The problem-solving power of AI – Part One

By Catherine Loftus / Head of Growth Marketing, Nuon AI

There’s no doubt that in recent months, AI has hit the mainstream. Almost daily, there’s a new headline about the ways in which AI is transforming industries, from insurance to healthcare, and to entertainment. 

These leaps forward fall broadly into two categories: AI technologies that are developed to solve specific problems, and those where the AI came first and the ways in which humankind could benefit were identified as a result.

In this two part series, we will explore examples of both categories of AI being applied in real-world industries. Starting here for part one, we look at applications of AI that have been developed to solve specific, existing problems. 

Medical diagnosis & treatment:

One of the most promising areas of AI that has been developed to help solve specific problems is in the medical field: the diagnosis and treatment of diseases.

Deep learning models, particularly Convolutional Neural Networks (CNNs), have shown impressive performance in accurately identifying patterns and anomalies in medical images including X-rays, MRIs, and CT scans. In fact, nine artificial intelligence platforms have recently been given the green light for use in NHS hospitals.1

Further reading: Explore how Neural Networks are transforming the insurance industry, too

While artificial intelligence won’t replace human medical professionals any time soon, it has the potential to transform the ways in which we are able to treat deadly diseases. In a recent exploration of AI-powered personalised medicine, The Guardian reports that AI “could allow clinicians to optimise the timing and dosage of medication for individual patients, or screen patients using their individual health profiles.”2 This would result in earlier diagnosis and more effective treatment to ultimately save lives. 

Data Analysis

One of the key strengths of AI is its ability to process large data sets and extract meaningful learnings, which opens up great potential for business across multiple sectors. Tools such as Tableau and Power BI use AI to analyse complex data sets and can automate data cleaning, visualisation, and predictive modelling. 

This enables businesses to generate more powerful insights from their data, transforming the way reporting, analytics and business intelligence functions. While this could be seen as a threat to those currently working in the fields of data and analytics, at present, it’s more a case that AI tools can do the ‘heavy lifting’ of processing the data. A human mind is still the best tool for the job in terms of the critical thinking, planning and strategising that must be done in response to that data. 

Insurance Market Pricing

One of the ways in which AI is transforming the insurance industry is in market pricing optimisation. This is where Nuon AI comes in, enabling insurers to adapt retail pricing in response to market changes with greater speed and accuracy than can be achieved through human intervention.

When retail pricing strategy relies on human intervention, pushing price changes through systems and rounds of review can take days or even weeks. Insurers using Nuon AI are able to make price adjustments in real-time to react to market conditions, and optimise both take-up rate and policy premium.

Learn more: How Nuon AI works

These three areas just scratch the surface of the various ways AI is solving problems great and small. Are you utilising AI technology in your industry? Share your experience with us over on LinkedIn.

Don’t miss part two in this series, where we’ll explore examples of AI that have been developed first, with the problems it solves being discovered later. 

Read here: The problem-solving power of AI – Part Two

 

Sources

1 Mail Online: AI is set to be used in NHS hospitals for the first time after health regulator gives the green light for its deployment in radiology departments

2 Guardian: AI-powered personalised medicine could revolutionise healthcare (and no, we’re not putting ChatGPT in charge)

 

 

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