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Integrating Artificial Intelligence into Businesses in 2020


To the average person, the concept of artificial intelligence may bring to mind sentient robots and the like, but the reality of AI is almost mundane. Used primarily in automation and data analytics applications, AI is a growing part of modern business models. But we’ve come such a long way in recent years, and businesses across a wide array of industries are constantly finding new ways to utilize AI technology.
In 2020 and beyond, companies are expected to put an even greater emphasis on the benefits of AI. Of course, AI bots have become the norm in the realm of online customer engagement, but AI’s potential applications reach much farther. And when partnered with big data, AI is poised to become an indispensable tool for increased customer retention and individualized experiences.
Big data has become a common buzzword thanks to the myriad benefits of the technology, which is helping to lead many industries into the future, from healthcare to education and finance. However, big data cannot exist on its own, and the task of analyzing relevant data and drawing useful conclusions from that data can be time-consuming and tedious. That’s where AI fits into the big picture.
As the old adage claims, time is money, and AI may just be the workhorse that companies and business owners need to produce results in an efficient time frame, one that’s likely impossible for human analysts. What’s more, the decision-making skills of AI are vastly superior to that of humans, and AI has even come out on top against world-class chess champions. Let’s delve deeper into AI and its benefits for businesses — now and into the future.
AI and Social Responsibility
As humanity continues to experience the lasting effects of climate change, the need for viable solutions becomes remarkably clear. And there’s no reason that social responsibility, sustainable practices, and profit margins can’t co-exist in our modern business landscape. Perhaps social responsibility is even the missing link that can help your business to maximize profits and retain customers over the long-term.
In fact, 21st-century consumers have come to expect business to achieve some level of corporate social responsibility. And they’re willing to pay for it: 87% of consumers claim that they would purchase a particular product if its associated company supports an issue that the consumer cares about.
Social responsibility is much more than simply a passing fad, with AI serving as a cornerstone of mobile big data solutions in sustainability and social change. For instance, a 2019 GSMA study found that advanced mobile network analytics and AI could “positively impact more than 150 million people over the next five years.” Relevant areas where AI is an effective tool for social good include disaster response, disease prevention, and air pollution management.
Improved Efficiency Using AI Tech
While corporate social responsibility is often a crucial consideration for modern consumers in an over-saturated market, efficiency isn’t far behind. Consumers prefer an experience that’s streamlined and relatively hassle-free, and project managers are likely to want the same. To keep business costs down and make more informed management decisions, big data analytics serve as an ideal option.
Big data analysis is vital to initiating effective business changes, as well as ensuring that projects are completed within both the set budget and allocated time frame. When project processes are streamlined to maximize efficiency, consumers can reap the benefits alongside the company. Further, big data can improve your company’s efficiency by identifying potential risks before a project is in full swing.
Of course, AI can’t handle the entire workload, and you want the right people for the job. Machine learning can assist with the hiring process as well, from ensuring that the right candidates see your job posting, to weeding out those who aren’t a good fit, all without the need for any human interaction.
Elevating the Customer Experience
In the current digital landscape where the bulk of our actions are tracked via AI, from online shopping habits to entertainment preferences, consumer personalization is easier than ever. And personalization is increasingly what consumers have come to expect from service providers:
AI and machine learning can help your business reach the ideal balance of personalized customer experience without seeming intrusive. Advanced machine learning-driven applications take the concept even further, essentially replicating human decision-making skills while interpreting massive data sets. Machine learning allows for reduced customer service handling times, improved response accuracy, and a streamlined scheduling process.
In addition, AI helps to keep personal data secure, as exemplified by Cisco’s ecosystem of partners and developers, which helps identify compromised devices and malicious activity. Advanced machine learning can also detect anomalies in the cloud and self-learn its normal activity in order to more accurately detect threats.
Key Takeaways
If you haven’t already integrated AI into your business model, don’t waste another second. The customer journey is increasingly fueled by machine learning, allowing for heightened efficiency and improved customer experience. Greater customer satisfaction through the use of AI thus drives retention rates and your company’s overall bottom line.
About the author: Jori Hamilton is a freelance writer residing in the Northwestern U.S. Coming from a marketing background, Jori took interest in blogging and content marketing and quickly found a particular interest in Technology, Business, and Productivity.
With over eight years of writing experience, she decided to jump fully into a freelance writing career. This gave her the opportunity to write for a number of great publications, including DataFloq, BizCatalyst360, Clinician Today, and The Job Network.
If she’s not writing, she enjoys traveling or being curled up in a blanket, reading a good book. You can follow her on her Twitter and LinkedIn.
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