These days, you no longer have to head to the movie theater or turn on your television set to experience a world where artificial intelligence is everywhere. That world is officially here and now on so many levels.
AI algorithms rule your favorite social media platforms, while numerous AI-powered programs make your smartphone as helpful and indispensable as it is. Popular AI programs like ChatGPT and Midjourney can even generate surprisingly human graphics, written content, and more.
But the more popular AI-powered technology becomes, the more important it is to know how to use it efficiently and responsibly. Many people still have questions about how it works and whether it can really be applied in different business segments.
Let’s go over a few of the key things to know.
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What Is Artificial Intelligence?
The term Artificial Intelligence is not a new concept.
In 1956, Professor John McCarthy coined it to refer to the ability of machines to solve problems that, until then, could only be solved by humans.
The concept of AI remains the same: machines thinking like humans; developing the ability to learn, reason, perceive, deliberate, and make logical decisions based on facts.
Another important aspect of AI is that, because of its ability to learn, it needs to be constantly fed to continue to evolve, like a person.
As complex as this process is, it is only possible with simple computing processes, such as:
- Data Modeling
Frameworks to intelligently process, categorize and analyze data.
- Big Data
Making large amounts of data available to be processed.
- Processing Power
The operational and logistical ability to process information quickly and efficiently.
Despite this brief explanation, to understand how AI works, you need to know that a combination of technologies makes it possible.
Technologies Enabling AI Functionality
AI is composed of code and data, with the former responsible for reading and interpreting the latter.
However, AI is more than just data analysis.
To fulfill a complex plethora of commands that can mimic humans, it relies on several technologies.
Machine Learning
The first pillar of AI is Machine Learning.
This is where computers evolve and become capable of learning. With this technology, logical processing of data and identification of patterns that generate intelligence take place.
Without Machine Learning, what we understand as AI would not materialize.
Today, for example, the technology is used extensively by Amazon to make more personalized and relevant recommendations to customers.
The system works as follows: the machine monitors all customer actions on a website and identifies patterns. Actions such as when customers who have seen product X also show interest in Y are great examples.
So, when a user does the first search, the system recommends the other product because it identifies a relationship between the searches.
In Machine Learning, these patterns are identified in infinite webs so that there are thousands of points of intersection consisting of connections between information, enabling intelligence on a large scale.
Deep Learning
Another essential concept for the achievement of today’s AI is Deep Learning.
This technology is a deeper version of Machine Learning, making it more intelligent and complex.
Deep Learning uses more sophisticated tools, making the results more accurate.
Going back to the Amazon example, the technology identifies exceptions so as not to make unqualified suggestions.
Imagine this: if out of 1000 customers searching for “smart TVs“, 800 continue their search with “home theater“, the software understands this is a relevant recommendation.
With Machine Learning, if five users start a search for “shoes” after searching for “smartTV“, the system could assume it is a valid recommendation.
Systems that rely on Deep Learning, however, know that these are unrelated products, preventing exceptions from becoming rules when it comes to user behavior.
Deep Learning uses more complex networks to conclude that this example is not a causal search. Although there is an occurrence, it is not a relevant result for the user.
In this sense, Deep Learning is able to understand human thoughts in more detail than Machine Learning.
Natural Language Processing (NLP)
The last pillar of AI is Natural Language Processing (NLP).
This is responsible for polishing results, making them more natural and human-like.
For example, several e-commerce businesses currently use chatbots for customer service. However, the quality of this technology lies in the presence of NLP.
When it is not incorporated into the solution, the bot becomes artificial. It is unable to improve its language to make it more similar to the one used by customers.
The over-perfection of the language and the inability to incorporate more informal elements is what makes the bot artificial, regardless of its ability to actually assist the customer.
What Are the Benefits of AI?
AI has enabled direct and indirect benefits for businesses, being incorporated into operational stages and strategies due to its many possible applications.
