that aside, You know, with, with all of this advanced language capabilities, ChatGPT can handle large volumes, you know, of these user requests. It's also got an API, and this means it, you know, positioned itself as a very cost-effective AI solution. It has massive potential for businesses, you know, looking to roll it in within their automation products.
Yeah, really cool. Yeah, so very exciting. So let's look at a few applications of ChatGPT generally in sort of in the business area. So what, what could ChatGPT do? Customer services, for example. Yeah, ChatGPT can be used in chatbots or virtual assistants to provide customers, especially if you have that APIs somewhere plugged in, you can put those things in your systems and provide customers with quick and accurate responses to their inquiries, allowing businesses to automate customer service. And of course, because of— oh, sorry. Yeah, because of that, it will reduce the workload of the humans in the customer services departments. The next one We touched on this already, because it understands text really, really well, it can help us doing content creation. So it can be used to generate social media posts for the business, articles, product description, landing pages. The latest version can even generate whole websites based on an image you can provide. So really, really powerful stuff. Yeah. That definitely can save a lot of time and resources within the business. Yeah, and if you create content regularly and a lot of that, yeah, it could be nearly on autopilot and you're saving lots of money and time which can be applied somewhere else in the business. Yeah, so marketing is one thing as well where ChatGPT can help, and especially when it comes to personalized marketing, it can really analyze the customer data. And obviously when you think about your customer, you put some personalization in the emails, and that is really, really powerful if you do it yourself. But if you want to automate that, in the past it wasn't so easy. And yeah, with ChatGPT, you can automate those kind of things too. Yeah. So that obviously helps your business to increase the customer engagement we all need. And very early in the process of marketing, it can help you doing the conversions you need in the business. Yeah, so that's very, very powerful.
Also, I'll go through a few other ones. So again, these are sort of just general applications. Inside business. Data analysis is a good one where you can use it to obviously analyze large volumes of customer feedback, for example. So things like social media posts or customer reviews, and then you could use that to identify patterns and any insights that, you know, can inform you to make better business decisions. Of course, the obvious one is language translation, so you could you know, provide these language translation services to businesses or perhaps yourself if you operate in multiple countries and you need to communicate, you know, with your customers or even employees who speak different languages. And this can be on-the-fly sort of translation. I've seen a specific use case where it is automated email translation. So it's no need to copy and paste into Google Translate. And the plugin just kind of does that for you. And then of course, you know, we talk about HR a lot in the podcast, HR scenarios, and I think HR management is a big one as well. We can automate various HR tasks such as answering common employee questions, perhaps scheduling job interviews. You know, it could help you to onboard new employees. And even managing employee performance. So if you train your models according to your requirements, you know, these are some of the common HR tasks you can automate. Things like financial analysis, for example, where you could look at financial data and analyze that using ChatGPT, and that provides you insights on, you know, budget optimization, perhaps forecasting, or even things like risk management. Specifically financial risk management. Then legal services. So obviously I'm still talking about applications generally inside business. So we're sort of skimming over the different types of disciplines and you know, you could use ChatGPT to assist in any legal research. That's perhaps document reviews, contracts analysis, things like that can be very useful and also you know, you can automate things like drafting of legal documents such as your contracts, customer agreements, and, you know, non-disclosure agreements. So again, sort of a lot of application. I would say these are kind of back office type examples. But again, you know, even if you just look at the last one, we look at contract management, that in itself can be quite expensive. Operation, if you have to send contracts to legal counsel. So I can imagine there are some scenarios where this can be very, very useful, especially when contracts are quite standard and you need ChatGPT just to generate them and check them to make sure they are compliant with, you know, all within your sort of legal parameters and framework.
As you can hear already, so it really touches every area you can think of in businesses. And yeah, let's continue on that a little bit. Education and training is another area. ChatGPT can be used in e-learning platforms, for example, to provide personalized experiences for the students. Yeah, and it can also be used in employee training programs to provide quick and really interactive training modules. So based on progress and understanding of what's going on. So next one is healthcare. ChatGPT can be used to provide that. That obviously will be really cool to provide medical diagnosis and advice. Obviously, I have to be careful what is coming out of that, but it can definitely support there very well. Yeah, monitor patient progress and provide feedback. So that, I guess, applies to lots of sort of AI tools out there. So they can, they can support there a lot. Yeah. And then analyzing their medical data and provide insights on areas such as disease prevention and management. So yeah, there are some, some groups out there, they are specializing around that healthcare area. And yeah, so we can all benefit from that. Get a quicker analysis and we don't need humans maybe in the early phases of training those models. But it's already used a lot as well as now in cancer diagnosis and going through all the images. And yeah, yeah, investment management is another area where ChatGPT can be used to assist, to assist in investment management by Yeah, by looking at the market data and come up with some information in real time, sort of suggesting trends and yeah, and also identifying investment opportunities just because of how, how good the AI can go through the huge amount of data. Yeah, it can be used for those things really, really well. Yeah, portfolio management and all those things, asset allocation, risk management and diversification. So these things are all coming up in that area. Yeah, yeah, yeah.
