How Is AI Used in Business? 10 Ways It Can Help

How Is AI Used in Business? 10 Ways It Can Help

AI is seeing widespread adoption across industries and business functions, and is reshaping how companies operate. From marketing to human resources, AI is being used throughout organizations to automate tasks, improve data analytics, and make smarter decisions more quickly.

Some of the top emerging trends in AI include generative AI and natural language processing (NLP) tools like ChatGPT, machine learning, and deep learning. According to research from Accenture, 40% of all working hours could be impacted by large language models such as Chat-GPT.

Rather than replacing workers, AI can be used to reduce repetitive work, drive efficiencies, and maximize human potential by helping employees and businesses across industries work more strategically.

Table of contents:

  1. Content generation
  2. Marketing
  3. Sales
  4. Customer service
  5. IT operations
  6. Human resources
  7. Cybersecurity
  8. Legal departments
  9. Accounting
  10. Finance

How is AI used in business?

AI has many use cases and business benefits across industries and focus areas. According to research from McKinsey, about 50% to 60% of companies have deployed some form of AI tools or resources. Below, we’ve highlighted some high-level ways AI is used in business.  

AI automation

Every role has at least a few repetitive, manual tasks, such as checking email, inputting data, and generating reports, that take away time from more impactful work. According to research from UiPath, 67% of respondents feel they are constantly doing the same tasks and waste an average of four and a half hours a week on tasks that could be automated.

AI can help automate routine tasks, which saves time, maximizes productivity, reduces the risk of human error, and drives team member engagement by enabling them to spend time on more meaningful work.

Depending on which tasks you’re looking to automate, a wide range of tools are available for different business functions and use cases, such as chatbots for customer service, applicant tracking systems for recruiting, and payroll platforms for accounting.  

Enhanced data analytics

Artificial intelligence and machine learning tools can process and analyze vast amounts of data at speeds and scale far beyond human capabilities. As a result, AI can identify patterns, behaviors, and trends that may not be immediately visible to human analysts, which helps predict future outcomes based on historical data.

Some use cases for enhanced data analytics include predicting customer churn, identifying worker turnover trends, projecting revenue, and flagging fraud patterns or behaviors.

Improved decision-making

Based on insights from enhanced data analytics, AI can also help support improved decision-making.

AI can improve decision-making by helping to identify new business opportunities, flag operational roadblocks, determine effective ways to personalize offerings and outreach based on customer data, and prepare for potential challenges.

One commonly cited example of how AI supports decision-making is that airlines typically use predictive AI analytics to determine pricing. Airlines optimize ticket prices using AI to analyze and understand demand patterns, consumer behavior, competition, and other factors in real time, leading to more informed pricing decisions.

The capabilities listed above are just a few of the many ways AI is used in business. While AI can offer significant benefits, human expertise and intelligence is still a necessity to ensure accuracy and credibility of critical business processes. With this in mind, let’s look at how AI is used across various business functions.

1. Content generation

Content creators are increasingly turning to generative AI tools to save time and improve the content generation process. Tools like ChatGPT, Google Bard, and Jasper enable users to input text prompts to quickly generate new written content such as outlines, emails, or blog posts. Tools like Midjourney, Stable Diffusion, and DALL-E generate images based on text prompts.  

A survey from Descript and Ipsos of nearly 1,000 content creators found that nearly two-thirds of respondents have already used generative AI in their content production, and more than three-quarters say they are likely to use AI tools moving forward.

Some of the benefits of leveraging AI for content creation include:

  • Increased productivity and scalability because using AI tools to generate content requires less time and fewer resources than developing content from scratch
  • Creative inspiration by using AI to brainstorm and come up with new ideas before developing content
  • AI-powered analytics track content metrics including page views, social media shares, and engagement rates to help optimize content generation strategies

While artificial intelligence can make content generation more efficient, be aware that AI content isn’t publish-ready. Content creators and marketers should see AI content as inspiration for their own content or an initial draft. Any content created by generative AI tools should be proofread by a team member, fact-checked, and edited to ensure it aligns with brand voice, style, and guidelines.