Let’s see four advantages offered by this technology:
1. Automation
AI allows the automation of voluminous computational processes, avoiding the need for people to perform tasks or even identify patterns.
However, this requires trained professionals to configure the system.
The resource is also used in robotic automation and, in these cases, replaces operational tasks, such as tightening a screw with precision.
In both situations, the technology optimizes processes and improves business performance.
2. Predictability
Among the many possible applications of AI are market predictions, behaviors, and processes due to Big Data analysis.
This process identifies patterns and establishes predictions from past events.
Through predictive analytics using Machine Learning and AI, it is possible to consider unlimited data and scenarios to identify the most likely events, contributing to more effective and strategic decision-making.
3. Deeper Data Analysis
Big Data has been enabling systematic data analysis for a few years.
However, AI has deepened this interpretive capacity, generating more intelligence from the analysis of information.
Thus, even a company whose competitors use similar techniques can differentiate itself enormously if it has a good data set and applies AI to identify patterns and predictions.
This strategy enables the extraction of more complex and valuable information from the data.
4. Constant Improvement
Artificial Intelligence enables constant evolution in regard to the use of data. As it deals with multi-layered neural networks, it is able to more complex and effective interpretive structures.
To adopt Deep Learning, a company needs Big Data so that the model can learn from this information.
Also, the more data fed into the model, the more effective it becomes.
AI in Practice: Applications in Various Industries
Artificial Intelligence is already used in almost all business segments due to its customization flexibility.
Possible applications of this technology include strategic development, Digital Marketing, customer relationship and new business models.
Curious about how AI is already impacting digital marketing? Learn more about it in this free interactive e-book.
E-commerce
Online stores use AI mainly to provide a better experience to their consumers.
Among the uses of AI in this field, it is possible to mention:
- Identifying consumer preferences according to browsing and consumption habits to provide a better shopping experience.
- Making recommendations to customers based on the behavior of others.
- Performing integrated customer services, such as using chatbots and CRM.
Through these AI applications, e-commerce becomes more efficient in customer relationships.
Giants such as Amazon are innovating in the use of technologies and gaining competitive differentials. Still, specialized tools and partners increasingly enable these resources to be adopted by small and medium retailers.
Automobile
Some applications of AI in automobiles are still in the testing phase, such as Uber’s autonomous car.
But companies like Google and Tesla are already showing solid results by using this technology.
In this context, AI is utilized to enable the car to carry out several commands on its own, such as parking, monitoring blind spots, and detecting collisions.
The goal is for the technology to increase traffic safety and to be affordable in the long term.
Entertainment
AI has even been used to enable new business models in the entertainment segment, such as Netflix.
The company uses the technology to make suggestions to users and improve recommendations, which is a core aspect of the experience on the platform.
In addition, the use also extends to the gaming segment, in which characters are endowed with personality, making interaction more complex.
Healthcare
Several applications of Artificial Intelligence have impacted the medical field to improve healthcare services.
Commonly, AI is used to read important exams, such as CT scans.
By training the technology, it can identify changes as accurately or more accurately than doctors.
Besides that, some applications in healthcare are also concerned with analyzing patient data to identify the early stages of serious diseases such as Parkinson’s and Alzheimer’s.
Manufacturing
One of the first segments to make use of AI was manufacturing.
With robotic automation, it became possible to assemble and pack parts without human interference, ensuring the quality of the process and, at the same time, production optimization.
The expectation is that the technology will contribute to operational processes in the industry and be increasingly determinant in the creation and planning stages, providing production and market intelligence.
Ethical Considerations and Challenges
At this point, AI is no longer just something people are playing with for fun and novelty. An incredible 35 percent of companies have already integrated various AI tools into their workflows, while 42 percent of those who haven’t yet say they plan to try it in the future.
However, while artificial intelligence can be an efficient, exciting way to optimize many tasks, there are important ethical concerns to consider before diving right in. Here are some examples.
