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The Use of Artificial Intelligence in Business: Four Verticals Where AI Changes the Game
5minutes read
Artificial intelligence is no longer a promising technology on the horizon but a foundational element of business strategy. Whether you’re optimizing customer experience, rethinking supply chains, or launching data-driven products, artificial intelligence for business is now central to creating long-term value.
Forward-thinking organizations are embedding AI across operations not as a novelty, but as a core enabler of growth, resilience, and competitive edge. From personalized media recommendations and real-time sports analytics to computer vision, intelligent sales engines and predictive healthcare, the application of artificial intelligence in business is transforming how industries operate and how decisions are made.
This article explores four verticals where the use of artificial intelligence in business has already reshaped processes, products, and customer relationships with clear, measurable outcomes. Companies across industries are rethinking products, services, and operations through artificial intelligence in business. Examples include AI-powered diagnostics in healthcare, real-time analytics in sports, personalized shopping in eCommerce, and content optimization in media platforms. Along the way, we’ll uncover how companies leverage AI to make smarter moves, reduce costs, and unlock opportunities that were previously invisible. These are not distant possibilities but today’s realities, backed by data, deployed at scale.
Personalizing user experience in media and entertainment business
In the media and entertainment industry, audience expectations have grown exponentially. Users now demand not just content: they want content that feels made for them. This is where the application of artificial intelligence in business has delivered one of its most powerful transformations: hyper-personalization driven by data.
Source: wired.co.uk
Modern platforms like Netflix, YouTube, and TikTok rely heavily on AI to analyze user preferences and deliver individually tailored experiences. These systems process vast amounts of behavioral data in real time, including watch history, search queries, in-app interactions, and even pause or rewind patterns. The result is an offering that feels intuitive, relevant, and often uncannily well-timed.
Take Netflix’s recommendation engine, for example: by combining collaborative filtering with deep learning, it generates personalized thumbnails, reorders featured shows based on your mood, and even promotes specific episodes rather than full seasons, leading to engagement rates where over 80% of watch time comes from algorithmic suggestions.1
But the use of artificial intelligence in business here goes beyond just suggesting what to watch. In production, AI tools now assist in everything from script analysis and casting decisions to trailer creation. Generative AI models are helping studios test scene variations, localize content for global audiences, and even simulate lighting or voiceovers during post-production — all while cutting costs and timelines.
Computer vision also plays a growing role in content moderation and copyright protection. Streaming platforms leverage AI to automatically detect and flag inappropriate content, apply region-based restrictions, and identify unauthorized uploads.
AI’s implications for business strategy in this vertical are profound: it’s not just about scale but about precision. Companies that can serve millions of users while making each of them feel individually seen are setting a new competitive bar.
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. With AI’s ability to track every move in a game, including athlete performance and accuracy, AI applications in business have untapped potential for real-time 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.
Currently, the use of artificial intelligence in sports has become essential not only for officiating but also for training and injury prevention. Wearable devices powered by AI now capture biometric and positional data during training and live matches. Algorithms analyze this data in real time to detect fatigue, predict risk of injury, and optimize recovery plans, helping teams protect athletes’ health and extend peak performance windows.
AI also supports coaching staff by generating opponent analysis, simulating different match scenarios, and identifying strategic gaps. For example, basketball teams are using AI systems to review every play in slow motion with predictive tagging, while football clubs use AI to recommend tactical adjustments based on real-time shifts in player positioning.
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.
The broader artificial intelligence implications for business strategy in sports are clear: better data equals better outcomes. Teams that use AI gain a competitive edge through smarter scouting, personalized training, and enhanced fan engagement via data-driven storytelling.
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.
Nowadays, the application of artificial intelligence in business has transformed eCommerce into an experience-first economy. Beyond basic recommendation engines, retailers are deploying AI to create interactive, personalized journeys in real time with dynamic pricing, predictive inventory, and even AI-curated product collections tailored to microsegments.
Generative AI is also reshaping product discovery. Visual search tools let shoppers upload a photo to find similar items, while AI-generated product descriptions now align with SEO and brand tone automatically. Voice commerce is gaining ground as well, with smart assistants understanding context, preferences, and even emotions to guide purchases.
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.
Retailers also use AI to manage supply chains: forecasting demand, optimizing delivery routes, and dynamically adjusting stock levels. This agility allows businesses to respond instantly to trends and disruptions, which is increasingly critical in today’s volatile global market.
Ultimately, the artificial intelligence implications for business strategy in eCommerce are profound: AI doesn’t just support sales but shapes the entire funnel, from discovery to retention, with a level of precision and personalization that manual systems simply can’t match.
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.
Currently, the application of artificial intelligence in business within healthcare has expanded to cover nearly every phase of the patient journey, from prevention and diagnostics to treatment and follow-up. Large language models (LLMs) are now used to assist physicians in reviewing complex cases, identifying anomalies in patient records, and even generating treatment summaries that patients can easily understand.
AI-driven clinical decision support systems (CDSS) provide real-time alerts on drug interactions, suggest evidence-based therapies, and support more accurate diagnoses. These systems are particularly valuable in overburdened health systems, helping doctors handle more cases without compromising care quality.
Finally, AI’s medical 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
Today, deep learning models outperform humans in early detection of certain cancers through MRI and CT scans, and even enable non-invasive virtual biopsies. Hospitals are also leveraging AI to automate pathology workflows, assess radiology reports, and detect early signs of diseases such as Alzheimer’s through voice and behavioral analysis.
Beyond diagnostics, the use of artificial intelligence in business strategy is reshaping healthcare operations. Predictive analytics are used to anticipate hospital admissions, allocate resources, and prevent equipment downtime. AI chatbots handle millions of administrative interactions, easing the load on front-desk staff and freeing clinicians for more critical tasks.
At the intersection of mental health and AI, startups now offer AI-powered cognitive behavioral therapy (CBT) chatbots that help patients manage anxiety, depression, or insomnia with real-time support. And in drug discovery, AI is used to simulate molecular behavior and optimize clinical trial design, drastically reducing time to market.
Artificial intelligence is well around — go for it
Artificial intelligence is deeply integrated into how businesses operate and make decisions. It helps companies respond faster, act with greater precision, and identify opportunities that aren’t visible through traditional methods.
Whether it’s refining customer experience, improving diagnostics, or optimizing logistics, the application of artificial intelligence in business delivers measurable results. For many organizations, it has become a key factor in shaping priorities and planning for the future.
Understanding the implications of artificial intelligence for business strategy means looking beyond tools and focusing on long-term value, and that requires the right partner.
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.