And I guess just fraud detection is another one where you can again analyze large volumes of data. I mean, you can detect and prevent fraud. So the way it works is it looks at the data and obviously identifies some patterns and anomalies. And you know, when it looks at your transactional data and obviously look at things like customer behavior and really sort of provide you those early alerts for suspicious activities. So obviously, you know, within sight, the realm of non-fraudulent transactions, you know, I guess the model learns that that's sort of how things should look like. And anything that falls outside of those boundaries, that's stuff that, that's flagged. And again, you know, that That kind of ties in hand in hand with, with risk management, especially around sort of financial transactions. We talked about financial planning and analysis as well. So, you know, that, that again sort of ties in with, with the financial elements of a business. And then earlier you did mention the customer service. So it sort of brings all of these I guess these things that's important for a business, perhaps internally, but also customer-facing. So it provides you that capability to really, you know, push some of these tasks out to an automated AI machine and then perhaps design your systems in such a way that humans are still kept in the loop. So you mentioned the the healthcare scenario where you provide medical diagnosis and advice. So perhaps, you know, the use case there is to have a sort of an early detection as to what I think perhaps the diagnosis is, but provide reasons why. So a trained clinician can then look over that and still vet that. But it's, you know, it's like we said earlier in the conversation, it's like a starting point, isn't it? To really try and expedite some of these tasks. You know, I did see that especially around sort of financial planning, risk management, contract management, they are sort of a crowd out there that's very skeptical about this, you know, and there could be various reasons. But, you know, I think like you say, from GPT-3 to 4, it's just massive increases in its accuracy. So, you know, once we get to 5, 6, 7, 8, you know, I think this will become a lot more powerful and mainstream. And, you know, it's, it's, it's like the age-old, you know, saying of, you know, when cars were invented, people didn't know how to use it, so they put a horse in front of it to pull it. But, you know, I mean, there's a lot of resistance. Steam trains as well. When, you know, electric trains and diesel trains were invented. So there's a lot of skepticism. But I think with this, it is a maturing technology. That's why it is sort of, you know, out there. A lot of it is beta. A lot of people are folding this into their products as well, which is quite interesting.
Yeah. Yeah.
You know, it's very topical. A lot of our listeners are asking us about this specifically on how do you apply this.
Exactly.
Yeah, on this, these examples are quite useful to, you know, to sort of think about its potential, you know, with inside your business. And if you look at unstructured data, turning that into structured data, of course you can take all of those inputs and then plug that into robotic process automation, for example, workflow automation. So again, it is just a place to to classify information, and then once it's classified and structured, use that then to follow perhaps, you know, orchestrated business processes within your organization.
Yeah, and the progress is really, really fast, isn't it? So I think in the beginning of the year everyone started talking about ChatGPT. Yeah, yeah, ChatGPT-3 is out for quite some time, was bundled in some other tools. But now we are just a couple of months down the line and the new module is out there and used by millions every day. So I think, yeah, the next step will be, will arrive very, very soon, very fast. Yeah. And then obviously there's lots of competition out there in the market to do all these things and maybe some specialized tools coming up, right? We'll see specialized, similar like just looking at sales stuff. So one topic which is really, really specific we could look at and sort of, yeah, it's a very, very popular topic. How can maybe AI in automation help in sales? As one example, so lead scoring pops up here in my mind. So you can use ChatGPT to analyze that the customer data you have and provide a score indicating how likely is that prospect to turn into a customer.
So obviously you see that's always email clicks and yeah, it's always a difficult thing, isn't it?