Potential copyright issues
Popular, widely used tools like Midjourney, GPT-3, and ChatGPT owe their magical generative abilities to huge information datasets. However, much of the material included in such training sets is copyrighted, which naturally brings up certain legal concerns.
Since generative AI and similar technologies are still so new, there’s still a lot of debate as to whether the use of copyrighted material constitutes fair use or not. There’s also always the chance a program could spit out results that mirror an existing work closely enough to cause legal issues, so discretion is essential.
Privacy concerns
It’s technically possible for an AI program to accidentally violate someone’s copyright by generating content that’s too similar to someone else’s original work. The same can happen with sensitive or unauthorized information.
Training datasets require absolutely massive amounts of information. Some of that may be private data that could identify individuals, companies, and other entities. Publishing such content could also open a company up to liability and other legal issues.
Bias-related issues
It’s human nature to be biased and opinionated, so it should make sense that most human-created content takes sides. But issues can arise when AI programs digest biased content and then reproduce those same biases when generating new content.
This can happen with image generators like Midjourney, Stable Diffusion, or DALL-E, as well. Many prompts unintentionally produce content that reinforces hurtful stereotypes about various types of people.
Job displacement
One of the biggest ethical concerns attached to using AI for business purposes is potential job displacement. Every time a marketer or creative director decides to trust their content marketing efforts entirely to ChatGPT, Midjourney, or a similar program, a team of talented content creators loses a gig.
Many people are also justifiably concerned that the widespread use of AI will eventually devalue human originality, creativity, and lived experience.
Recent Developments and Future Trends
So, how exactly are today’s brands and marketing teams using AI for marketing, content creation, SEO, and more? Here’s a look at some of today’s up-and-coming trends, as well as those just around the corner in 2023 and beyond.
Increased use of generative AI
Chances are you know at least a few people who have already leveraged the power of an Ai-powered tool to create new, marketable goods. Folks are out there using such programs to write books, generate fine art prints, create original products, and more.
You’ll see this happening a lot more throughout the rest of 2023 and in the years to come. You’ll also see people, brands, and companies using AI to write code for various purposes, brainstorm new inventions, and more.
Voice-driven AI advancements
Saying that voice-powered technology is red hot right now is really quite an understatement. And it’s only going to get hotter moving forward. Presently, experts predict that speech recognition will evolve into a $49.7 billion-dollar industry by 2029, and AI tech will naturally be a big part of that.
So, you will see a lot more of the helpful tech you already recognize (like voice-powered smart speakers). In fact, voice-focused artificial intelligence is working its way into multiple business processes across the board, including AI-powered marketing initiatives.
AI security options
Data protection, privacy, and security are huge deals for digital-age businesses, and that’s only going to become more the case in the future. However, cybercriminals and identity thieves are often able to hack their way through many of the security measures businesses are already using.
So, watch for formidable AI cybersecurity options to explode onto the scene, either in 2023 or soon after. They’ll be better able to protect against both traditional digital attacks and those made possible by thieves who exploit AI tech themselves.
Ethical AI options
The ethical concerns attached to the training and use of today’s popular AI options desperately need solutions, especially if the industry is going to continue to grow. So, those who use AI for SEO, marketing, content marketing, and other purposes should prepare for the tech to evolve accordingly.
Future versions of your favorite AI programs will not only take greater care to use only authorized data sources for training purposes, but offer users more transparency as to where the data they use does come from.
Wrap-Up: Artificial Intelligence Will Be Everywhere
At this point, it’s clear to everyone that artificial intelligence is here to stay, and that’s a good thing. AI-powered solutions can help businesses and individuals of all types streamline their workflows, turbo-charge their creativity, better understand modern audiences, and more.
This comprehensive technology with such diverse applications that it has become present in the day-to-day of all people connected to the internet. Whether by accessing a social network, a news website, or even just checking their email, people are already in constant contact with it.
However, as incredible as AI is, it still requires human creativity and innovation to be genuinely useful. Understanding how it works and its most frequent uses offers insights and intelligence for greater resource distribution.
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