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The evolution of machine intelligence in business: catch it if you can

Machine intelligence is a hot topic not only for businesses but also in our daily lives. If you find it murky and unreal, this article will change your mind.

Machine intelligence and artificial intelligence are no longer a science fiction creation. They have evolved in a way that they are surrounding us and affecting our routine in unprecedent ways. In this article we will explore the impact they have on businesses and how they are shaping the future.

What is machine intelligence?

To understand what machine intelligence (MI) means, we must look at two others terms that connect with each other: artificial intelligence (AI) and machine learning (ML).

Artificial intelligence can be simply described as systems that imitate human cognitive processes or execute tasks done by humans.

Machine learning is the ability of computer systems to learn from inputs instead of being exclusively programmed for certain tasks.

According to an article published by Forbes, machine intelligence is “what’s created when machines are programmed with some (but not all) aspects of human intelligence, including learning, problem-solving, and prioritization. With these (limited) abilities, a machine can tackle a complex set of problems”. So, machine intelligence combines machine learning and artificial intelligence, acting like an upgrade.

Introduction in business

Despite being present in many (if not most) businesses, there are companies that are leading the way while others follow them. McKinsey published an article that analyses the evolution of MI in business operations. It divides organizations into four groups (leaders, planners, executors, and emerging companies) according to the stage they were with the application of machine intelligence. If we focus on leaders, they are the ones who invest, study, and use more sophisticated approaches, as well as train employees to use the MI and AI tools.

According to it, the journey from dashboards to MI depends on multiple factors, but the first is “reliable and available data”. By monitoring and analyzing data through machine learning, organizations can predict failures and adjust small parameters that increase overall performance.

Nowadays, investing in MI is easier through the acquisition from direct suppliers in order to apply it to the necessities of the corporation. Another way is through partnerships, which are growing in number and importance. Thanks to them, it is possible to delegate the investigation to partners, reducing costs and the time needed to solve problems.

However, to succeed there are four steps that McKinsey mentioned to be crucial:

Decisions rely now on artificial intelligence, allowing people to focus more on the creative side of businesses.

Machine intelligence: what can it do for you

When in place, MI demands a tremendous effort to monitor all aspects of the programs. To achieve better results, entities must build top-performing teams that accompany every stage. However, the advantages of these processes are worth the effort. Let’s explore some of them:

  • Forecasting and predictive analyses: one of the advantages of MI is the ability to forecast production failures, shortages, or consumer demands and needs. When doing so, companies can easily adapt and ensure good results in production, delivery, and customer service. McDonald’s, for example, used machine intelligence to analyze how clients reacted to promotions and what would be the affluence to their restaurants.
  • Maintenance and manufacturing: when done wrong, this can cost a lot of money. That is when AI and MI come in place: they alert before problems arrive; they make adjustments in real-time; they improve energy efficiency and overall performance. The final result is more automated processes, better products, and a reduction in costs.
  • Customer service: improving the response time to customers’ questions is definitely a plus! Chatbots are the perfect ally to avoid queues and interminable phone calls. Another example is engagement with people. Netflix, for instance, provides recommendations based on preferences. Those recommendations make customers feel like they are unique and increase the feeling of “belonging”. Remember: pleasing the client is always a good idea.
  • Marketing and content creation: algorithms became the unsung heroes. They suggest keywords and, in some cases, they are able to produce blog posts according to them. Marketing campaigns also benefit, since AI and MI allow better customer segmentation, optimization, and interactions.
  • Sales: integrating AI into a CRM is totally worth it. Salespeople can access information on preferences and customize products according to them. As a result, clients will engage with the brand quicker and increase the chances for conversion.

As products and services become more efficient thanks to AI and MI, many industries are increasing their competitive advantages. Decisions rely now on artificial intelligence, allowing people to focus more on the creative side of businesses.

Examples of industries applying AI and MI

With all the benefits that artificial intelligence and machine intelligence bring, it is no surprise that renowned companies are putting them to their best use.

The examples are numerous and are everywhere. In financial services, for instance, artificial intelligence can detect fraud and generate algorithmic trading. Similarly, insurance companies evaluate risks and claims by looking at the numbers and possible scenarios generated by programs. Another close example is healthcare and medicine, which predicted and evaluated the proliferation of COVID-19 using AI systems. Aviation is no exception to this rule! Artificial intelligence acknowledges seasonal tourism and facilitates planning traffic and routes.

Among famous companies is Uber, which started using AI to predict demand and adjust the time of arrival. In doing so, the efficiency increases: each driver connects with a passenger, and they can even communicate using an automatic response.

Magma International, a mobility-technology company, implemented machine learning to analyze production. As data were collected and processed, they were able to understand that one single variable would reduce by 80% the need for reworks or leftovers.

A major disruption has been natural language processing. It focuses on interactions between computers and human language. The aim is to understand and analyze the information in documents and conversations, giving business important feedback about products, online comments, customer’s wishes, and others.

The boundaries of machine intelligence remain unknown.

Machine Intelligence: what’s next

The boundaries of machine intelligence remain unknown. Research and development are always in place with the view to do better than the day before. Of course, we cannot ignore the challenges, such as data collection, security, and privacy. Acquiring the correct amount of information and securing it is a complex task that demands highly trained workers.

On the other hand, there is a concern that many jobs will be extinguished or replaced by machines. So far, this was not the case, as companies are needing more qualified workers to perform well with AI demands. But what will come next remains to be seen.

For now, it is undeniable that structured organizations with defined digital strategies, artificial intelligence, and machine intelligence are breaking the ground and shaping the way business is done. 

Graduated in Languages and International Relations, Jéssica loves travelling and meeting new people. She has been working as a sales representative for more than seven years, and recently found another passion: Digital Marketing. She is constantly challenging herself and trying to improve her skills, without forgetting that every day is a new opportunity to create fantastic memories.