By: Sourav Chhabra     July 6, 2020

Artificial Intelligence (AI) has been top of mind for many of us in business intelligence for quite some time. It's featured prominently in Gartner's hype cycle, and it's evident that AI will play a big part in business intelligence 's future. For example, some of the newly established AI capabilities tend to come straight out of a science fiction movie: voice recognition and digital assistants, task automation, medical diagnosis, and facial recognition systems — and systems to combat those facial recognition systems.

Not only is AI capable of doing all those fantastic science fiction things, but it can also make a big difference in our world of analytics. Business artificial intelligence helps democratize the data and improve the adoption of analytics. A new generation of BI tools has opened the door to radical advances in computing power, predictive analytics, machine learning and AI. If properly implemented, AI draws actionable lessons from diverse data sets and automatically recommends next actions. AI provides data points with very little work required by the user exactly where and when they're needed most.

Artificial Intelligence and business these days

Instead of acting as a replacement for human intelligence and creativity, artificial intelligence is commonly seen as an instrument of support. While artificial intelligence is currently struggling to complete common sense tasks in the real world, it is excellent at processing and analysing data troves much faster than a human brain could. Artificial intelligence software may then return to the human user with synthesized course of action and present it to them. Humans can thus use artificial intelligence to help possible effects of each action and streamline the decision-making process.

"Artificial intelligence is the only way to maximize the value out of the big data ," said Janak Patel co-founder of Null Innovation, AI and IoT company. "It's a type of software that makes decisions on its own, that's capable of recommending the action in circumstances not foreseen by the programmers. Artificial intelligence offers a wider range and accurate decision-making compared to conventional software."

These features make artificial intelligence highly valuable across many industries, whether it is simply helping visitors and employees make their way around a corporate campus efficiently or performing a task as complex as monitoring a wind turbine to predict when repairs are needed.

Machine learning is frequently used in systems which capture large amounts of data. Sales and marketing tool, for example, collect data from transaction, visits and interaction on various digital endpoints that are varied in nature from analogue to comments. Data troves are then contextualized by machine learning algorithms and distributed to human decision-makers to better understand the behaviour of visitors and propensity to buy certain products.

"Because of the size and volume, you can't really get enough business intelligent experts to look into the data," he said. "Artificial intelligence plays an increasingly important role here too."

Artificial intelligence is also changing management of customer relations (CRM) systems. To remain up-to-date and accurate, software like Salesforce or Zoho needs strong human intervention. But when you apply artificial intelligence to these platforms, a normal CRM system transforms into a self-updating, auto-correcting system that stays on top of the management of your relations. Dolphyn is the great example of next level intelligence driven tool for digital marketing and sales experts. The software is integrated with the decision makers’ thought cycle to make the best recommendation.

Use cases of AI for company

⦿ Stepping up performance

Speak of gains in productivity as superpowers for an employee. You 're still doing the same quantity of tasks with this but getting more done.

Talk of the most common example of AI: speech recognition. There's huge interaction between Alexa and Siri alone. Nearly half of Americans consent to use some sort of voice recognition, and there are clear signs of making these platforms workplaces. Alexa for Business is currently used by Brooks Brothers, WeWork, Mitsui USA, Capital One and Vonage.

⦿ Making epic breakthroughse

There are certain blind spots in some organizations processes or product. When anyone sheds light on those blind spots, breakthrough happens. Machine learning and AI have been able to address these blind spots by organizations.

For medicine, this could mean evaluating the risk of patients or enabling the introduction of a new diagnostic drug. It means detecting defects in fabrication before it happens.

⦿ Real time Analytics

To a company, one of the best business advantages of AI is storing and analysing the vast amount of data in real time. This strategy enables companies to make strategic decisions and operate at a quicker pace, maintaining the firm's strong competitive position.

In the transportation industry, for example, drivers might get traffic jam data based on their location and adjust their routes promptly.

⦿ Better Customer Experience

The best thing is that computers never sleep, and customer service should be available 24 hours a day. AI-based chatbots can provide shorter response times and improved quality of interaction that will help businesses improve loyalty to current customers and attract new ones.

⦿ Automatization of business processes

AI is capable of handling both service delivery and development process automation. For example, regulating and maintaining the required environmental conditions for product storage, managing factory robotic lines, process payments, tracking warehouse balances, recording customer service requests and more.

⦿ Improving Data Security

Areas where data privacy is of considerable importance, such as the financial sector, banking services, AI can be effectively used to detect fraud and to access unauthorized personal data.

Drawback of AI to businesses

⦿ Expensive Implementation

AI is a costly undertaking mixing construction costs with servicing and repair. That can only be introduced by those with giant pockets. Businesses who don't have big pockets would find it costly to have their systems or plans enforced.

⦿ Growing machine dependency

For all the automation occurring around us, we may be moving towards a time when it would become impossible for humans to work without the help of machines. Our dependency on machines will increase exponentially, due to the introduction of AI. Therefore, human thinking and mental capacity can only diminish over time.

⦿ Hampering opportunities in jobs

There is still an ambiguity about AI creating or wiping out jobs. Perhaps, because of it, jobs will be created as well as jobs lost. Any work that has repetitive tasks is likely to be replaced by artificial intelligence.

Examples of Data Science Uses

Additionally, here are few examples of how businesses are using data science to Novel in their sectors, create new products and make the world around them even more well-structured and Organized.

⦿ Healthcare Data Analytics

Data science has acquainted number of Development in the healthcare industry. With a broad network of data now available via all from EMRs to clinical databases to personal fitness trackers, medical professionals are finding new methods to understand disease, practice preventive medicine, diagnose diseases faster and search new treatment possibilities.

⦿ Self-Driving Cars and Data Mining

Tesla, Ford and Volkswagen are all executing portending analytics in their new wave of autonomous vehicles. These cars use thousands of mini cameras and sensors to reinforce real-time information. Using machine learning, predictive analytics and data science, self-driving cars can adjust to speed limits, avoid menacing lane changes and even take passengers on the fastest route.

⦿ Logistics Data

UPS turns to data science to escalate efficiency, both internally and along its carriage routes. There is tool which uses data science-backed statistical modelling and algorithms that create ideal routes for transportation drivers. The algorithm considers weather, traffic, construction, vehicular movement etc to suggest the best route. It is estimated that data science is economizing the logistics company up to 39 million gallons of fuel and more than 100 million delivery miles every year.

⦿ Entertainment

Do you ever amaze how Spotify just seems to suggest that perfect song you're in the mood for? Or how Netflix knows just what shows you’ll love to watch? Using data science, the music streaming can cautiously curate lists of songs based off the music genre or band you’re currently into. Netflix’s data assembler will recognize your need for culinary inspiration and recommend relevant shows from its huge collection.

⦿ Finance

Machine learning and data science have saved the financial industry millions of dollars, and quantitative amounts of time. Thanks to data science, what would take around 360,000 manual labor hours to complete is now finished in a few hours. Additionally, fintech companies like Stripe and Paypal are investing extensively in data science to generate machine learning tools that quickly detect and prevent fraudulent activities.

⦿ Cybersecurity

Data science is functional in each industry, but it may be the most influential in cyber security. Being able to detect and learn new methods of cybercrime, through data science, is essential to our safety and security in the future.