The rise of AI is fueling the discovery of business use cases and AI applications across a range of major industries, such as healthcare, finance, technology, sales and marketing, and others. AI utilization has reached unprecedented levels, with substantial investment and research directed toward powering automation in real-world scenarios.
According to Statista, the current AI market value of approximately 100 billion U.S. dollars is projected to skyrocket to nearly two trillion U.S. dollars by 2030, indicating a twentyfold increase.
Let’s explore different AI applications across 6 major industries, along with some tips to get started with AI adoption in your organization.
What Can AI Do For Business?
AI enables machines to execute tasks that traditionally necessitate human attention but are repetitive. It can analyze and interpret information using vast amounts of data and algorithms, allowing for accurate predictions and informed decision-making.
AI tools brings several benefits to businesses, including;
- Efficiency and productivity by letting humans focus on higher-value tasks.
- High-velocity business decisions and operations, enabling shorter development cycles and faster ROI on development dollars.
- Agile capabilities and business model expansion, such as identifying new revenue streams.
- Reduced human error and improved quality, such as delivering error-free results in financial reconciliation.
- Better monitoring capabilities to prevent costly and disruptive breakdowns.
AI Applications Across 6 Major Industries
Artificial intelligence improves operations, streamlines workflows, and enhances customer experiences across various industries. Let’s explore some of them below.
1. AI Applications in Marketing
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The global AI market in marketing is projected to reach $40.09 billion by 2025, with a compound annual growth rate of 29.7% from 2020 to 2025.
Companies use AI to improve their marketing tactics and increase client engagement, from tailored content and dynamic pricing to AI-led email delivery times and ad targeting.
Here are some AI applications in marketing:
Personalized Content
AI technology can evaluate data and forecast consumer preferences using machine learning algorithms, enabling businesses to customize their content to each customer’s unique requirements and interests. For instance, BuzzFeed is a media firm that uses AI to tailor its content for its audience.
Conversational AI
Conversational AI refers to technologies like chatbots and virtual agents that enable users to communicate through natural language. These technologies utilize machine learning and natural language processing to simulate human-like interactions. Due to their ability to personalize, scale, and effectively communicate with users, conversational AI allows businesses to provide a seamless and dynamic consumer experience.
Ad Targeting
AI has significantly impacted ad targeting by analyzing enormous quantities of data to produce comprehensive client profiles, enabling marketers to target their adverts more precisely. As a result, marketers enjoy higher conversion rates, cheaper costs per acquisition, and a better return on investment.
2. AI Applications in Legal Services
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AI adoption is playing a crucial role in transforming the legal industry by automating routine tasks, reducing costs, and improving accuracy. Up to 60% of the responsibilities carried out by attorneys and paralegals could be automated, according to a report by Accenture.
Let’s discover how AI is revolutionizing the legal industry.
Legal Research
AI offers sophisticated algorithms to aid legal practitioners in saving time and effort while conducting legal research. Lawyers can swiftly assess and analyze massive volumes of data using AI-powered legal research tools, which helps them make better choices.
For instance, ROSS Intelligence is an AI-powered platform that helps several law firms, like Dentons, automate their research procedures and boost productivity.
E-discovery
Finding, gathering, and producing electronically stored information (ESI) in response to a legal request is known as e-discovery. Compared to conventional manual approaches, e-discovery can be carried out more quickly, precisely, and inexpensively with AI. With Relativity AI-driven technologies, legal practitioners can streamline collection to production processes.
Judge Bots
One area where AI is gaining traction is in the development of judge bots, which are AI-powered systems that can help judges make more informed decisions based on legal precedent and data analysis. Judge bots can give judges a more thorough understanding of legal issues and aid in making more accurate and consistent judgments.
China employed the nation’s first judge bots, named Xiozhi, capable of effectively handling certain civil cases through adjudication.
3. AI Applications in Sales
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The sales sector is witnessing a significant transition as AI enables them to make data-driven choices and boost performance across lead generation and customer engagement. According to a report by McKinsey, sales teams that use AI for lead generation and opportunity identification can increase their productivity by up to 50%.
Here are a few applications of AI in sales.
Conversation Intelligence
Conversation Intelligence (CI) uses AI to record and analyze speech and extract data-driven insights from the conversations between sales agents and customers. Businesses can use conversation intelligence to gather insightful information about customer behavior and preferences. This allows them to customize their sales strategy to fulfill client expectations.
By providing insights into human communication patterns and identifying common pain points, CI informs the design and development of conversational AI systems to meet customer needs better.
