The Crossroads of AI Across Six Industries: Exploring the Latest AI Applications from a Business Perspective

Applications of AI


The rise of AI is driving the discovery of business use cases and AI applications across a range of key industries, including healthcare, finance, technology, sales, and marketing. The use of AI has reached unprecedented levels, with significant investment and research being done to enhance automation in real-world scenarios.

According to Statista, the current AI market value is around US$100 billion and is projected to soar to nearly US$2 trillion by 2030, representing a 20-fold increase.

Let’s take a look at various AI applications across six major industries, along with tips for getting started with AI adoption within your organization.

What can AI do for your business?

AI enables machines to perform repetitive tasks that traditionally required human attention. Massive amounts of data and algorithms can be used to analyze and interpret information, enabling accurate forecasting and informed decision-making.

AI tools offer several benefits to businesses, including:

  • Increase efficiency and productivity by freeing humans to focus on higher-value tasks.
  • Accelerate business decisions and operations to shorten development cycles and achieve faster ROI on development costs.
  • Extending agile capabilities and business models, such as identifying new revenue streams.
  • Reduce human error and improve quality, such as providing error-free results in financial reconciliations.
  • Enhanced monitoring capabilities prevent costly and catastrophic failures.

AI applications across six major industries

Artificial intelligence improves operations across industries, streamlines workflows, and enhances customer experiences. Let’s take a look at some of them below.

1. Application of AI in Marketing

Applications of AI 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.

Businesses use AI to improve their marketing strategies and increase customer engagement, from customized content and dynamic pricing to AI-driven email delivery times and ad targeting.

Here are some AI applications in marketing.

personalized content

AI technology can use machine learning algorithms to evaluate data and predict consumer preferences, allowing businesses to tailor content to each customer’s unique requirements and interests. BuzzFeed, for example, is a media company that uses AI to tailor content to its audience.

Conversational AI

Conversational AI refers to technologies such as 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. Conversational AI enables businesses to deliver seamless and dynamic consumer experiences through its ability to personalize, augment, and communicate effectively with users.

Ad targeting

AI has had a major impact on advertising targeting by analyzing vast amounts of data to create comprehensive customer profiles, enabling marketers to target ads more precisely. As a result, marketers see higher conversion rates, lower cost per acquisition, and a higher return on investment.

2. Application of AI in legal services

AI applications in legal services

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The adoption of AI is playing a key role in transforming the legal industry by automating routine tasks, reducing costs, and improving accuracy. Up to 60% of the responsibilities of lawyers and paralegals could be automated, according to an Accenture report.

See how AI is revolutionizing the legal industry.

legal research

AI provides advanced algorithms that help legal professionals save time and effort when conducting legal investigations. Lawyers can quickly assess and analyze large amounts of data with AI-powered legal research tools to help them make better choices.

For example, ROSS Intelligence is an AI-powered platform that helps several law firms, such as Dentons, automate investigative procedures and improve productivity.

eDiscovery

The retrieval, collection and production of electronically stored information (ESI) in response to legal requirements is known as e-discovery. AI makes eDiscovery faster, more accurate, and less expensive than traditional manual approaches. Relativity AI-powered technology enables legal practitioners to streamline the collection-to-production process.

judge bot

One area where AI is gaining traction is the development of judge bots. Judge bots are AI-powered systems that help judges make more informed decisions based on case law and data analysis. Judge bots help judges understand legal issues more thoroughly and render more accurate and consistent decisions.

China has adopted the country’s first judge bot named Xiozhi, which can effectively handle certain civil cases through sentencing.

3. Utilization of AI in sales

Applications of AI in sales

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The sales force is undergoing a sea change as AI enables data-driven choices to improve performance across lead generation and customer engagement. According to a McKinsey report, sales teams that use AI to generate leads and identify opportunities can increase productivity by up to 50%.

Here are some examples of AI applications in sales.

conversation intelligence

Conversation Intelligence (CI) uses AI to record and analyze audio to extract data-driven insights from conversations between resellers and customers. Businesses can use conversation intelligence to gather insightful information about customer behavior and preferences. This allows you to customize your sales strategy to meet customer expectations.

CI provides insight into human communication patterns and identifies common pain points to inform the design and development of conversational AI systems that better meet customer needs.

