What Are The Top Applications of AI in Business?

We hear so much about artificial intelligence (AI) these days. But business owners have different takes on this concept as per their niche.

Some don’t know how the applications of AI in business can influence bottom-line discussions. Others stammer when asked what the tech means or how it works. 

If you’re somewhat in the dark about the benefits of artificial intelligence in business or don’t know how AI works, maybe because of the misinformation out there, this piece is for you.

Key Takeaways 

AI eliminates repetitive tasks, allowing professionals to do their best work without watching the clock.

AI doesn’t work on its own. It needs datasets and customized training to provide useful results.

AI outperforms a lot of regular staff, so yes, it will lead to layoffs. But overall, below the surface, it’s generating a new pool of creative jobs.

How Artificial Intelligence Works?

Artificial intelligence underpins three basic technologies; Machine vision, conversational AI, and Robotics. 

Independently, each AI tech can either sense, comprehend, or act. But laced with machine learning, they can work together and learn from the environment instead of just receiving commands. Here is a brief overview of the three technologies that underpin AI:

  • Machine vision: technologies that allow computers to see and interpret images like the human eye. Eg, facial recognition techs. 
  • Conversational AI: technologies that use natural language processing to understand speech and written text. Eg, generative AI like ChatGPT. 
  • Robotics: technologies that take away any work regarded by humans as dangerous or hazardous, repetitive, or just boring. Eg, automation tools like HubSpot.

Top Applications Of AI In Business

1. AI in Marketing 

Creating marketing messages that convey the right emotion can be a drag, especially if they’re inaccuracies in your consumer persona or behavioural analysis. But it doesn’t have to be. AI in business is changing the marketing dynamics; below are a few takeaways:  

  • Predict customer churn: customers stop using a product for a myriad of reasons, mostly unknown to you – until now. One of the major benefits of artificial intelligence in business is it can help mitigate churn rates. Simply sign-up for an AI customer data personalization tool such as Cortex – or any other suitable platform – build a customer churn prediction model and export your data. Within minutes, you’ll be able to predict and prevent churn. 
  • Run seamless competitor analysis: learning about the competition is easier said than done. Basic knowledge about their SEO ranking or social media presence can keep you filling in spreadsheet data for hours. Automation software waves goodbye to such tedious and boring marketing tasks. AI can help you effortlessly categorize competitors’ tweets, blogs, and other digital materials by topics, trends, and themes. 
  • Speak to one customer at a time: just like you and me, consumers love to feel seen. They react better to marketing messages specifically tailored to their needs. In a nutshell, confidently creating hyper-personalized content at scale was impossible before the dawn of AI. Nowadays, with tools like Adobe Target and Blueconic, you can find that one customer out of a million and give them what they want. 

2. AI in Customer Support

Chatbots are no longer news to the ears. We all use the internet, so I’m guessing you’ve at some point come across the little pop-up – usually at the right side of a website – telling you to leave a message; we’re available 24/7. That’s AI in action. There is voice AI, too. 

But while one of the major benefits of artificial intelligence in business is that it’s making automated support seamless, you can take it a step further; there’s more: 

  • Identify behavioral patterns: if you have got a detailed record of purchasing history or buying habits stacked in a folder somewhere far away, probably collecting dust, now is a good time to pick it up. Predictive AI tools can help you anticipate customer sentiment and identify patterns, leaving you with proactive insights on how to improve each customer’s buying experience. 
  • Detect and translate customer language: the world is interconnected, especially for SaaS brands. So on multiple occasions, consumers not familiar with your mother tongue might be at the other end of the line. Don’t fret! You can use AI natural language processing (NLP) tools to detect and translate foreign languages before it gets to your support team.
  • Synthesize existing information: having a ‘knowledge base’ or ‘FAQ page’ about your offerings makes buying a breeze. But that also means you must spend countless hours creating these materials. Well, with the application of conversational AI in business, you can generate answers to common questions about your product within seconds. 

3. AI in Human Resources

From how businesses find talents to how they recruit and onboard, AI is changing the entire HR lifecycle. While I’m about to state a few use cases (applications of AI in business), bear in mind that the success of AI-powered HR is still heavily reliant on humans. Here goes: 

  • Map out talent needs: many employees multitask. They’re forced to handle diverse issues within and outside their field of expertise. Sometimes because of low staff count; other times, HR has yet to identify the need for additional staff. AI’s predictive analysis ability makes it a plausible tool for collecting and analyzing data around vacancies. Human resource managers can use AI to highlight new team requirements across departments.
  • Target the right talent pool: finding the right people for a job involves placing your ads in groups, communities, and organizations where such talents hang out. Indeed, this is a herculean task. But, like always, AI makes it easier. Human resource managers can train AI systems with datasets about the traits and requirements needed from an ideal candidate. This way, you can easily target a limited and duly defined talent pool on LinkedIn, GitHub, Quora, etc.
  • Resume scoring and ranking: a single job ad leaves you with thousands of applications. AI-powered application tracking tools can help with resume scoring and ranking, reducing the time recruiters spend reviewing applications. 

4. AI in Accounting 

FinTech is the new name of the game. Almost every accounting department across businesses relies on AI-powered software to create invoices and automate repetitive processes. Amongst the many benefits of AI in businesses, these three accounting use cases stand out: 

  • Identify anomalies that suggest fraud: fraudulent acts such as bonus abuse, fake accounts, or affiliate frauds are hidden in data pools too granular for humans to notice. This has been an issue for Fortune 500 companies… until now. Artificial intelligence algorithms, trained on historical data, flags risk indicators at digital speed. You can use AI to spot patterns and anomalies in transaction logs or onboarding processes. 
  • Predict future financial performance: Imagine being able to predict – without sentiment – what your business’s financial state will be like in the next, let’s say, 3 to 5 years. Predictive AI can take in qualitative and quantitative data, analyze it, and forecast a company’s future financial results with high-level accuracy. 
  • Enforce corporate financial policies faster: complex and bulky legal documentation policies make enforcing new financial models tough, eg, changing billing models. If such is the case with your business, AI’s natural language processing tools can help you automate legal documentation and develop rapid case analysis faster, reducing the amount of legal work required. 

Conclusion

In retrospect, the applications of AI in businesses transcend the use cases listed above. AI also comes into play in manufacturing, sales, supply, distribution, and management. 

Anyways, finding a balance between human brain power and modern technology is key to the successful implementation of AI. So regardless of the scope or size of your business, if you want AI to work for you, you must learn to blend the best of both worlds. And, we cannot deny the fact it’s the future of the IT industry and one of the emerging technologies to watch in coming years.