AI Avatar
AI avatars are one of the newest AI technologies causing a stir in the market. These are virtual assistants that offer individualized customer care and sales assistance using machine learning algorithms and natural language processing. With the help of AI avatars, sales teams can automate repetitive operations to free up time for business-critical activities. For instance, Synthesia.io is an AI video creation platform that lets you create AI avatars for professional videos.
Lead Generation
Another area in which AI has made strides is lead generation. By using machine learning algorithms and predictive analytics, businesses can effectively identify and prioritize high-quality leads based on their likelihood of conversion.
Automated lead scoring procedures can free up valuable time for sales staff, allowing them to focus on building meaningful relationships with potential clients. This way, businesses can optimize their sales efforts and improve their chances of closing deals while streamlining their lead management process.
For example, Leadzen.ai is an AI-powered lead generation tool that provides real-time updates to businesses in the prospecting process.
4. AI Applications in Technology
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IDC predicted that by 2024, the world would spend $110 billion on artificial intelligence, with the technology sector accounting for most of the expenditure.
Some latest applications of AI in the technology sector include the following:
Machine Learning Software Development
ML software development refers to developing intelligent systems that can learn from data and improve over time. This involves automating ML operations (MLOps), backend development, data engineering, and ML model deployment.
Natural Language Processing
Natural Language Processing (NLP) empowers machines to go beyond mere reading and delve into the realms of comprehension and interpretation of human language. By harnessing the power of NLP, machines gain the capacity to extract meaning from written or spoken text and undertake various tasks such as speech recognition, sentiment analysis, and automatic text summarization.
In NLP, GPT development refers to developing text generation models based on GPT-3 and GPT-4. It includes custom model training and model optimization to help businesses improve their goods and services, automate procedures, and enhance customer experiences.
5. AI Applications in Healthcare
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AI supports the healthcare industry by enabling faster diagnoses and improving patient outcomes. Let’s explore some AI applications in healthcare.
Drug Discovery
Clinical trials for each drug cost an average of $1.3 billion, and only 10% of drugs make it to the market. However, AI accelerates drug discovery by analyzing and predicting drug side effects and efficacy. AI also reduces time-to-market for critical-care drugs.
For instance, Therapeutics Data Commons is an open-access platform that facilitates collaboration and provides data set curation and algorithm design for multiple treatment modalities at all stages of drug development.
AI-Assisted Robotic Surgery
Robots in surgical procedures are rapidly gaining popularity, with hospitals relying on them for minimally invasive procedures and open-heart surgeries. Robot-assisted surgeries have resulted in fewer complications, reduced pain, and faster recovery.
For instance, Mayo Clinic in the US utilizes robot-assisted surgeries to provide precision, flexibility, and control that surpass human capabilities, enabling doctors to perform complex procedures easily.
AI-Powered Virtual Therapists
AI-powered virtual therapists offer an innovative solution to everyday mental health challenges by providing improved access to healthcare and digital patient engagement. Moreover, healthcare chatbots can collaborate with human therapists in real-time to provide feedback or suggestions.
6. AI in Finance
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AI has disrupted various industries but none like banking and finance. According to a Financial Services report, banks could save $447 billion by 2023 by using AI apps.
Let’s walk through some of its applications.
AI-Powered Personalized Banking
Personalized banking powered by AI is revolutionizing the industry. Machine learning algorithms integrated into mobile banking apps help customers make better financial decisions by identifying their spending patterns and offering valuable tips.
For instance, Tally, a fintech company, helps customers pay off their credit card debts by offering guidance on which debts to pay first and when.
Behavior-Based Investment Predictions
Behavior-based investment predictions are investment strategies that leverage machine learning algorithms to predict market trends based on investor behavior. These strategies use a combination of financial and non-financial data, such as news articles, social media sentiment, and investor sentiment, to identify patterns and trends that can be used to predict future market movements.
Micro-investing apps like Acorns use AI to analyze users’ spending patterns to predict when they can save or invest small amounts of money without affecting their daily expenses.
Anti-Money Laundering
With the help of AI, financial institutions can now detect fraudulent activities in real time, reducing false positives and improving the identification of suspicious transactions and behaviors. This is because AI algorithms can analyze a large amount of data and detect patterns humans may miss. For example, Feedzai is a fraud detection software that helps banks manage financial risks.
AI Adoption in Business
Getting started with AI adoption in your organization can be overwhelming. Here are three tips to get started.
- Start by identifying the business problems that can benefit from AI solutions.
- Assess your organization’s readiness to adopt AI, including data quality, technology infrastructure, and employee skill sets.
- Establish a cross-functional team with IT, business, and data science representatives to oversee the AI adoption process.
Visit Unite.ai to learn more about the latest trends and technologies in AI.
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