How to use AI in business

Most applications of AI focus on drivinggrowth in your business, but you can use it in many other ways. Companies that embrace AI find innovative methods to improve overall company performance. With almost endless applications, artificial intelligence fits nearly every business strategy. Below are some examples of how to use AI in business:

Product recommendations

You can use AI to recommend products that align with your customers’ interests and keep them engaged. AI tracks customer behaviour on your website and presents them with products similar to what they view. The e-commerce industry finds this tactic especially useful. Streaming services also take advantage of this behavioural learning strategy by analyzing the types of shows and movies you click on and offering similar titles and genres to keep you on their app longer.

Segment target audience

Similar to recommending products, your marketing department can use AI to separate audiences into different demographics and create targeted campaigns. Being in front of the right audience can make your advertising campaigns more effective. AI can compile your data and predict how customers respond to specific advertisements.

Analyze customer satisfaction

Emotion AI, sometimes called sentiment analysis, is a strategy companies use to gauge customer reactions. Companies use AI to gather data by scanning social media reviews, posts, and ratings to see how customers perceive their brand. This tactic allows companies to use those insights to make improvements.

Identify fraud

You can also use AI to help detect and respond to fraud threats. There are specific AI tools that can identify suspicious transactions in the financial industry through machine learning algorithms. Once the AI detects a fraud risk, the application halts the transaction and alerts the appropriate parties.

Supply chain operations

AI-driven solutions can help companies with supply chain issues by predicting material and shipping costs and estimating timelines for products moving through the supply chain. These valuable insights help decision makers choose the optimal way of shipping. AI also helps delivery drivers find alternate and faster routes.

Customer service

Websites use Chatbots to greet customers, which is one of the more common instances of AI interaction. Chatbots generally use a combination of machine learning, natural language processing, and AI to understand customer queries. They allow businesses to streamline their customer service processes by freeing employees to focus on matters requiring a more personalized touch. Chatbot technology can also route customers to a live agent who’s better equipped to address their requests.

Related: Customer Service Skills and How to Find Candidates with Them

Advantages of AI in business

AI is transforming the digital landscape for businesses by providing convenience, automation, efficiency, and accessibility—all geared toward increasing productivity and enhancing user experience. This tool can empower companies to reach larger, more targeted audiences and establish long-term customer relationships. Below are some advantages of AI in business:

• Automation: Most organizations perform hundreds of tasks daily. Incorporating AI into business can automate routine operations, allowing employees to focus on more critical tasks. Automation minimizes human error and ensures accuracy, which leads to more efficient and higher-quality output.
• Informed decision making: Organizations can compile massive amounts of data that may be challenging for humans to analyze thoroughly. AI technologies can predict future results, identify trends, and suggest proper action plans, allowing business leaders and management to make more informed decisions according to their goals. Companies can save time, resources, and money with this quicker and more accurate process.
• Enhanced productivity: Productivity levels typically increase when you use AI to automate workflows and optimize daily tasks. Your employees can achieve more in less time, enhancing company-wide productivity.
• Customer-centric approach: Many modern digital consumers feel empowered and prefer to deal with businesses that show they care about them. Companies that deploy AI technologies cater to the wants and needs of their customers and develop on-demand experiences. For example, a music streaming service allows users to create playlists—the AI technology can recognize their preferred artists and genres and recommend other music accordingly. As a result, they receive a more personalized experience.
• Talent sourcing and recruitment: The general recruitment process for many companies requires posting an ad for a job, reviewing resumes from all potential candidates, and conducting interviews. AI eliminates that time-consuming process using talent sourcing and recruitment solutions. You can use AI to weed through resumes and recommend the best candidates based on qualifications. Recruiters can also utilize chatbots to screen potential candidates further by asking them questions about their experience and skills, enabling hiring managers access to a larger pool of applicants. AI uses algorithms to identify patterns in resumes, interview answers, and social media profiles and summarize pros and cons based on required qualifications, making the final hiring decision much faster and more personalized.

Read more: Recruitment and Selection: How to Choose the Right Candidate

Challenges of AI in business

The business landscape is rapidly transforming with the continuous development of AI-powered applications, so implementation may not always be seamless. Below are some challenges you may face:

• Lack of understanding: AI is a relatively new field, so there’s much to learn about its inner workings. A lack of understanding can inhibit companies from choosing the right solutions for their intended purpose. The complexity also makes it challenging for businesses to identify and correct errors.
• Privacy concerns: AI technology relies on vast amounts of data to operate effectively. This data often includes sensitive, personal information, leading to privacy and data protection concerns. Companies can invest in secure data storage and data anonymization and comply with relevant regulations to mitigate these risks.
• Processing power requirements: Some AI systems can require substantial processing power to conduct complex tasks, resulting in high infrastructure costs. Cloud computing can provide cost-effective and scalable solutions to access the necessary resources.
• Not enough data: AI relies on diverse and large datasets to achieve peak performance. Not every company has access to the required quality and volume of data without forming partnerships and collaborations with others. There are options to help overcome limited data availability, like data augmentation, data generation, and transfer learning.
• Unreliable results: In some instances, AI can produce unreliable information for various reasons, such as algorithmic limitations, incomplete datasets, or the complexity of the task.
• Lack of trust: Skepticism of AI often relates to a lack of understanding of how it works. Your company can improve confidence with transparency by clearly explaining how AI arrives at its conclusions. The more your team understands, the easier they’ll get on board and trust the processes.
• Unclear goals: Implementing a practical AI system without clear goals can be difficult. Step back and evaluate your organization’s needs to identify specific processes where AI can bring tangible value. Your AI initiatives can align with your business strategies when you have clear objectives with measurable key performance indicators.
• Technical difficulties: There are many technical challenges to overcome when implementing your AI system, including scalability, data storage, and security. Considerations for the potential expansion of your AI system start at the planning stages, and investing in a robust infrastructure can control the complexity, volume, and security of company data.
• Implementation strategy: Conduct thorough assessments of your existing data availability, infrastructure, and organizational readiness to create a tailored implementation strategy for the AI system. Every company’s strategy will look different because each company has unique requirements. Create a clear roadmap to outline resources, timelines, and steps required for a successful AI integration. Collaborate with AI experts who can provide valuable insights about the implementation process.
• Cost: Implementing an AI system and the required infrastructure can be costly. Small- and medium-sized businesses feel it the most with the extra training, development, and maintenance costs.
• Lack of expertise: With a shortage of experts in the AI industry, some companies find it challenging to recruit the talent they need to implement their AI solutions.