5 Common Use Cases For Artificial Intelligence

AI and Data

There’s an abundance of misconceptions surrounding AI. With it comes confusion as to what areas of life and business this fascinating technology is capable of improving.

Understanding the unique differences artificial intelligence can make through machine learning, natural language processing and artificial neural networks gives us the ability to decide for ourselves whether or not it will impact us in a positive and beneficial way.  

(Spoiler Alert: It has – and will continue to enhance our lives for the better.)

Let’s unwrap some of the most common use cases for AI and computer science in this day and age.

5. Customer Service

We all know that the customer is always right. It’s a sentiment that has positioned the customer at the very center of any business that seeks to become successful. To make a profound impact. And to dominate their competition.

With statistics and insights from Microsoft, Harvard Business School and Gartner, it’s becoming clearer that customer experience is huge. Microsoft reminds us that 96% of consumers see customer service as essential to brand loyalty. Harvard Business School claims that businesses achieve profit increases of 25% to 95% by increasing customer retention rates by as little as 5%. And Gartner predicts that 89% of businesses will see customer experience as a major point of competition going into the future.

Considering that customer service is such an important aspect of running a successful business, AI is gaining significant traction. The improvements that it brings to the customer experience are impressive, to say the least.

Through Natural Language Processing (NLP), Biometrics, Chatbots and Machine Learning, AI is transforming the way that organisations interact with customers and vice versa.

With the use of NLP, companies are able to better identify and classify customers based on their needs. It’s also able to analyse and understand user queries. Which aids in the selection of relevant agents to help deal with customer complaints, issues or questions.

By using biometrics to identify users’ voices, things like PIN codes and passwords will become a thing of the past. This technology will allow customers to log in and interact with apps through voice authentication. It will work to increase simplicity and improve the overall experience that customers have.

Machine learning and NLP is also analyses and processes customer intents, desires and patterns in order to improve satisfaction and offer greater value .

Chatbots are also becoming increasingly advanced in the way that they discern user inputs (questions, statements, complaints, etc.). They are capable of providing responses in a clear, understandable and efficient way. With 24/7 availability, a noticeable reduction in costs and the ability to discover desires, pain points and the best path to take when upselling or cross-selling, chatbots are enhancing the customer experience in more ways than one.

As a matter of fact, Kia has even seen a 3x increase in conversions through their chatbot alone. This was when compared to the conversions that their website brings.

4. Marketing

Marketing is crucial to any business, whether big or small. Having a plan around your marketing strategy is essential for higher returns, an increased customer base and the overall credibility of your brand.

By simply setting goals and having a solid plan behind marketing strategies, there’s a 429% chance of higher success rates. Not to mention the fact that content marketing leaders have around 7.8x the amount of traffic on their websites. This is compared to those that don’t engage in strategic content marketing at all.

With AI entering the arena, organisations can become far more familiar with their customers; they’re able to create more persuasive and engaging content and implement marketing campaigns that are tailor-made for each individual.

Through marketing analytics (processed by ML and NLP), we’re able to analyse, discover and determine engagement levels. That and the motivators behind customer purchases and interest.

This technology has also given us access information around traffic flow on websites, giving insights into which content customers prefer. It also allows companies to discover what they’re target market enjoys. This helps with setting up customised strategies and campaigns to be directed at loyal or potential customers.

AI is ultimately able to enhance marketing approaches, business strategies and even content for potential and existing customers.

3. Sales

While sales is essential to most businesses, AI aims to make the sales process a lot easier to deal with.

By using AI, companies can extract useful insights through accurate sales forecasting. Automation combines with analytics to look at things like previous sales outcomes, which improves lead generation. Automation will free up a lot more time, allowing sales teams to better convert potential customers and strengthen existing relationships.

According to studies done by McKinsey research, AI has increased sales leads and appointments by up to 50%; Sales teams spend around 40% less time doing sales processing, gathering customer information and taking orders through the use of machine learning and automation; and call times are seeing a decrease of up to 70%.

With more time left for salespeople to focus on customer relationships, retention rates improve and there is far more opportunity to upsell or cross-sell.

AI also aids in identifying customer pain points and needs, while determining the most beneficial solutions. This helps sales teams take the best course of action.

Researchers have also found that automation can almost halve costs that are associated with simple sales activities. Machine learning can provide accurate automation that can do many of the lower-level processes that often take up a lot of time, allowing sales teams to close, strengthen rapport with customers and provide better solutions – all at a much faster rate.    

2. Healthcare Industry

The healthcare sector is essential to the maintenance of health, the prevention and management of diseases, as well as the reduction of mortality rates.

Other than the obvious reason that healthcare is essential to our longevity and functionality as human beings, this industry is responsible for massive economic growth as the employment growth rate surpasses that of other industries.

And considering the fact that AI is capable of transforming pretty much any industry for the better, it goes without saying that it has already made a significant impact on this sector.

According to Accenture, AI’s effect on the American health industry alone, has the potential to bring about savings of up to $150 billion by the year 2026 and with the use of AI in the global healthcare market predicted to grow at a compounded rate of 41.5% from 2019 to 2025, it’s safe to say that this technology is making a significantly positive impact on healthcare.

Through the use of AI, ML and NLP, major changes are already taking place in the healthcare industry. And with time, this technology continues to bring about even more improvements.

Consider the improvements in diagnostics through patient data analytics. Underlying symptoms can be detected more efficiently and better actions are recommended based on collected and processed data. Early diagnosis helps in the prevention and management of certain illnesses and diseases. It helps to reduce risks and free up availability of more resources.

These improvements extend to the following:

Pregnancy management, to observe fetus health and accurately predict and identify any potential complications.

Healthcare market research, where things like insurance plans and medicine prices can be analysed and compared to enhance competitive intelligence and action.

Real-time prescriptions and triage, where patients can be prioritised for urgent care with reduced risk rates.

1. Financial Industry

Artificial intelligence will come to impact the financial industry in a number of positive ways.

Research done by Forbes shows us that there is a large migration towards AI technology within the UK, US and Chinese financial industries.

According to the research, 85% of the financial institutions surveyed currently use some form of AI; 77% expect AI to become essential to their business in the next 2 years; and 16% of the respondents have yet to implement AI effectively.

With those stats, it becomes clear that this technology is of huge benefit to the industry as a whole.

Through the use of AI, NLP and ML, financial institutions are able to detect fraudulent and abnormal behaviours, improve regulatory matters and overall workflow, practice effective financial analysis and market trading, and gather important market-related data for better decision-making.

A popular use case for NLP is to scan through thousands of legal and regulatory documents to pick up on compliance issues. This also happens way faster than humans are capable of, helping free up time for employees to focus on more important areas.

Chatbots are also of major use to the financial industry, as they can help assist with and manage personal finances, give necessary financial advice and insight when needed, and offer better deals, packages or contracts that suit and cater to the customer.

This list provides only some of the promising benefits that AI is capable of offering humanity. By acknowledging the profound effect it will have on the future of civilisation, we’re more likely to accelerate even faster towards new innovations, more efficient systems and promising horizons.

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Michael Cowen
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Michael Cowen

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Michael Cowen is the CEO of teraflow.ai and co-hosts the Making AI Podcast. Michael is the Ex Deloitte Digital Director and Mindshare Digital Partner. He focuses on the way business models and culture shift and change to change the way people that they work in an AI-enabled organisation.

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