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Welcome to the Ksense Technology Podcast where we discuss the trends in software development, web applications, and how custom software can help businesses scale. Ksense is a full-stack software development company using state-of-the-art technologies to build cutting-edge applications. With over a decade of software development experience, our team is confident we will deliver results for your organization.
Calvin Smith [00:00:00]:
This is how we can stack these technologies on top of each other to achieve, like, basically mind boggling automation efficiency.
David Guthrie [00:00:07]:
You might not want to go to a robot barber, or you might not want it to be the person who serves you your food at a restaurant. Okay, welcome, everybody. Excited to be here today with Calvin. He's the COo at ksense Technology Group. And what they do is they build business software, custom software, to do all kinds of specific tasks or to provide solutions to all kinds of organizations. So I'm excited to talk to Calvin today about the future of business automation. What does business automation look like now, and where's it going in the future? So thanks for joining me, Calvin.
Calvin Smith [00:00:46]:
Yeah, thanks for having me.
David Guthrie [00:00:48]:
You bet. Awesome. So for my first question here, can you just explain to us a little bit about what automation is?
Calvin Smith [00:00:56]:
Yeah, so business automation is basically just what it sounds like, creating processes or using tools or even using other methods, like AI, to basically allow your business to run without you having to be directly involved in doing those tasks or performing that work. So there's a whole bunch of tasks out there that, you know, people used to do by hand, obviously, like before we had really good machinery, people used to, you know, work in factories and build things by hand or, you know, for farming. Before we had tractors, people used to plow by hand. And it's the same with digital businesses and information businesses, where in the old days when computers were first getting invented, people used to do a lot of stuff by hand that we just completely take for granted. Nowadays, you know, scheduling, writing, even like spreadsheets, stuff you might do in a spreadsheet nowadays was done completely by hand. But now we're moving one step further where those tools that used to be considered business automation are now no longer necessarily considered business automation. Like a spreadsheet, for example, is now considered pretty manual by today's standards. So really what we're doing with business automation is continually pushing the boundary of how much can be automated to the point where, you know, you're focused on the very best, like the very highest level tasks that really require your brainpower and really require your domain knowledge without having to waste time on those tasks that, you know, may be repetitive or maybe, you know, just sort of tasks that, you know, a computer can do.
Calvin Smith [00:02:33]:
So I hope that gives you a good idea of sort of what we're talking about when we talk about business automation.
David Guthrie [00:02:38]:
Yeah, it's cool to think about how the definition of automation might change over time. It's hard for me to define it past just using the word automation. But what that means over time definitely changes and shifts. And the impact that automation can have definitely changes over time. Let's talk about some of the benefits that people are getting from automation. What are, I guess, some of the reasons that people are looking to automate business processes.
Calvin Smith [00:03:08]:
Yeah. So people's expectations tend to shift over time. Like, you know, we'll talk about AI a little bit, but, you know, when, when GPT four first came out, or even chat, GPT-3 first came out, people were blown away by it, and now it's just, you know, business as usual. People don't really think about it as impressive, whereas if you would have shown this to somebody ten years ago, they would say, oh, this is, you know, this is human level intelligence. Right? So the same with business automation where it's like, the more these systems can do for you, the more people just expect it, including customers. You know, they expect to be able to have an automated experience where everything's streamlined for them, where they can go into the app that they're, or use your service or book a call or do whatever in a way where it doesn't really require them to do much thinking. So the main benefit of automation is that I, people can get more done with less effort. That's really the bottom line with it.
Calvin Smith [00:04:05]:
So your customers can get more done with less effort, which means they're going to enjoy working with you more because you're not making them burn calories to do things like schedule a call or do calculations or figure things out that a computer could figure out for internal business operations. Your employees are going to benefit because they don't have to do as much thinking and checking for errors and manually checking data. Things like this can be automated and really reduce the amount of effort people can put in to the parts of the business that are tedious, repetitive, error prone things that people don't want to spend their time thinking about, when they could be spending their time doing creative work. So that's really what it comes down to with business automation, is how can we reduce the effort on the employees, the customers and the business leaders so that they can get more done with the same amount of time?
