Benefits of Artificial Intelligence (AI): 7 ways it makes life better

7 benefits of AI

Let’s take a look at each benefit in turn, the concerns they address, and real-life examples.

1. Automation

In the early 90s, businesses relied heavily on manual data entry and paperwork for their operations. This often required a great deal of human effort – and time – to complete.

Nowadays, many companies are turning to software robots to complete these processes automatically, in order to improve workflows and productivity – and remain competitive. This automation is one of the best-known benefits of AI, and it is widely used across all sectors from manufacturing to transport.

Simply put, automation is when a machine carries out simple, repeatable activities, following instructions set by people. Although automation still needs a certain level of human input, it’s not as labour-intensive as its legacy counterpart.

For example: insurance companies have to go through the painstaking process of validating, assessing and approving claims – taking weeks, sometimes months, end-to-end. This leads to frustrated customers, a huge backlog of requests and loss of revenue.

BNP Paribas Cardiff improved their workflow by automating the key processes, cutting down the time it took to issue a claim from 4 weeks to 10 minutes. This meant they could use the time saved to focus on more productive tasks, such as improving their marketing and client-facing efforts.

2. Smarter decisions

There’s a reason why companies are actively placing greater value on emotional intelligence than ever before; it helps reduce bias and subjectivity from decision-making. And when you have companies with high asset risks on their books, you can’t afford to get this wrong.

Artificial intelligence can analyse trends, develop data consistency, provide forecasts and identify anomalies – all of which helps it to make smarter, unbiased data-driven decisions. It’s no wonder 86% of executives are now using AI for their businesses.

For example: talent scouts at recruitment companies are responsible for finding the right candidate for the right role. But they usually become encumbered with entering, categorising, and evaluating applicant data, which takes time away from them doing what they’re supposed to be doing.

AI helps in two ways. The first is to take these responsibilities away from the scouts (automation), freeing up time and headspace for them to actually go and look for suitable candidates. And the second benefit is in the selection process itself.

AI can analyse scores of CVs in seconds, without bias, creating a more robust selection process – which may lead to greater matching accuracy, longer employee retention.

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3. Better customer service

From long wait times, to unresolved tickets, poor customer service is a common grievance everywhere, causing endless frustration, inefficiency and a strain 

But when customer service agents are bombarded with email after email – and call after call – you’d be hard pressed to call them out on delivering poor service.

There are many ways in which AI has improved customer service in recent times, especially with the introduction of smart chat bots. These are proactive, rather than reactive (like regular bots), and are able to take user inputs and algorithmically find solutions without (much) human interference. And while there is still a need to be connected to an agent for the more bespoke cases, improvements in augmented conversation means it’s only a matter of time before chat bots can seamlessly handle customer queries, end-to-end.

For example: Watson-powered “digital concierge” 1-800-Flowers uses Natural Language Understanding and Natural Language Generation to take customer orders. Instead of filling out a form and having somebody contact you, you’d simply type your request into a chatbox and 1-800-Flowers will be able to handle your query and support you in your purchase.

4. Accurate medical diagnosis

In 2020/2021, there were 12,629 clinical claims made against the NHS for medical malpractice – a 133% increase from 2006/2007; highlighting the serious need for innovation in the healthcare sector.

Over the last 50 years, medical researchers have made huge advancements in leveraging AI for more accurate diagnosis – and treatment – of disease. Building on early rule-based systems, they have overcome integration issues to establish a model that can carry out this crucial function with a level of accuracy equal to – if not a higher than – humans.

Early indications already point towards drastic improvements, with experts claiming the use of AI in analysing and reviewing mammogram and radiology images can speed up the process by at least 30 times, with 99% accuracy.

For example: Google’s DeepMind is actively involved in Deep Learning technology to fill gaps across different sectors. Part of this initiative – a collaborative effort with Moorfields Eye Hospital – is training a neural network to analyse 3D retinal scans to detect more than 50 types of eye disease.

5. Faster data analysis

Data analysis and processing has always been at the heart of successful business strategies. With the increase in the amount of data available, it’s become a tall order for analysts to manipulate data in a way that produces meaningful insights  – without spending copious amounts of time and resources.

AI in analytics can be categorised into: predictive analytics, where the AI uses historical data to make predictions; prescriptive analytics, where the AI not only predicts, but also prescribes a course of action; and augmented analytics, where the AI is able to extract meaningful insights from datasets.

For example: Arguably the most reputable data analytics tool, Google Analytics uses a powerful AI that regularly scans your data to find outliers, which represent major changes that can impact your business, delivering these insights in a simplified way to improve decision-making.

6. Reducing human error

Historically, human error has lead to some pretty devastating consequences. Billions lost in property damage. Cyber attacks. Aeroplane crashes. Data loss. Even the sinking of the “unsinkable” Titanic.

Reducing human error is a cross-cutting priority, required to save time, reduce the financial impact following damage or loss and improve efficiency. And AI has been used as a viable solution in the form of automation, forecasting and more.

For example, Suntory Pepsico in Vietnam faced production delays and expensive stoppages every time their Quality Assurance agents failed to scan expiration date code labels due to poor printing or similar issues.

To resolve this, the company introduced an AI solution incorporating cameras called “Machine Vision,” which could read the labels and instantly determine whether or not the code was valid. If a label was damaged or illegible, an ejector would remove it without stopping the production line, thereby keeping the whole process streamlined and smooth.

7. More reliable forecasting

Traditionally, analysts used historical observations to estimate future metrics, such as asset performance or revenue. But the past doesn’t necessarily represent the future, and the heavy reliance on historicals widened the gap between forecast values and actuals.

Conversely, automated AI-driven forecasting utilises data in real-time, continuously identifying new patterns to anticipate changes in the live market, thereby enabling businesses to respond in a quick and agile manner, reducing risk and protecting margins.

For example: In 2017, while many legacy retailers struggled to post positive revenue figures, Walmart saw a 63% increase in online sales, year-on-year. AI and predictive analytics were central to this drive.

Walmart’s AI instantly captured sales data from its point-of-sale systems and incorporated this within its forecasts to determine which products were likely to sell out. It was then able to suggest a substitute in real-time to shoppers who used the app, thereby improving the buying experience.

While training and development in human capabilities is a commendable effort, it’s hard for you to deny that AI makes life a lot easier. More than 90% of leading businesses continuously invest in AI, especially in terms of cybersecurity, compliance, explainability and personal privacy.

It’s not just businesses either. Around 40% of adults use voice assistants for their daily searches, while 63% prefer communicating with a chatbot than an actual person.

It remains to be seen how far these benefits of AI will extend over time and just how much more they’ll be able to reduce human error and increase efficiency in our daily lives.