Yeah. And this can help your sales teams to look at the leads in a certain priority and focus just your efforts on those with a high score and then get rid of the ones in the low score and let automation then kick in again and nurture them further. So We talked about this personalization element before, specifically in sales. It could provide personalized product and service recommendations to customers based on their preferences. Currently, salespeople have to do all that manually. Sure, you have marketing suite, but you have to configure it. So it gets, it's very complicated. And if you have an AI or that system, ChatGPT, plugged into it, to do all these things itself, that would be amazing. Yeah. And obviously sales support, you can really see that real-time customer data, you see the purchase order straight away, you can act on it, see the customer preferences, the feedback, and then let ChatGPT to come up with a very good decision or suggest decisions how to do better customer service. And of course it can support in training of the sales team and coaching. Basically can sit there and see what the inputs were and suggest recommendations or recommend how they can improve and become more productive and more effective.
Yeah, and I guess you could also, you know, it can help you with sales forecasting because you can look at your sales data and, you know, it's going to look at your existing data and then from a predictability sort of look at your future sales trends and patterns. So again, you know, you can just then from a sales perspective, look at your strategy and adjust that. And customer retention is obviously important. So you could again sort of look at your customer data and look at, you know, customer behaviors, their preferences. And, you know, again, that can really help sales team to identify, you know, the right sort of perhaps products to target the customer with and also, you know, identify areas where they can improve and develop targeted retention strategies because obviously that will keep customers engaged. So overall from a sales perspective, and I think, you know, it's important for us to actually touch on sales because, you know, that is the heartbeat of a business. It does help your sales teams, will help them to increase their productivity, improve the customer engagement to kind of get to those insights and really grow sales through personalization and real-time sort of ability to look at sort of real-time know your customer insights. And like you mentioned, the sales training and coaching. So sales is sort of one important example. You know, just another example is legal teams. So, you know, if you look at corporate legal departments, you know, if you look at them, historically they have been kind of slow to adopt automation technologies and, you know, and sort of the changes of how they work. So, you know, These, you know, with these examples that we've mentioned, you know, and if you bring in sort of robotic process automation and AI and, you know, machine learning technologies, this opens up that the ability, you know, for these teams to adopt automations that allow them to execute sometimes things that will take weeks within a matter of hours or even minutes. So, and again, for years people thought this technology would replace humans in the workplace because obviously RPA has been around for a very long time, but instead it is actually helping to redefine all of the, you know, these workplace processes and sort of just making it better. And again, you know, legal teams' work is often, you know, quite, you know, manual-heavy or manualic. And, you know, it's heavily focused on language and long-winded documents. You know, so again, with these latest advancements that we see in AI, and the processing or the whole sort of, you know, the changes to press on with, do more with less. You know, ChatGPT has definitely got the potential to reduce the pressure on legal teams by, you know, accelerating these sort of manual-heavy tasks. Yeah.
So what comes to mind here when you're talking about the legal teams, Arno, is So when, when really used correctly, ChatGPT can, can support very specifically in this research area within these legal teams. I think, yeah, law has lots of data, lots of laws, regulations, compliance elements. So just keeping up with that, I think it's so, so time-consuming. Very often that's, that's down to, and then in some, some legal cases down to the, to the juniors, isn't it, to go through is a vast majority of data. And then, yeah, now with ChatGPT, that could be so much easier. Document reviews comes into that as well. So it can look at the contracts and summarize and find certain things and look for certain things. And yeah, really, really support the teams and And of course, predictive analysis is a really, really cool topic. Yeah, it can analyze all this legal data. Yeah. And then provides that insights to help them to make better decisions. So yeah, it is an exciting technology. It is not just ChatGPT, as we mentioned. It's just one form of what GPT GPT-4 can do. So there's so many different models out there and using, using OpenAI's GPT-4, so it can generate images and do all sorts of stuff. So yeah, really exciting to, to really apply that in, in the business. So we, we have explored how ChatGPT can be used in, in those areas from customer service, marketing, finance, and sales, and leveraging the power of AI, ChatGPT, ChatGPT can help pretty much every business to become more efficient and therefore reduce costs. And yeah, it ultimately helps to improve customer satisfaction. So that's all what we want. Yeah, reach out to us on theautomationguys.net. Listen back to other episodes we had on the topic AI and ChatGPT. And yeah, we will be back for more. Episodes. And until then, let's automate it. Unfortunately, that's it again with this episode of the Process in Automation Podcast. If you like this episode, please give us a 5-star rating and don't forget to subscribe to this podcast so you don't miss any upcoming episode. We hope you will tune in next time, and until then, Let's automate it!
More from Sascha
EP112: Inside Enterprise Automation, How Yexle Delivers Real Impact with Appian w/ Vijay Poondy
EP110: Turning Insights into Action with GenBl w/ Dr. Andreas Koeberl @ milo.ai