David Guthrie [00:05:08]:
Yeah, makes sense. So there's all these benefits that people are really looking to get from automating something, making it more efficient, making it more seamless, smooth, stress free experience for their customer. What are some of the ways that you've seen companies do that? What are some ways that you've seen them automate either a task or just an experience for their customer.
Calvin Smith [00:05:34]:
Yeah. So the main things that businesses are doing nowadays with business automation is it's taking their data and centralizing it. So there's just so much that can happen when all of your data is in the same place. And, you know, it sounds pretty broad to say it that way, but if you think about it in terms of your own business, are there areas where you're having to move data that's in one place to another place? Like if you have data in a spreadsheet or you're having to then copy that data into another system, or enter that data twice into two different systems. Like, there's a lot of areas where just moving data around and keeping data up to date is extremely important. Also connecting people with the data they need. So, like, you have customers who need to know certain things, you have employees who need to know certain things. And when people are trying to make decisions, like business leaders, they need to have certain information in front of them.
Calvin Smith [00:06:33]:
Automating the flow of that data so that you know that data is in front of you when you need it, and it tells you what you need to know. That is a huge part of business automation. And then there's actual tasks that can be automated completely or streamlined massively by building certain systems. Like, let's say you need to send quotes to your customers. Well, there's a lot there, right there. There is pricing information that you need to have access to. So maybe right now you have a big spreadsheet and it's full of different prices and then also different inventory levels. So you know what you can sell to the customer.
Calvin Smith [00:07:11]:
Like, do you have this part available to sell? And if so, what's the price point of that? So how much? Like, when you're building the quote, if you have to put 30 of those parts in, how much is that going to be? You have to think about this in advance because it takes time to ship those parts. So it's like if you had all that information sort of aggregated and automated, so that basically all you have to do is like, okay, I need to send a quote. You pick the part you want to include. You pick the line items to include in that quote, and it just automatically you put in the quantity, and it's like, okay, here's the price for this quote. Here's the total for the quote. And you also are able to project in advance your inventory level so that you know that by the time that customer orders that part, it's going to be shipped and available to send them. Right. So automating these type of processes.
Calvin Smith [00:08:02]:
These are some of the things businesses do. And this is an inventory management example. There are countless examples across different industries of different use cases for business automation. And really the main thing that we do is we build interfaces for businesses so that like apps and user interfaces that they can use to actually get work done. Sometimes businesses, they're using a spreadsheet. Well, that's an interface, right? You're opening something on your computer, you're either entering data, reading data, you know, deleting data, or updating data. And we can automate that instead of having to use a spreadsheet where errors can happen, where the data is incomplete, we can automate that and put that into a web application where these, you know, instead of having to build each equation in the spreadsheet and making, there could be mistakes or, you know, those constantly have to change depending on business needs. Like all that logic can be built into the web app, so that all you have to do is the simple work of, let's say, building a quote and choosing what products are on it.
Calvin Smith [00:09:04]:
And in the background, all those analytics and all of those data points are automatically aggregated and the right calculations are made. So yeah, that's hope that gives you a good idea of some of the use cases. Obviously there's tons of different use cases. And part of what we do for our clients is we'll talk to you for free. I mean, we can discuss your use case and I can tell you what, based on my experience in your industry, you can tell me what your problems are, and I can give you a good idea of what types of business automations are available in your industry.
David Guthrie [00:09:37]:
Yeah, that's awesome. And you mentioned logic. I think that's a really big piece of automation, is how much logic is needed, how much decision making needs to take place in this process to get a good result. And so if you've got a process that's really rigid, really kind of black and white, yes, no questions, then that's easy to automate. How do you handle levels of complexity? Like for example, if maybe like the mortgage industry or the solar industry, where each customer might be coming from a different place and there might be regulations around how the processes need to go? So there's a lot of decisions that are taking place, is that pretty much the same thing? Do you just need to add more and more logic rules to how the process works? Or is there kind of an evolution of automation? Are there different kinds of automation or different approaches that allow you to handle these complex situations?
