Humanity is peeking through the doorway that will lead us into a technological revolution, perhaps only comparable to the disruptive emergence of the Internet. Of course, we’re talking about Artificial Intelligence (AI).

And although AI has existed for a long time, its current level of development is having an unprecedented impact on product creation and the way we interact with those products, especially in the realm of software.

Several of the most respected contemporary thinkers indicate that soon AI will bring profound changes to the world of work and the inevitable modification of all business models. In the face of this, thousands of companies will disappear for failing to adapt, while others will grow exponentially by evolving into this new reality.

In this article, we explore how AI is changing businesses and revolutionizing various industries by enabling the creation of smarter products that are more aligned with user needs.

How AI is revolutionizing various industries?

Advanced personalization

One of the ways AI is causing disruption is through advanced personalization.

AI-based products collect data of all kinds through user interactions. They then process, correlate, and analyze this data, which enables them to offer tailored recommendations and suggestions to the user.

For example, Netflix’s content recommendation system uses AI algorithms to offer users movies, series, documentaries, and more that are customized to their individual tastes and preferences.

To achieve this, the platform stores information about the viewer’s preferred genres, the time they spend on Netflix, when they log in, which days of the week, from which part of the world they access, on which device, and a host of different factors.

But over time, Netflix realized that it wasn’t enough to just show suggested titles; it also needed to provide attractive video thumbnails to pique the viewer’s interest in the content that AI offers them.

Let’s go even further. If you log into Netflix using a friend’s account, you’ll notice that the thumbnails for the same movies or series you watch can be completely different from the thumbnails Netflix shows you. This is possible thanks to two of Netflix’s AI algorithms: Aesthetic Visual Analysis and Contextual Bandits.

These algorithms take each title from Netflix’s catalog, detect which frames would be most attractive for a thumbnail (considering that an hour-long movie has approximately 86,400 frames), generate different thumbnails for each title, and determine which thumbnail is most likely to keep the user engaged with the platform.

All of this is done with the purpose of creating a completely personalized user experience, increasing customer satisfaction, and, of course, boosting the company’s revenues.

Continuous learning

AI also enables products to continuously learn from users over time. This means that a product can come to understand a user’s current preferences and needs, but more importantly, it can anticipate their future needs.

An example of this is the evolution of virtual assistants like Amazon’s Alexa. In its early days, back in 2014, its capabilities were limited to playing music through voice commands. However, it quickly evolved to become a smart home controller, allowing users to manage thermostats, light bulbs, vacuums, and more.

The next significant step was the desire to understand the user. So, in 2017, Alexa introduced the functionality that allowed users to request it to make purchases on their behalf, searching through Amazon’s vast product catalog. Over time, a series of AI capabilities were added: a road assistant for cars, a fashion assistant to recommend outfits, a veterinary assistant, and so on, culminating in Astro, Amazon’s domestic robot that integrates the capabilities of Alexa with advanced hardware and software, computer vision, and cutting-edge AI.

Astro is capable of learning and understanding the home environment, reacting to its surroundings, and proactively anticipating the user’s needs without waiting for requests. It can recognize family members, so you could ask it to deliver pills to your grandparent. It can also autonomously alert the police if it detects an intruder at home or simulate a dog’s barking when it detects unusual movements outside during unusual hours.

If you’ve just left the house, you can ask it to check if you left the iron plugged in or the stove turned on. Then the next time Astro detects that you’re about to leave, on its own initiative, it will visit the ironing room and, if necessary, alert you that you’re leaving the iron plugged in again.

Advanced decision-making

Smart products can make real-time decisions using complex data, as seen in AI-based inventory management systems capable of predicting product demand and placing orders automatically, thus enhancing the operational efficiency of companies, while significantly reducing costs.

An example of this is the AI-driven automatic replenishment solution used by Alibaba Group, the Asian giant that operates China’s largest e-commerce platform. Considering that this platform generates billions of dollars in annual revenue, it’s easy to see how critical and complex it is to manage the inventory that moves through it.

Alibaba Group has a team of expert buyers who make replenishment decisions, and although AI algorithms generate recommendations, these individuals can choose to ignore them and make their own decisions.

However, the company has gradually been implementing a new AI-based replenishment system where algorithmic recommendations are final. The initial strategy was to select a group of slow-moving consumer products and entrust replenishment to AI, while decision-making for the remaining universe of SKUs would remain in the hands of human experts, including fast-moving consumer products—the e-commerce honey.

