Business Technology

Artificial Intelligence and Machine Learning. What Are Some of Their Benefits for Your Company?

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Artificial Intelligence (AI) and Machine Learning (ML) are booming technologies that constantly make media headlines with their latest working features. Don’t worry, the chances that machines take over human jobs completely are still pretty low. However, the need for the right technical partners that help businesses adapt to the new environment and embrace digital transformation has surged ever since the pandemic outbreak last year. 

Working in a bespoke software development company has taught me the importance of incorporating the latest technologies not only because they are trending but rather as a way to secure a competitive advantage. The practical, real-life applications of AI and ML in business are numerous, and many more are bound to be realised in the near future. In this article, we explore the main benefits of AI and ML for your business today. 

What’s the Main Difference Between AI and ML?

Machine Learning is a subsector of AI, and AI itself is a branch of computer science. It is generally concerned with the automation of human and intelligent behaviour. In addition to machine learning, for example, knowledge-based systems, neural networks and robotics also belong to the broad field of artificial intelligence.

Similar to human learning, the computer can also learn to identify and differentiate between objects. For this purpose, programmers train the self-learning software with data and teach it which object is, for example, “a dog” and which is “not a dog”. The ML algorithm continuously receives positive or negative feedback in the form of data and uses it to adapt and optimise the model. This process continues until the software can clearly distinguish dogs from non-dogs.

What Happens in the Business World?

Besides imminent tech advancements, one of the leading reasons why AI and ML solutions invade the business landscape is that even simple autonomous systems can and thus exponentially reduce operational costs. Moreover, the immense potential of AI to leverage Big Data and handle massive amounts of data is yet to unfold fully. Currently, the combination of the two provides businesses with process optimisations, in-depth data analysis and enhanced customer service.

On a more fundamental level, AI-powered chatbots and personal assistants let you process business inquiries coming from prospective customers, answer FAQs, schedule a demo and book a meeting with an actual human expert. Though it can automate all kinds of manual tasks, the true power of AI lies in handling complex processes. Thus, another AI use case is identifying process bottlenecks and providing recommendations so that company executives can make an informed data-driven decision. Industries as healthcare, pharma, banking or transportation already benefit from AI’s powerful capabilities. 

AI-driven Data Analytics for SMEs

Small and medium-sized enterprises (SMEs) make up 99% of all world companies. They want to reduce time and costs, improve relationships with their customers or take part in developing pioneering innovations. Data analytics are becoming more and more important, and coupled with AI, such methods based on ML are able to assembly robust Business Intelligence (BI) from current and previous data and optimise business performance.

In this way, decision-makers know about specific trends in customer behaviour or the future condition of their production machines – and can thus react early and proactively respond to changes. In the future, there will also be log data from IT systems, sensor data from the Internet of Things and content from social networks. 

Enhanced Trend Predictions Using AI 

We see how in recent years, entirely new markets emerge thanks to technological advances. Just a decade ago, there were no FinTech, HealthTech or InsurTech industries, and now these sectors are booming. With personalised user experience, highly relevant predictions and high-speed data processing (e.g. financial transactions), today’s end-users really have it easier compared to previous generations.

So how is this all possible, and how can companies keep up with the latest trend in our fast-paced world? It all boils down to the way businesses tackle one of the most complex challenges of the digital era – making sense of all the available data. While having enough relevant data is a challenge on its own, knowing what to do with it so you can unlock its potential is another story. That’s why trend predictions with AI can boost up competitiveness, accelerate time-to-market and secure business continuity, which is more needed than ever. 

Next-Level Marketing Solutions

Currently, a major struggle for businesses is to stand out from the crowd. It gets increasingly difficult to be spotted in an ever-increasing online business arena without having the right digital tools in your arsenal. For example, AI and Deep Learning can be integrated into a CRM system and help analyse incoming messages so that it can produce smart answers and forward them to human experts, reducing processing time and increasing customer satisfaction and thus increasing credibility.

Another possible application of AI and ML in the marketing context are software tools used for emotion analytics (EA). EA software solutions track real-time biometric data from users and optimise app and business performance. By using custom AI-powered software, companies can obtain vital information about the user’s experience while browsing their web or mobile application, detect mood patterns, attitudes about certain pages and identify which modules receive the most attention. Ultimately, businesses can then tailor their data-driven success strategy according to customer demands. 

Beyond Task Automation: Tackling Interdisciplinary Challenges 

We all know that today’s business environment is dynamic and unpredictable. For instance, as soon as pharma companies were ready with vaccine development, new problems emerged: distribution and logistics. Pharma and transportation had to unite forces and face the challenge together. In fact, our future is likely to hold many more interdisciplinary opportunities to solve major problems and which technologies will help us tackle them? You guessed it right – AI and ML technologies.  

When you think about it, hardly any modern business operates without some kind of digital operations. However, as companies become increasingly reliant on bespoke software development, another prospective issue arises – making the most of interdisciplinary fields and merging assets to remain relevant. Some promising areas will be exploring how to fully utilise quantum computing to collaborate with AI algorithms and gaining multidisciplinary insights to develop more advanced software in key areas such as digital security, robotics, genetics and even eco-agriculture.

Author Biography Aleksandrina Vasileva 

Aleksandrina is a Content Creator at Dreamix, a custom software development company, and is keen оn innovative technological solutions with a positive impact on our world. Her teaching background, mixed with interests in psychology, drives her to share knowledge. She is an avid reader and an enthusiastic blogger, always looking for the next inspiration.