Calvin Smith [00:10:43]:
If you think about decisions that need to be made. A lot of times, if it's black and white, the computer can make those decisions automatically. The logic and the app can make those decisions. Sometimes it's about putting the right information in front of a human so they can make a decision easier and quicker. So in a solar industry, if you're building a quote and you get a call from somebody who's in a different state, maybe, and they have different regulations, it would really help if all those regulations are pulled up on the screen. This customer's pulled up on the screen, you could see a satellite picture of their house. So you know exactly what it looks like. So you can give them a quote right on the phone and then send a tech out.
Calvin Smith [00:11:25]:
See, you could see what techs are available in their area, exactly which tech is closest to them and would be able to come out the soonest. So, like, all this information, just putting that in front of the person who's, let's say, the call center rep or the, you know, even the. The employee at the business who's sitting there receiving those calls, that is, you know, obviously gonna massively automate their job, even though ultimately they have to make the decision of like, okay, which rep are we going to send out? And can we service this house basically based on the zoning regulations or whatnot? Right. So that's one way to go. And that's like, you know, every single problem you have in the business, there is probably at least some level of automation that can be applied to it. Even in this framework, in this paradigm, where it's like humans still have to make the ultimate decision, it's. There's still some sort of business automation. There's some way to streamline it, some way to make it better, faster, more accurate.
Calvin Smith [00:12:19]:
Like, there's going to be solutions in almost every single situation. And then with AI, the fact is, oftentimes things that we considered, you know, human level decisions are often being automated completely by AI. So there's a whole, you know, area, there's a whole use case. There's like, many, many different use cases for AI that is starting to emerge. And basically what we can do there is actually analyze your businesses and identify, okay, is there anything that an AI could do? I mean, really, AI is just another tool in our arsenal to automate your business. Right? So if there are certain areas in your business where, for example, text generation is needed, text summarization, classification, image generation, like these certain use cases that generative AI is extremely good at, then we can just build that in, because that's part of the app that would be part of the product. It's basically a tool. And oftentimes to leverage these AI tools, you do need to build it into the app or customize it with code or do something like that.
Calvin Smith [00:13:26]:
So that's just part of our toolbox now. As AI has evolved, we have really good understandings of which model would be best for this use case. There's countless tools out there now that basically make it easier for developers to implement AI in your web application and customize it to your business. Really, it's the same process. It just gives us even more to work with, even more ways to automate. Because now if you have something that, let's say customer support email or a chatbot for your customers, instead of now having to build an app where a human's going to sit there and know, like I was saying in the solar example, they're going to sit there and they're going to look at all the information, you know, the zoning laws, the location, and they're going to have to manually create the quote, well, now you can possibly have an AI do that, you know, like, and it'll be instantaneous, it'll be more accurate, and the customer will be able to go on your website and get a quote and have it sent to their email immediately rather than having to wait for someone to answer the phone. Like, also some customers don't really like calling into a call center because they feel like they're going to get sold on something. So there's just so many opportunities for AI to be integrated as well.
Calvin Smith [00:14:46]:
And really it's just expanding business automation rather than shrinking it. It's giving us more options to automate. And so part of the consultation we provide too, is like helping you decide what tool is going to be best for your use case, since we have a lot of experience automating a lot of businesses, we can give you the options, say, hey, AI could do this or we could do it this other way. You know, which one is going to be better for your business? We're going to basically take a look and tell you what we think, and then you'll have the tools and the information to make a decision on that.