2. Marketing

Artificial intelligence tools and machine learning algorithms are used by marketing teams to analyze data, identify customer trends and patterns, optimize marketing campaigns and strategies, and enhance the customer experience.

In addition to improving marketing strategy results, AI can also help team members save time by automating manual tasks. According to a survey from Drift of more than 600 marketers, 74% believe they will be intelligently automating more than a quarter of their tasks in the next five years.

Here are a few examples of how AI is used in marketing:

  • Enhanced market research and competitor analysis. Marketing teams and professionals spend a significant amount of time conducting marketing and competitor research. AI systems and tools have advanced capabilities to find, organize, and analyze relevant market data and competitive differentiators, saving time that would have been spent on manual research. Because AI can process large amounts of data automatically, important market or competitor insights may be uncovered that marketing team members may have missed.  
  • Improved audience segmentation and personalization. AI can simplify how marketers track, understand, and predict customer behaviors. Using AI tools, businesses can also create customer profiles by segmenting customers into different categories depending on their behaviors, preferences, and demographic indicators. Based on customer profiles, marketing teams can personalize messaging and communications to highlight products, services, or promotions that are most relevant to specific customer segments.
  • Predictive marketing analytics. Marketers can use predictive analytics to identify patterns and trends from historical and current customer data, enabling teams to more effectively predict which strategies or campaigns may be most effective in the future. Predictive analytics help anticipate customer needs, optimize targeting, and identify upselling and cross-selling opportunities.

3. Sales

Predictive analytics and AI-powered algorithms enable sales teams to better understand customer behavior and preferences and automate and improve sales operations.

Sales teams can use AI to help with the following aspects of the sales process and strategy:  

  • Automating manual tasks. A survey of 7,700 sales professionals from Salesforce found that sales representatives spend an average of less than 30% of their week on actual selling. Much of their time is spent on manual tasks such as data entry and sharing updates on their deals in the pipeline. AI tools can help automate time-consuming tasks so sales representatives can spend more time on selling.
  • Demand forecasting. AI can help analyze past performance and current economic indicators to help sales teams forecast future demand. Analyzing customer data, interactions, and historical sales patterns using AI algorithms can help identify leads, prioritize prospects, identify next steps or actions to engage prospects, and optimize the sales process.
  • Lead scoring. AI-powered lead scoring tools use machine learning algorithms to provide real-time updates to sales teams about prospects and leads, which helps ensure lead scores are accurate and up to date. Each time a lead clicks on a link in an email, downloads a resource from the company website, or takes another action, the AI algorithm automatically updates the lead's score.
  • Writing and personalizing outbound email campaigns. Similar to the use case in content generation, generative AI tools like ChatGPT can be used to draft outbound emails to customers and leads. Leveraging data from AI-powered lead scoring tools, sales team members can also personalize outreach and share product recommendations based on an individual’s score, preferences, and behaviors.

4. Customer service

AI can help transform how businesses engage with customers, identify relevant insights, and improve the customer experience. Some benefits of leveraging AI for customer service include faster response times, 24/7 availability and support, and opportunities to offer tailored solutions based on customers’ specific needs.

According to a survey from DialPad of more than 1,000 customer service professionals, almost 60% of respondents believe that AI helps them save time or work faster. On the customer side, a global survey of 3,700 consumers from Zendesk found that 70% of respondents who often interact with customer support believe the use of AI by companies can lead to more personalized and effective experiences.

