Artificial intelligence (AI) Benefits and Advantages for People and Business

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Artificial intelligence (AI) Benefits and Advantages for People and Business

Artificial intelligence (AI) Benefits and Advantages for People and Business – What are all the benefits of AI? Well, it turns out that there’s a lot of benefits that many people may not be aware of, and so, if you want to learn more, stick around, ’cause that’s what we’re going to talk about next. Well, the first is that people are starting to realize that historical precedent, simple analytics and gut feel is no longer really getting the job done.

In today’s data age, we need to better understand how to extract meaningful information and insights from data as quickly as possible, and so, as a result, you know, companies realize that, and they’re starting to realize that data is a core advantage potentially, and are trying to find ways to become more data driven or what they call data informed, and so, one of the benefits of AI is taking data and using it in much more sophisticated ways than was traditionally done before.

Another benefit of AI is the outcomes that you can get from it are impossible to get any other way. So what I mean by that is, you know, think of more traditional analytics. You have things like business intelligence, data analysis, you know, a lot of data visualization, metrics, charts, graphs and so on.

Those things are super helpful. There’s definitely a place for them, and in fact, I think AI and advanced analytics techniques in general are very complimentary to traditional analytics and both should be used in tandem. But that being said, AI and machine learning is able to learn these very complex and deep underlying relationships and correlations and patterns across many different data sets all at once, and, you know, sometimes potentially thousands or tens of thousands of different data features.

Whereas, you know, think about dashboards, even if you created 3000 dashboards, each one with 1000 different charts and graphs, no human could actually really analyze all that at once to try and understand all those relationships. Not only that, when you have humans as analysts, you know, people interpret data differently. You know, people interpret metrics and graphs and charts differently. AI, one of the really great benefits of it is it allows you to quantify things and make things very objective in a very sort of deep and complex way in terms of insights and actionable insights and being able to, you know, support decision making in ways that you just can’t do any other way.

Now, another benefit is actually capturing the title of my book, the title, the full title of my book is “AI for People and Business, “A Framework for Better Human Experiences “and Business Success.” And so, in this case, the benefit I’m talking about is the better human experiences and business success part. Now the business success part’s a little bit more obvious probably where, okay, you can use AI to, you know, optimize top level business goals like increase revenue or decrease costs or optimize something, right? Or increase efficiency.

But on the better human experiences side, that’s a really interesting topic, and in fact, I break that down into many different categories of how AI is directly impacting and influencing human experiences across the board, whether it’s through financial planning and retirement planning or through health, you know, detecting diseases earlier, resulting in earlier treatment and better health outcomes to things like, you know, making people’s jobs more enjoyable and more productive at work.

Something we’ll talk about in a minute a bit more and so on, but there’s many benefits that AI is able to have not only for businesses, but also for people as well. Another one is that AI allows you to be proactive and not reactive. So you may have heard these terms like descriptive, predictive and prescriptive analytics. Descriptive being sort of what did happen, looking backwards at your data. Again, looking at the metrics, the charts, the graphs, historical data, trying to understand it.

How did things change after you made a decision and so on and so forth. But it’s always rearward facing, and then with predictive analytics, you start to predict things and you say, okay, well, if I pull these levers and I tweak these knobs and things, make these decisions, what’s going to be the outcome of that? And that allows you maybe to plan better or schedule or invest in different ways within your company and so on, but then prescriptive analytics is sort of taking that even a step further and saying, okay, not only can I predict things, but now I can even optimize for a certain outcome that I want.

So I know exactly what settings or what decisions to make to get the exact optimal outcome or to make recommendations automatically like I should do this or I should decide that or I should take this action automatically, and so, in this case, being proactive rather than reactive is quite a bit more powerful because it allows you to drive your own results, right? You know, and again, in the descriptive sense, looking backwards, more that historical way of doing things, you know, you have like a lag to understand the results of the decisions that you make from those actionable insights.

So, you know, you might look at your historical data and say, oh, well, we need to do more promotions around this through our marketing program. So then you make that decision. You do that thing. Now you have to wait another month, two months, three months, and then look back again and say, did that help? Okay, try another thing. Now wait another two, three months. With AI, you kind of just make the changes that get you the results you want, and that’s a very big benefit.