David Guthrie [00:15:22]:
I think you really hit the nail on the head with the ways that AI can be useful or could be, you know, like we were talking about. We have sort of the rigid portion right where there's a really black and white decision that needs to be made. Does it go down this way or does it go down that way? And then when you get to that point where you need to sort of make a decision based on your best judgment or maybe based on a really complex series of decisions. AI models tend to be really good at things like classification, right? So if you can basically keep the decision making as rigid as possible and use the AI basically just for one little nodule, one little piece of that automation where it basically just says, okay, consider this, how would you classify that and then send it that way? Then the normal automation continues from there, which is just these functions that are rigid and pre planned, but the AI could choose, do I send it down that chute or down that chute based on this information or based on however you might have trained that model to, to assist in that process?
Calvin Smith [00:16:28]:
Exactly.
David Guthrie [00:16:29]:
And yeah, it's very much limited by is that decision making process something that's unique to you and your business, or is it something that a general AI that just has general knowledge of the world would be able to make that decision or that classification? How does that work? Do you need to train a new AI for AI enabled automation? Or is it usually something that general knowledge that the AI is going to have is going to enable it to make those decisions that you need it to?
Calvin Smith [00:17:01]:
So if a general AI is able to make the decision, then maybe you're able just to use chat GPT and you're able to give that to your employees and maybe make a custom GPT on chat GPT and then have your employees access that and use that. Typically you're going to get a lot more out of it if you go more of a custom route. Now, you don't need to make a new AI model necessarily. Sometimes it's just a matter of plugging in that AI model in the right place. So if you're, you know, it's one thing to use chat DBT, that's a whole separate window you have to open. You have to open the website, you have to copy, you have to have text to put in. Right? If you don't have access to that text, like what if that text is, is in your customer's file, you know, like. So then it becomes a matter of plugging that AI into the app so that instead of having to open chat GPT, well, instead you just open the customer's file and the AI writes a summary right there, or the AI makes the decision and classifies it right in the app.
Calvin Smith [00:18:04]:
Right? So that a lot of what we're doing a lot of times is we're using the API of these, like chat GPT or of Google's AI or anthropics AI. We're using their API so that we can build their AI, their general AI model, into your app, so that you have the features in your app that are powered by Aihdem. But it can go a lot further than that, actually. So there's a few different areas where AI is very powerful for business automation. One of them that you might have heard of is rag. It's called rag retrieval augmented generation. Basically, the AI is able to look into its knowledge base, and let's say you put all of your business knowledge, or business knowledge about a very specific domain in that AI's knowledge base. And what that does is it grounds the AI to that knowledge base so that that knowledge base is now the AI single source of truth, right? So let's say you put all of your product information in there.
Calvin Smith [00:19:06]:
You put all of the common questions and answers that your customers ask. You put decisions like, if the customer asks this, then here's what you should say. You put all those things in this database, and the AI is specifically trained that when it. When it receives a question, or when it is put into a situation where it needs to give an answer, it looks into its knowledge and finds the answer there. And if it can't find it, it won't give an answer, or it'll give a pre programmed answer that you tell it to give, which means that it won't be making these mistakes, right? Like, you see these hallucinations that happen on these, you know, on chapter or on other models like that, those can be eliminated by using rag to build a specialized app, to using even a pre built solution out there that takes your business data and uses that as its single source of truth, rather than just whatever data was in its training data, right? So that's one way to go, and that's very good for particular use cases. Now, there's a lot of talk about the next generations of these AI models, and there's a lot of people saying that probably rag will become obsolete in the future because the AI models will not need it anymore, right? Because the context window for these AI models will grow so large, and they'll become much more accurate, and the hallucinations will be fixed. So now you won't need to actually build a specialized rag bot or an AI that uses retrieval augmented generation. Instead, you could just put all of your business data in the AI's context window, which is basically in its working memory, and it'll be able to accurately grab the pieces of information it needs right from there.
Calvin Smith [00:20:45]:
So that is something to think about. And we can help you understand that. If you were to come to me and tell me about your business problem, I can help you understand. Okay, is this a solution where in the short term rag might be a good way to go, or is this something where we can do this a little differently, or maybe even wait on it, because pretty soon that solution would be obsolete. There's a lot of knowledge that goes into choosing the best AI solution. There's also another way to go with AI, which is fine tuning an AI model for a specific use case. And it's actually a lot easier than a lot of people think. So there's a lot of APIs out there and developer tools that are available to basically take some of these AI models and give them very high quality business data.