Common applications of AI in customer service include:

  • AI-powered chatbots. Chatbots use natural language processing and machine learning to communicate with customers in real time. Many consumer-facing and business-to-business (B2B) websites and apps across industries incorporate AI-powered chatbots to quickly answer customer questions, offer personalized recommendations, and provide support. Chatbots enable customers to receive assistance without waiting for the next available customer service representative and help businesses save time and resources. When an inquiry requires additional support from a human representative, chatbots can also route customers to the right agent or channel.  
  • Self-service and knowledge base systems. Similar to chatbots, self-service and knowledge base systems help customers find answers to their questions and solutions to common problems on their own. These systems feature advanced search functionality and include resources such as frequently asked questions (FAQs), tutorials, troubleshooting guides, and interactive tools. Accessing resources on self-service and knowledge base systems help customers save time and free up customer service representatives from answering the same questions or walking through repetitive tutorials.
  • Enhanced analytics and customer insights. AI-powered data analytics can provide detailed insights about sentiment and satisfaction based on data from customer interactions, including chatbot logs, emails, social media posts, reviews, and surveys. Using this data, businesses can identify customer preferences, pain points, and opportunities for improvement, which can help enhance and personalize the overall customer experience.

5. IT operations

In recent years, artificial intelligence has become so prevalent in IT operations that Gartner coined the term “AIOps” to describe the combination of big data, analytics, natural language processing, and machine learning to automate IT operations processes.

AIOps enables IT operations teams to integrate multiple, separate IT operations tools using a centralized platform, which helps businesses more effectively manage an ever-expanding IT landscape. As a result, IT teams can quickly respond to—and even proactively identify—slowdowns and outages, which minimizes disruptions to day-to-day business operations.

Key benefits of AIOps include:

  • Faster response and resolution time for IT tickets, slowdowns, and outages
  • Lower operational costs by combining and integrating IT systems and tools
  • Enhanced collaboration and monitoring between DevOps, ITOps, governance and security functions through integrated tools
  • Improved resource allocation by automating manual tasks and enabling IT operations team members to spend time on more complex work  
  • Capabilities to shift from reactive to predictive IT operations management using predictive analytics

6. Human resources

Leveraging AI throughout the employee lifecycle—including for sourcing and recruiting candidates, onboarding, managing employee records, and developing existing team members—can help human resources teams drive efficiencies and keep talent engaged.

According to a survey of 1,688 HR professionals from the Society for Human Resources Management (SHRM), 85% of respondents that use automation or AI say it saves them time or increases efficiency.

Some of the many use cases for AI in human resources include:

  • Writing content for recruitment materials. Recruitment and talent acquisition teams can use generative AI tools such as ChatGPT or Google Bard to help draft copy for recruitment purposes, including job descriptions, interview questions, candidate outreach emails, and job offer letters. By providing the tool with a prompt featuring relevant details about the job and type of content, the tool will generate suggested copy. While additional details may need to be shared and edits will likely be required to finalize recruitment materials, AI tools can save time compared to writing copy from scratch.
  • Automating candidate screening. Many applicant tracking systems (ATS) and similar solutions include AI technology to automatically screen candidates based on specific criteria and qualifications and weed out individuals who aren’t a fit. These systems often include capabilities to send automated emails to candidates letting them know they aren’t moving forward. This enables recruitment and talent acquisition teams to focus their time on the most qualified talent.
  • Driving candidate engagement. Similar to customer service chatbots, some employers are embracing chatbots as an innovative solution to drive candidate engagement. Companies include AI chatbots and virtual assistants on their careers pages to direct individuals to jobs that align with their skills and experience, guide them through an interactive application process, and answer common questions along the way.
  • Simplifying workforce planning. Technology such as talent management systems and human resources information systems (HRIS) centralize employee data, making it easier for companies to manage and automate HR processes. Through these systems, organizations can manage payroll, benefits, time and attendance, learning and talent development, and other HR functions. Many of these systems also include data related to talent reviews, performance, engagement, retention, and skills, helping organizations better understand worker competencies, skills gaps, and future workforce needs.

7. Cybersecurity

As cybercriminals become more sophisticated, security teams need the latest technology to detect and reduce the risk of emerging threats. According to an IBM survey of 1,000 IT and cybersecurity executives, 64% of respondents have implemented AI for enhanced security capabilities and 29% are evaluating implementation.

