Artificial Intelligence in Business: Four Verticals Where AI Changes the Game

March 19, 2019

In current tech-driven global market, you’re either on track or you’re gone. To maintain a healthy bottom line, bringing value has always been a must. Today, artificial intelligence in business is fast becoming all about value, even beyond the tech arena margins. This makes stakeholders well aware of AI’s power to redefine the way industries compete.

To join the bandwagon, companies are now more willing to underpin their products with advanced computer vision or machine learning features. What’s in it for us tech market contributors? We seized upon our relevant expertise to nail down the major verticals where artificial intelligence helps gain a competitive edge.

Personalizing User Experience in Media and Entertainment Business

Some couple years ago, machine learning algorithms broke into motion picture industry to help early adopters produce movie trailers and design ads. To unburden humans from the time-consuming routine, algorithms are trained to spot key plot points, produce short trailer-like movie versions, and make predictions on the audience reaction.

Source: wired.co.uk

With machine and deep learning at hand, today’s media and entertainment industry contributors can crack the daunting problem of understanding client behavior in no time. Using artificial intelligence in business helps grasp who, why, and when follows content, how long an average session lasts, and why users leave.

Incorporated within your media service, deep learning or computer vision algorithms automatically determine user preferences. To make the most of the data, you can treat it as value-based recommendations on how to arrange visual assets and build marketing and advertising strategies.

Take Netflix, for instance. The video streaming platform utilizes the ML approach to tailor offerings to user needs. Analyzing a wealth of viewer’s social data along with location, movie genre, favorite actors, and more, AI neural networks come up with recommendations that convert into some 75% of viewership.

Source: medium.com

Making Fair Play a Rule in Sports

Over the last years, the advent of AI-powered solutions backed with smart algorithms have laid the groundwork for overall sports digitalization. Capable of harboring rich stats on each athlete’s performance — down to trick recognition and accuracy estimation — AI-based systems got an untapped potential for real-time visual data analysis.

Let’s take racing competition, for example. Neural networks can be trained to detect overtaking with utmost precision, leaving no room for human error or unfair play. Add to this the backup of drone-mounted camera video footage analyzed by AI algorithms within a fraction of a second — and you get amazingly detailed stats to pinpoint the winner.

Source: sporttechie.com

From volleyball and rugby to cricket to tennis — objectivity and exactitude are critical. To ensure a thorough accuracy while solving challenging cases, broadcasters can now implement AI in business. With automated processing and tagging of multi-dimensional video, artificial intelligence software streamlines tracking of the ball’s trajectory. This aids judges in spotting violations like outs, touches, and falls — all the way to stay in line with fair play.

Notably, sports teams can put AI algorithms to good use by processing rich real-time stats from sensor-powered clothing and equipment. Analyzing data on each player’s condition, artificial intelligence enables coaches to make informed tactical decisions and develop strategies on game improvement. What’s more, motion sensing helps detect individual infractions and thus disciplines athletes.

Source: skysports.com

Redefining Sales Intelligence to Drive eCommerce

To showcase products at their best, online retailers can harness artificial intelligence in business for tracking user behavior and making predictions about customer preferences. Just sit back while the algorithms process big data — from transactions to search requests — and an instant later see user shopping habits neatly mapped out. Way to go for an ecommerce scale-up.

It’s no news that ecommerce isn’t just about selling goods. It’s more about building a robust investment strategy and winning over a long-term customer base. You never know — the shopper that’s just bought a pair of glasses could have been searching for costly shoes on your site a day ago.

How to lure him to get back and buy it? Does it make sense to risk your budget going for an aggressive marketing right after the first purchase? With user behavior patterns that artificial intelligence helps generate, online businesses can make informed upsell and cross-sell decisions, keep control of sales success rate, and retain customers who are likely to bring tangible income.

The trick is, once you define the manner in which one makes purchases, shopper segmentation becomes a breeze. Handling data like zip code, average basket, loyalty subscription or search keywords, AI algorithms come up with the stats that shed light on purchasing power.

The neural networks are also good at analyzing customers’ social media activities to figure out what drives users to search and buy goods, or instead — to leave, as the case may be. Moreover, AI can efficiently tell real leads apart from tons of disparate emails and route the clients to the salespeople. Add to this the aid of chat bots that help automate inquiries, or voice services enabling customers to search for what they need via spoken word.

Bringing Together Mind and Machine in Healthcare

Despite an ongoing debate around its ethical, financial, and clinical implications, AI has found its feet in healthcare well enough to undertake a makeover in this giant industry. Dealing with an enormous pool of biomedical data, healthcare is exclusively positioned to benefit from AI’s ability to translate raw data into actionable insights.

The bulk of AI-powered medical business solutions are designed to solve healthcare problems that are well up in the air worldwide. Take telemedicine — the domain is uniquely aimed at providing care across underserved or developing regions. Enabling patients to reach out to a remote healthcare provider anytime, telemedicine apps optimize treatment resources and aid in practicing predictive diagnostics.

Underpinned by computer vision’s ability to replicate human perception, telehealth virtual assistants or chatbots can process natural language, which helps users talk or text to them as if there were human doctors behind the screen.

The IBM Watson Care Manager is an example of a full-blown cloud-based business solution that’s designed to tailor individualized care plans.

Source: ibm.com

With an eye to patient’s needs and budget, the system matches individuals with healthcare providers. On top of that, the solution considers psychological and social factors, which gives the service a bit of human touch.

Finally, AI’s image analysis power comes in handy within diagnostic X-raying. Smart algorithms aid in detecting pneumonia, identifying broken limbs and even tumor phenotypes and genetic properties.

Source: ncip.nci.nih.gov

Leveraged for non-invasive virtual biopsies today, in the near future AI can well disrupt computed tomography, magnetic resonance, ultrasound, and even nuclear medicine.

Artificial Intelligence Is Well Around — Go For It

Despite the numerous headline-grabbing use cases flashing here and there, AI has undoubtedly shown just a small fraction of its power. With its long-run potential to substantially increase industry profitability rates, AI makes great strides to breath new life into a wealth of domains.

Source: accenture.com

Oxagile boasts years of hands-on expertise in computer vision, machine and deep learning domains, building solutions that address complex challenges across a wealth of industries. Whenever you decide to start the ball rolling with artificial intelligence development, contact us — our all-rounder team has got your back.

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