Calvin Smith [00:21:35]:
So let's say that you want an AI to be able to generate press releases. Let's just say as an example, right? So these press releases need to be in a very specific format. They need to be the same length, like they need to be not too long and not too short. There's a bunch of stylistic things that you need in these press releases. And if you try to use chat GPT or you try to use a standard AI model, it may do five of them, right? And then the other five, it might mess up a little bit, right. So does that mean you can't use it? You can't use it for the press release use case? Well, not necessarily, because if you are able to get together a collection of, let's say, 100 press releases that your team has written, and they're really high quality examples, and you're able to give it the input and the output, which is like, okay, here's the raw information, like maybe an unstructured paragraph or an email or something that describes what the press like, the information that's in the press release, and then the output is this finished press release that's in the right formats, the right length, you know, it's perfect. You give a hundred AI, you give an ex 100 examples, and you run a fine tuning job, which is basically changing the, the AI's brain to match your use case specifically for like $30 worth of fine tuning. You can now have an AI that is perfect at press releases.
Calvin Smith [00:23:02]:
It gets them right 99% of the time. That is a really good use case for businesses, because a lot of times the AI, like chat GPT and these other models are just not quite there yet. But if you fine tune the model, then all of a sudden it becomes exactly what your business needs. And imagine also building a fine tuned model into your app so that now it's like you pull up the customer's profile or you pull up the app in your browser, you click a button and it generates a custom press release, you know, right there in the app, and then you click another button and it emails it. Right? So, like things, this is how we can stack these technologies on top of each other to achieve, like, basically mind boggling automation efficiency like that. It'll save you, it could save your business if you were paying somebody full time to do those press releases, you know, $60,000 a year. Well, one fine tuned AI model and an app could potentially cut out that entire, you know, salary out of your expenses. Right? So, and maybe that person can go do something else in the business that it's less, you know, monotonous and, and less tedious.
Calvin Smith [00:24:11]:
I hope that gives you an idea about how these tools can be used, because there is a lot of ways that they can be used. And people, you know, if you're just looking at like chat, GPT or whatever, people don't realize that AI is already at a point where it can probably automate 50% of knowledge work if it was used in the right way and fine tuned and built into tools. I think about 50% of knowledge work can already be automated by AI.
David Guthrie [00:24:33]:
And so you're touching on some pretty, pretty big topics here. Let's dive into that a little bit more, because a lot of people have concerns around what are the ethical considerations that we need to have when it comes to the technologies, capabilities? And one of those ethical concerns is job displacement. Are our machines going to replace all of us? Are we all going to lose our jobs and not have, you know, any way to make money anymore? So obviously, there's a lot of speculation and it's hard to, you know, we can't predict the future. But in your opinion, should people be worried about that? Should people be, should people be investing in these types of automations right now? Should they be holding off? How does the future look, in your opinion?
Calvin Smith [00:25:27]:
I think that people should be investing in these technologies because when it comes down to it, other businesses are going to invest, really, the next couple decades is going to be defined by the businesses who are able to invest early and powerfully into AI technologies and into business automation. You know, when, if your competitor invests in AI and they are able to cut their costs in half for a particular service, how long are customers going to continue paying you to do the same thing for twice the price? Right? So and not only that, but a lot of these technologies, not just AI, by the way, a lot of these business automation technologies improve the customer experience dramatically in many different ways. If a customer goes on your website and you have a shiny web application that they can log into, and they can see all of their, you know, everything they need to see right there, and everything's super fast, super streamlined. And then when they have a question, they can ask an AI and it can give them a perfect answer or it can print them out a perfect quote like that. That is such a dramatic difference in experience than having to call in to talk to somebody who then says, okay, I'll send you a quote in a couple of days. And then when you get the quote, it's like maybe not what you were expecting. There's just a massive difference in customer experience, too. So really, as businesses, what we want to do is we want to give our customers the very best experience possible.
