10 real-life applications of AI for your business

In 2019, Elon Musk made headlines by touting AI as a “fundamental risk to the existence of civilization”. Ironically - for a man in his line of work - Mark Zuckerburg countered this argument, describing the warnings as “pretty irresponsible”. 

Outside of the tech world, global leaders have also made their position known. Uncharacteristically, The Pope has even weighed in this year with a surprisingly tempered response: “Artificial intelligence can make a better world possible if it is joined to the common good”, urging his followers to pray for AI to always benefit mankind. 

And how about the rest of the world? Some seem to be grappling with the fear that James Cameron’s demonic rise of the machines could be our fate or that they’ll be soon out of a job, unapologetically replaced by a bot. 

But in digital transformation, we know the reality would make a far more sedate film plot. 

AI technologies such as machine learning, natural language processing and knowledge based systems can transform the way we work and how businesses benefit the world. 

Now is the time to question, what could AI do for your business? In my book and as a technologist, it certainly doesn’t have to be feared. AI creates systems which work to help and empower humans not remove them from society.

1. Enrich your website’s user experience with an AI assistant

Wouldn’t it be great if you could humanise the face of your website without using one of those stock automated pop-up chats? AI assistants can do just that, by offering a personalised service to visitors to your website 24/7. Not only can they provide online support, they speak to your customer on their level using natural language processing methods to understand queries and respond in a human-like manner. Adopting a more personal tone also allows you to speak in the true voice of your organisation.

Think of our very vocal friend Alexa, the brainchild of Amazon. She uses machine-learning technology to get smarter and better able to predict and understand our natural-language questions and requests.

2.            Use sentiment analysis to monitor and analyse social media opinion

Social media is a force every business on the face of the planet needs to be conscious of and depending on your customer, a negative social media image could make or break you. Counting raw social media posts is unlikely to tell the whole story, AI-powered, sentiment analysis allows you to track positive or negative social media posts to the letter making sure your business always has its finger on the pulse of public opinion.

3.            Conduct predictive maintenance of equipment

In today’s world, where premises have been left unoccupied for an extended period of time during the pandemic lockdown, wouldn’t it be advantageous to be able to be ahead of your maintenance schedule? For future-proofing, it is possible to use AI to leverage data gathered from sensors on equipment, combined with historical maintenance data to create predictive models informing maintenance procedures and minimise downtime. 

4.            Carry out logistics and supply chain optimisation

Another pressing topic for our current reality is the efficiency of our supply chains. Using AI as a prediction tool to forecast demand in your supply chain can optimise route planning to reduce delivery time and costs. Rather than replace your workforce, automation and human augmentation in warehouses also helps your staff work more efficiently

5.            Extract information from paper documents using computer vision

Optical character recognition allows you to automate the processing of printed or handwritten documents into electrical formats. This can be made possible by AI platforms such as Azure Cognitive Search that enable you to build search engine capabilities on top of this data.

6.            Voice recognition

We’ve mentioned website chat support, but why not add a voice to this tool to ensure full accessibility across your platform. Proving handy, voice recognition can also be used to transcribe meetings and automatically subtitle videos. 

This kind of technology can also be used for important AI language translation. The Children’s Society reported in 2017 that it was using Microsoft’s Translator app to facilitate some of its interactions with refugee and migrant young people. Practically this reduced costs but charity workers shared that in some cases it had eased interaction. 

7.            Personalise content and engagement for your users

Back to the work of Mark Zuckerberg, AI can help serve personalised content to users based on their previous activity. The tool analyses your interaction with content and uses this to predict relevant content you would be most interested in next. It sounds dark and if you’ve seen Netflix’s ‘The social dilemma’ you’re probably unnerved, but this type of AI can be helpful if used properly. 

Moving away from social media, Netflix uses similar tools by enabling highly accurate predictive technology based on customer's reactions to films. It analyses billions of records to suggest films that you might like based on your previous reactions and choices of films. Brilliant for choosing a festive film this season. 

8.            Create an expert system 

An AI expert system simulates the decision making carried out by an expert, it can solve complex problems by analysing large tranches of data. This sounds like we’re in classic rise of the machines territory but applications like these remove human bottlenecks in business processes and enable all members of the organisation to make informed decisions. 

Even in its infancy, AI can already do things that humans will simply never be able to. If we leverage that to augment what humans do well, AI could transform business on a magnitude only matched by the internet. We’re scaling up humans, not replacing them. 

9. Make laborious tasks, easier 

Imagine that task in your business, the one that is labour intensive, but not exactly repetitive and requires at least one person’s brain. It could be processing incoming claims, bills or purchase orders - documents all in different formats and construction which need to be understood and processed. 

Using optical character recognition, computer vision, natural language processing and layered machine learning they can be understood and processed. Couple this with integration with the existing systems and you have a much more effective process. 

The system may not be able to cover 100% of the transitions but even if it was able to do 40% or 50% that would be a huge gain on these tasks which are usually open to human error and are massively time-consuming. 

10. Abnormality detection

As humans, our brains are always tuned to spotting something out of the normal way of things - an anomaly that does not fit with the usual pattern. Data Science tools can supercharge this very human ability to be quicker and more efficient. Examples of this in action could be an ML tool flagging an “unusually high” number of login attempts pointing to a potential cyberattack, or a major hike in credit card transactions in a short period which could be linked to credit card fraud.

Thanks to the growth of various deep learning technologies, anomaly detection using machine learning is a practical solution today. Machine learning algorithms can be deployed to define data patterns that are normal and using ML models to find deviations or anomalies.