Artificial intelligence and machine learning can be beneficial in cybersecurity to stay ahead of cybercriminals, automate threat detection, and quickly respond to the latest risks.

A few examples of artificial intelligence cybersecurity include:

  • Threat detection and response. AI can analyze large amounts of data to identify patterns in user behavior and automatically flag anomalies that may indicate a fraud or another cyber threat. This can help cybersecurity teams detect threats in real time. AI-enabled tools can also automate tasks related to incident response and remediation, helping to address threats before they cause significant damage.
  • Security monitoring. Cybersecurity threats continue to evolve and AI-powered security monitoring solutions use data analytics to continually learn about and adapt to evolving threats and environments. Using this data, detection models can be adjusted over time, helping to enhance security capabilities and more proactively detect and prevent threats.
  • Bot prevention. Bots pose many threats to businesses, including delivering spam emails, sending a high volume of illegitimate traffic to websites, and initiating account takeovers using stolen credentials. AI-powered machine learning algorithms can be used to automatically scan incoming emails for red flags, such as malicious IP addresses and links, suspicious keywords, and large attachments and filter email to spam folders. Similar capabilities can also be used to differentiate between authentic website traffic, good bots (such as search engine crawlers), and bad bots.

While AI can drive efficiencies and improvements from a cybersecurity perspective, AI tools have the potential to pose security and privacy risks. Security teams should thoroughly vet any AI solutions or engage an outside information security professional to do so before selecting tools. Implementing company-wide policies to ensure AI tools are used securely can also be helpful.

8. Legal departments

Corporate legal departments process and analyze large volumes of data and documents. Rather than reviewing documents and completing other administrative processes manually, AI can simplify many legal tasks, enabling lawyers to spend more time providing clients with expert guidance.

LexisNexis surveyed more than 4,000 individuals, including a mix of lawyers, law students, and consumers, about generative AI. According to the survey, 36% of lawyers surveyed have used a generative AI tool either personally or professionally and 19% already use these tools in their legal practice. Areas in which lawyers see the most potential for AI tools include increased efficiency, research, and drafting documents.

Here are some specific ways that AI can be used in legal departments:

  • Research and analysis. Legal research involves spending a significant amount of time reviewing legal cases, laws, regulations, and precedents, among other information. AI-powered tools can automatically retrieve, organize, and analyze relevant legal documents, making it easier for legal professionals to find critical information, extract key insights, and make informed decisions.
  • Contract review and due diligence. Manually reviewing legal contracts and documents can be time-consuming and prone to human error. In addition to being reviewed by human legal experts, AI tools with machine learning capabilities can review and analyze contract language to flag potential issues or unfavorable terms that may otherwise be overlooked.
  • Document automation. AI can help generate initial drafts of standard legal documents, such as contracts, nondisclosure agreements (NDAs), wills, and leases, saving legal teams time and reducing human error. Keep in mind, while AI can create drafted legal documents, thorough review by a legal professional is critical before using any AI-generated documents.
  • Compliance. Different industries and businesses have to maintain compliance with specific regulations, such as HIPAA for U.S. healthcare data and GDPR for businesses that collect data from European Union Citizens. Compliance standards are complex and failing to maintain compliance can lead to breaches or penalties. Companies can leverage and train AI algorithms to understand specific laws and regulations and identify discrepancies more efficiently than manual methods.

9. Accounting

Accounting teams often spend a lot of time on manual, repetitive tasks, such as data entry, managing payroll, and approving expenses. By adopting artificial intelligence on accounting teams, many of these tasks can be automated, saving time and resources.

According to an Intuit survey of 2,000 accountants, 48% of respondents plan to invest in automation tools and AI in the next year. The survey also found that 82% of respondents believe technology creates more meaningful client relationships.