Calvin Smith [00:26:51]:
We want to provide the very best service we possibly can at the very best price. Right. And we either want to make our shareholders happy or we want to continue growing our business, because at the end of the day, we have a mission to benefit society. We have a mission to benefit our customers and our employees. So, yeah, absolutely, I would invest in these technologies. The question is how to do that in the smartest way and with the least amount of risk. Right. So that's where knowing where things are going is useful.
Calvin Smith [00:27:21]:
So as far as job displacement and where AI is headed, yes, there's going to be job displacement. There's also going to be new jobs created. There are a lot of opportunities in the technology space that are being created, but to some extent, it's going to be hard for some people to transition. If you're a call center worker that's taking phone calls, it might be hard for you to transition from that to a prompt engineer, right? Or from that to like a developer or a business leader or something like that. One of these other jobs that might open up, because there's going to be, first of all, there's a lot more call center workers who, they may be unskilled in those other areas. And I do think that there is probably going to be more jobs over time that are disappearing than new jobs that are being created, even though there will be new jobs created. The reason for that is because once AI takes over a task that it becomes better at than a human, the human never gets any part of that task back. Like, the human will never again out compete the AI.
Calvin Smith [00:28:25]:
Like chess, for example. AI's can now compete in chess at a superhuman level. We're never going to retake that throne. Right. It's not going to happen. And so every time there's another thing that AI takes over better than a human, you know, at some point, there's no more things for it to do better. Right. It's just going to be able to do almost everything.
Calvin Smith [00:28:43]:
Now. I think it's extremely speculative to, to say when that's going to happen or how fast it's going to happen or, you know, exactly. Um, would it be 100% of jobs? Will it just be 80% of jobs? Like, it's very speculative. And for, for most business people out there, they're more worried about the short term. Like, uh, okay, what do I do? What can I do now with AI? And, and is it the right time for me to invest in it now? And if so, how can I, how can it benefit my business and my customers? So looking into the tools and how you can implement them and how you can make your business ready for AI, you know, make a transition your business into an AI ready business, that's where you're going to be able to get benefits. And no matter how things change in the future, the important thing is that you're adaptable to that change, right. That you have the mindset of saying, okay, you know, if we're in the call center industry right now, we have to realize and we have to be real about the fact that soon, like, there are a lot of things in this industry that are going to be automated. So how can you pivot, how can you change your business model? How can you incorporate the technology so that maybe you benefit from the transition, maybe you actually gain instead of losing from the transition.
Calvin Smith [00:29:58]:
You're, you're one of the winners. And the way to do that is to know as much as possible about what this technology can do and how to implement it and to go out there and get consultation on your specific use case so that you can start moving in that direction, hopefully before your competitors do.
David Guthrie [00:30:19]:
I definitely see that where there's some people are jumping in way too quickly into being like, well, for example, I just readdez, I think last week I read about a company that their AI chatbot gave incorrect information about a promotion or like a refund, and then they ended up getting taken to court, and they had to honor it because their official, you know, representative on their website told their customer that they would get this, this deal, this promo. So there's definitely some risk there, you know, and you, you don't want to jump in too quickly to, to going, well, I want to be on the front line of this innovation curve, and I want to be, you know, the cutting edge. But then there's also a balance where you don't want to get left behind. You want to be kind of pushing the boundaries a little bit. You want to be testing out what's, what's possible, what's new? Does it work well for my business, for my customers? How do customers react to it? Right. Because I think that's going to be a big piece of which jobs stick around. You might not want to go to a robot barber, right? Or even if AI is really, really accurate and good at giving you information, you still might not want it to be your lawyer or you might not want it to be the person who serves you your food at a restaurant. Like you said, it's very speculative at this point.
David Guthrie [00:31:38]:
We don't know exactly where the impacts will be and how big they'll be, but you want to find that balance, right, of engaging with the technology. Don't hold back too much, don't be too scared, but don't dive all the way in there either. And make sure that you're getting good advice, right. On what the realistic capabilities are today. What's it going to do for me today, and what can I be doing today so that I'm ready when there's more functionality down the line?