AI avatar

AI avatars are one of the latest AI technologies to shake the market. These are virtual assistants that use machine learning algorithms and natural language processing to provide personalized customer care and sales assistance. With the help of AI avatars, sales teams can automate repetitive tasks and free up time for business-critical activities. For example, Synthesia.io is an AI video creation platform that allows you to create AI avatars for your professional videos.

lead generation

Another area where AI has advanced is in prospecting. Using machine learning algorithms and predictive analytics, businesses can effectively identify and prioritize high-quality prospects based on their likelihood of conversion.

Automated lead scoring procedures free up valuable time for your sales staff so they can focus on building meaningful relationships with potential customers. In this way, businesses can streamline the lead management process while optimizing sales activities and increasing the likelihood of closing deals.

For example, Leadzen.ai is an AI-powered lead generation tool that provides companies with real-time updates in the lead generation process.

4. Application of AI in technology

AI applications in technology

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IDC predicted that the world will spend $110 billion on artificial intelligence by 2024, with the technology sector accounting for the majority of spending.

Some of the latest applications of AI in technology include:

Machine learning software development

ML software development refers to developing intelligent systems that can learn from data and improve over time. This includes automating ML operations (MLOps), backend development, data engineering, and deploying ML models.

natural language processing

Natural Language Processing (NLP) enables machines to go beyond mere reading and delve into the realm of understanding and interpreting human language. By harnessing the power of NLP, machines will be able to extract meaning from written or spoken text and perform various tasks such as speech recognition, sentiment analysis, and automatic text summarization.

In NLP, GPT development refers to the development of text generation models based on GPT-3 and GPT-4. This includes custom model training and model optimization to help companies improve their products and services, automate procedures, and improve customer experience.

5. AI Application in Healthcare

AI applications in healthcare

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AI supports the healthcare industry by enabling faster diagnoses and improving patient outcomes. Let’s look at some AI applications in healthcare.

drug discovery

Clinical trials for each drug cost an average of $1.3 billion, and only 10% of drugs hit the market. However, AI accelerates drug discovery by analyzing and predicting drug side effects and efficacy. AI will also reduce the time-to-market for life-saving medicines.

For example, Therapeutics Data Commons is an open-access platform that fosters collaboration and provides data set curation and algorithmic design for multiple therapeutic modalities at all stages of drug development.

AI-assisted robotic surgery

The popularity of robots in surgery is growing rapidly, with hospitals relying on them for minimally invasive and open-chest surgeries. Robot-assisted surgery results in fewer complications, less pain, and faster recovery.

For example, the Mayo Clinic in the United States is using robotic-assisted surgery to achieve precision, flexibility, and control beyond human capabilities, making it easier for doctors to perform complex surgeries.

AI-Powered Virtual Therapist

AI-powered virtual therapists offer innovative solutions to everyday mental health challenges by improving access to healthcare and digital patient engagement. Additionally, healthcare chatbots can work with human therapists in real time to provide feedback and suggestions.

6. AI in Finance

AI applications in finance

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AI has transformed many industries, but none as big as banking and finance. Banks could save him $447 billion by 2023 using AI apps, according to a Financial Services report.

Let’s look at some of its applications.

Personalized banking powered by AI

AI-powered personalized banking is revolutionizing the industry. Machine learning algorithms integrated into mobile banking apps identify customers’ spending patterns and provide valuable tips to help them make better financial decisions.

For example, fintech company Tally helps customers pay off their credit card debt by providing guidance on which debt to pay first and when.

Behavioral investment prediction

Behavior-based investment forecasting is an investment strategy that leverages machine learning algorithms to predict market trends based on investor behavior. These strategies combine 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-investment apps like Acorns use AI to analyze users’ spending patterns and predict when they can save or invest small amounts of money without affecting their daily spending.

Anti-money laundering

With the help of AI, financial institutions can now detect fraud in real time, reducing false positives and better identifying suspicious transactions and activities. This is because AI algorithms can analyze large amounts of data and detect patterns that humans might miss. For example, Feedzai is fraud detection software that helps banks manage financial risk.

Adopting AI in business

Getting started with AI adoption within your organization can be daunting. Here are his three tips to get you started.

  • Start by identifying business problems that can benefit from an AI solution.
  • Assess your organization’s AI readiness, including data quality, technology infrastructure, and employee skill sets.
  • Establish a cross-functional team of IT, business, and data science representatives to oversee the AI ‚Äč‚Äčadoption process.

To learn more about the latest trends and technologies in AI, visit Unite.ai.



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