Another one is sort of what I call deeper, actionable insights, and I just pretty much described that. The reason I use deeper is ’cause, again, it’s, you know, everybody’s looking for actionable insights. Everyone’s looking to, you know, use, more and more anyway, use data to help drive decision making and so on. But again, it’s because AI allows you to really understand what’s going on in your data in ways that humans just can’t on their own like I said. It gives you this idea of deeper, actionable insights. Insights that you can’t get any other way.

So in some sense, it’s the, it’s the same thing I was saying before, but I like to point out that term, that concept of deeper, actionable insights, and one of the results of these deeper, actionable insights is that you’re able to make better, faster and more efficient decisions, but also see the results of those decisions quicker as well. Another benefit of AI is this idea of human augmented intelligence. So it’s this idea of AI that’s, you know, it’s not just automating away people’s jobs completely, but rather augmenting people’s jobs.

Basically, you know, we all do a lot of rote, repetitive tasks everyday, some administrative, some just like, you know, whatever they are, but they’re just kind of, you know, sometimes annoying. They’re just things we have to do and there are things that are really well suited to machines to do, which, you know, if we can automate those things, but not the entire job, ’cause at the end of the day as well, AI is really not able to do many things that humans are able to do, especially in areas like be creative or think critically or, you know, reason through things, especially outside of the area that they were trained, like these AI models, for example.

So if we can automate the sort of rote, you know, tedious, repetitive tasks, what that then allows us to do is really focus on the job that we truly were hired for, you know, the value, creating value, being more productive, being more creative, thinking more critically, solving more problems, and overall, enjoy our jobs more because we get to do the things we really want to do, and so, it’s sort of a win-win because not only can employees be happier overall in their job, but it’s beneficial to companies if their employees are happy as well, and you get just the best sort of, the ideal state is you get the best outcome overall from human augmented intelligence potentially.

Now some of the examples of this in the real world, not long ago, I read about, you know, people looking at ICU’s, intensive critical care units in hospitals where, you know, doctors and nurses are understaffed and they’re overwhelmed, and especially when people are on life support, there are many different machines that they’re sort of plugged into or they’re helping support them that have all these different settings and everything, and need to be monitored constantly.

By automating using AI, though, the monitoring and the adjustments and tweaking of those settings, that then frees up the doctors and nurses to focus on the patients that need their care the most and actually be able to give proper and effective care to as many patients as possible while also, you know, enjoying their job more because they’re able to do what they’re there to do as opposed to some of these more sort of rote, tedious tasks that really don’t leverage their true value, and finally, AI allows you to convert the subjective into objective.

So what do I mean by that? Well, think like you’re at a company, you’re in the marketing department, and you know, you sell products and people can write reviews about the products online somewhere, think like yelp, and also, people are out there, you know, saying things on different social media platforms like Twitter, and so, you kind of monitor that to see, you know, what do people think about your brand and your products?

Now just reading people’s comments and opinions and things like that is very, it can be very subjective, and especially if you have thousands and thousands and thousands of these to deal with, you know, you probably can’t remember all of them all at once or try and find some underlying pattern or series of patterns that are surfacing in these different comments and reviews and try and make sense of it in such a way that you can, you know, take very concrete actions or make decisions accordingly.

With AI, and particularly, techniques like natural language processing, you’re able to turn this subjective data, like reviews and comments, into objective analytics, things like sentiment analysis, you know, is the overall sentiment from your customers positive, neutral, negative? What about word frequencies? Are certain words popping up, you know, 100 times more than other words? What are the relative frequencies? So you know how to prioritize and focus on the different things that matter most about your brand and your products and make decisions accordingly to address those things.

Also, what, what do people like? What do they not like specifically? What are these themes that keep popping up? And you could really quantify these things using these AI and natural language techniques such that not only do you get this objective analytical sense of everything, but as you tweak things and you, maybe you change your marketing strategy or you start improving your products based on this quantified feedback that you’re getting, you can actually track how these sort of analytics like objective metrics and things that you’re getting through natural language processing change over time, so you have direct, objective, quantifiable, numeric comparisons, as opposed to, you know, just some people reading comments and going, well, I don’t know, I mean, it seems like people are a little happier now, but you know, let’s just see what happens and so on.

So a huge benefit for sure, and I would keep your eye on that ’cause there’s a lot more to come in the natural processing or in the natural language world, in general. Okay, well, hopefully it’s become clear that there are many benefits of AI, some more obvious, some less obvious, and hopefully, today, you got a better sense of what some of those benefits are.


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