Benefits of using AI tools in accounting include:

  • Automated tasks. Artificial intelligence can automate many manual accounting tasks, including data collection, data entry, categorization, reconciliation, and invoicing, freeing up accountants’ time to work on more strategic projects and interact with clients.  
  • Streamlined payroll management. The American Payroll Association estimates up to an 8% human error when manually processing payroll. AI and machine learning can automatically process payroll, saving time, eliminating human error, and ensuring payroll is accurate.
  • Tax audit support. AI-powered tax audit support tools can help auditors and accountants effectively prepare financial statements and records to ensure they’re accurate, up to date, and relevant. AI also simplifies document management, enabling tax auditors to easily identify and access relevant financial data and reducing the time and resources spent to complete audits.

10. Finance

A 2022 report from PwC found that 53% of CFOs surveyed are looking to accelerate digital transformation using data analytics, AI, automation and cloud solutions to help drive standardization and intelligently automate as many manual processes as possible.

Embracing AI in finance can help finance teams and organizations analyze patterns from large data sets, streamline processes, improve decision-making, prevent fraud, and maintain compliance, among other benefits.  

A few specific ways AI is being used in the finance sector include:

  • Real-time data analysis. Finance teams and financial services organizations manage a significant amount of data—keeping track of the most critical business insights can be challenging. AI tools can automatically process high volumes of data and identify patterns and trends, saving time and uncovering insights that may have otherwise been overlooked. These insights help finance professionals make better data-driven decisions related to managing credit, calculating risk, vetting borrowers, and determining investments.
  • Fraud detection and anti-money laundering (AML). Many fraud detection and AML processes are manual, time-consuming and pose a risk of human error. AI-powered data analytics can be used to evaluate financial transactions and related activities in real time to identify normal versus abnormal or suspicious behavior. Once suspicious activity is detected, AI tools can notify human analysts or other relevant parties to review further, which helps increase efficiency.
  • Compliance. AI can help automate compliance checks and maintain real-time records of all financial transactions and activities, which can reduce the overall risk of regulatory breaches and penalties.
  • Forecasting and budgeting. AI tools can analyze financial data to make predictions. AI can process large volumes of historical performance data, including market trends, economic indicators, and company-specific metrics, to generate predictions about future trends or outcomes. As a result, AI can help inform improved budgeting and resources allocation decisions, while minimizing potential financial risks.

Embrace AI across your business

By integrating AI across your business, your organization can save time, reduce costs, leverage advanced data for improved decision-making, and empower your team members to focus on more strategic priorities.

The most successful AI initiatives are powered by human expertise. If you’re looking for expert support to help maximize the business benefits of AI, consider engaging an independent professional on Upwork. Skilled AI engineers are available on Upwork to help your team identify and implement impactful AI tools.  

With Project Catalog™ you can simplify the process of identifying AI experts by searching for fixed-priced projects or one-on-one consultations. Find the right generative AI project that best aligns with your budget and business needs and begin working with an expert right away.

Disclosure: Upwork is a Jasper Affiliate and may receive referral payments from Jasper. When using Jasper, you will be subject to Jasper’s Terms of Service and Privacy Policy. As always, independent professionals remain responsible for evaluating the tools offered and determining the fit for their business needs, as well as their own compliance with all laws and legal requirements in operating their freelance business.

The other tools and services listed in this article are provided only as potential options, and each reader and company should take the time needed to adequately analyze and determine the tools or services that would best fit their specific needs.

This article is intended for educational purposes and should not be viewed as legal or tax advice. Please consult a professional to find the solution that best fits your situation.

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Author Spotlight

How Is AI Used in Business? 10 Ways It Can Help
Beth Kempton
Content Writer

Beth Kempton is a B2B writer with a passion for storytelling and more than a decade of content marketing experience. She specializes in writing engaging long-form content, including blog posts, thought leadership pieces, SEO articles, case studies, ebooks and guides, for HR technology and B2B SaaS companies. In her free time, you can find Beth reading or running.

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