Because the results of the initial strategy proved successful, Alibaba Group decided to expand the number of products to be replenished in line with AI recommendations. In a short time, the algorithms demonstrated their ability to outperform human experts in reducing out-of-stock rates and maintaining inventory at optimal levels.

Now, more than half of Alibaba Group’s catalog products are automatically replenished based on AI decision-making, including all slow-moving consumer products. Consequently, the number of products managed by human expert buyers has decreased drastically, allowing them to focus on what matters most—fast-moving consumer products.

Regarding economic benefit, it’s estimated that for products with a daily sales volume of USD $10 million, AI algorithms can increase annual profits by USD $30.9 million. That’s intelligent buying!

Other examples of AI applicability

• Predictive Analysis: AI is also used for forecasting trends and future outcomes by analyzing historical data. In the field of healthcare, for example, AI algorithms can assist in predicting diseases or identifying potential risks by analyzing patient data.
• Productivity Improvement: Thanks to AI, the performance and efficiency of production processes can be enhanced. In the manufacturing industry, AI-based quality control systems can identify defective products in real time, reducing waste and improving quality.
• Visual Quality: Through AI, it’s possible to enhance the visual quality of products such as video games or image editors by automatically correcting imperfections or applying special effects. AI is also being leveraged to deliver more immersive visual experiences with optimized image rendering and frame prediction.
• Lifestyle: AI can even be implemented in basic aspects of everyday life. An example is meal planning applications that use AI to recommend recipes based on the ingredients available in a family’s pantry, making it easier to plan healthy and economically sustainable menus.

Is AI accessible to companies of all sizes?

The good news is that AI is no longer a technology reserved for large corporations. With the proliferation of tools and platforms at increasingly affordable prices, companies of all sizes can harness the benefits of Artificial Intelligence. This unquestionably democratizes innovation and allows any organization to be capable of developing smarter and more competitive products.

However, when companies embark on the initial paths of AI adoption, they often encounter an initial complexity that can be bewildering, partly due to terminology that may sound like science fiction. This can lead smaller organizations to believe that implementing AI solutions is beyond their reach. Nothing could be further from the truth.

Because of their smaller size, relative novelty, and lack of ties to large systems, small and medium enterprises can quickly leap into AI-based solutions and transform their commercial management, sales, marketing, logistics, product development, and more in the short term.

In summary

While AI is not a new field, it’s playing a bigger role than ever in the creation of smarter products across a wide range of industries. From advanced personalization to key decision-making, continuous learning, productivity improvement, and more, AI is transforming the way we interact with technology and with each other, promising to enhance our quality of life in the process.

Fortunately, AI is not exclusive and can be adopted by organizations and businesses of all types and sizes. A multitude of tools and technological platforms have enabled better access to AI, ensuring that its impact will continue to grow in the future. Those who fail to adapt will have a difficult time competing with those who do.

Finally, it is important to reflect on the fact that a product’s intelligence is related to the context of its use and the technological development level of its time. In other words, in 1988, the state of the art in AI was the Deep Thought system for playing chess at Carnegie Mellon University. Over 30 years later, this milestone may seem anecdotal and playful to us.

Now, let’s imagine what future humans might think in three decades about our current entertainment recommendation algorithms, predictive analysis, and virtual assistants. But more excitingly, what will they consider a smart product?

As a technology company, Capmation maintains an internal team of AI specialists who continuously engage in training, researching, and evaluating AI technologies, all with the aim of bringing this exciting technology to our clients.

Appendix

What is Artificial Intelligence?

To answer this question, it is valid to first question, “What is intelligence?”

Without delving into philosophical, theological, scientific, and other conceptions, we can agree that intelligence, in general terms, is the ability to acquire knowledge, understand, reason, solve problems, and adapt to the environment.

Biological intelligence has been extensively documented in orangutans, dogs, dolphins, octopuses and crows, among other species. In addition, recent studies claim that plants possess intelligence, even at higher levels than certain animals. Of course, within the realm of biological intelligence, human intelligence stands out prominently.

As the 20th century progressed, stimulated by technological advances, humans began to seek ways to replicate human intelligence. This gave rise to Artificial Intelligence, as an interdisciplinary field of study that combines computer science, mathematics, psychology, and philosophy, with the purpose of creating technologies capable of performing tasks that require human intelligence.

Some tools based in AI were employed for the creation of this article. However, the primary content was developed using the Capmation team’s knowledge and expertise.

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