Calvin Smith [00:32:06]:
One thing we can know I'm pretty confident in is that experience, like, experiences are going to be something that people continue to want. Like, there's going to be a premium on really good experiences, and that may be a customer service experience. It may be an in person experience. It may be, you know, like that there's an AI that can do something for your customer, but they just like the way that you like that. They like your user interface. They like your method of doing things because it, there's a bit more of a personal touch to it, or, or something like experience is going to be important. So how can you adjust your business so that you're really providing a top notch experience to your customers and also to your employees? Because there's going to be a talent crunch, too. Like in some cases, like, I don't know, like if you, if you look at AI engineers, like these companies are, are constantly trying to steal each other's employees, right? Because there's, it's such a in demand job.
Calvin Smith [00:33:08]:
So, like, if you basically are able to enhance the experience of your employees and your customers, that's going to put you ahead because even if there is another AI solution out there that can do it, you're going to have a lot more loyalty from your customers and employees if they are able to get that kind of experience.
David Guthrie [00:33:29]:
So we mentioned that, you know, you want to find the right balance in looking forward and holding back.
Calvin Smith [00:33:36]:
Right?
David Guthrie [00:33:36]:
So let's talk about some of those practical perspectives that business owners should have or decision makers should have. What should people be focused on today? What should they be doing right now when it comes to business automation and, you know, kind of keeping in mind where the technology might be going over the coming years.
Calvin Smith [00:33:57]:
Yeah. So I guess the first thing is there are so many opportunities to automate that have nothing to do with aih. Like for your business operations, right? Like for making sure that your business is streamlined and that your customers have what they need and their user experience is really good. I would look at that whole, you know, pipeline and say, okay, is there, you know, what are our biggest pain points? Because the truth is, is that whatever those pain points are in your business or for your customers, there is probably something that business automation can improve or fixed. So, you know, you know, it may be hard to think about it. Like, okay, what type of business automation do I need as a business? That may be kind of hard to think about. But what's easy to think about is what are my pain points? Right. If you think about it from that perspective, what are my biggest pain points today? It's probably something automation can resolve or at least, you know, increase, like a reduce the issue or reduce the pain quite substantially.
Calvin Smith [00:34:56]:
So. So basically that's the first thing I would focus on is how, like, what are my highest priority pain points? And can business automation solve those? And you can do your research on that. You can look into solutions. Like, I spend a lot of time every day, like just researching different solutions and tools because you'll find that you never even knew how many tools are out there that are the perfect tool for you, but you just didn't know about it, right? So I would definitely. Speaking of AI, there are some things it does really well. For example, research is one of them. There's a tool called perplexity that is absolutely fantastic for businesses. I mean, really for anyone who does any knowledge work, including students or anything else.
Calvin Smith [00:35:36]:
Like if you don't have this tool, you probably need to get it because it's like chat GPT, but about ten times better for research, right? Because what, it's basically an AI search engine, like the replacement for Google. It's like Google, but AI powered right. So trust me on this. You want to look into that and doing research into your pain points and starting to use AI as like that research assistant to actually find the solutions that are going to make up the biggest impact for your business. That's the, probably the place I would start is start diving into this topic like what types of automations have you not thought about yet that might be able to solve some of your pain points? And you know, don't be afraid to get some consultation from people that do this for a living. You know, like if you want to jump on a call with me, I'm more than happy to give you some consultation. The thing is, like my philosophy and probably the philosophy of a lot of other people that sort of do this is I'm more than happy to jump on and give you a consultation even if you're not really interested in buying anything from me because I'm getting, I'm, I'm basically building my own brand by helping you. And so it's, it's no problem.
Calvin Smith [00:36:53]:
Like if, you know, don't be afraid to reach out to an expert to actually talk about some of this stuff and see how you might be able to improve your business with, with this type of automation. So I'd say that's, those are my main tips. I would say.