When AI or ‘Artificial Intelligence’ is mentioned, the thought of talking robots and self-driving vehicles spring to mind. While these technologies do exist, we are yet to be served our morning coffee by a distant cousin of C-3PO. However, artificial intelligence is advancing and becoming more common place in organisations; an increasing number of businesses are adopting AI technology to improve many aspects of their operation behind the scenes. But where has the real success with AI been?
Big data has unlocked a wealth of insight for small enterprises and multinational corporations alike. In today’s world, data is collected from every aspect of our lives; from our viewing habits on the internet and television to our travel patterns. For a business, access to this insight is an extremely valuable asset. In a recent report published by Capgemini, it is stated that 61% of companies’ surveyed say that Big Data is becoming a driver for current revenue in its own right. In order to obtain these insights, businesses must compile and analyse the data, however the volume and frequency in which it is collected has challenged traditional methodologies. According to the IDC, there will be 44 Zettabytes (or 47,244,640,256 Terabytes) of data in the digital universe by 2020. The constant increase of data is a double-edged sword for collecting customer insight: on one side it allows for a better understanding of your customers, but on the other, it shrouds the data signals in a prodigious smoke-screen of irrelevant statistics and outliers disguised as valuable insights.
The advances in artificial intelligence, particularly the Machine Learning sub-field, have paved the way for a new generation of data analytics. Machine learning systems sift through billions of data points, latching onto unique ‘’gems’’ hidden within the data sets. As the name suggests, these systems not only locate the signals within the noise, they also learn and evolve when exposed to new data. This agile data analysis creates a number of benefits for those that implement it:
- Targeted Marketing & Sales communications: AI systems have the ability to segment customer groups with more precision than ever before. By segmenting into smaller groups, the system can develop bespoke communication tracks, in some instances unique to each customer, in real time.
- AI-Powered Recommendations: The ability to make recommendations that precisely fit a customer’s needs is the holy grail of sales & marketing. With a Machine Learning system, data from multiple sources can be used to build a customer knowledge base of incredible depth and can be utilised to make accurate predictions for products or services customers are most likely to resonate with.
Businesses from every industry have been using systems to automate basic tasks for many years. What was once considered the work of robots in factories is now part of the everyday working environment. With recent developments in AI technology and its availability, now even the smallest of businesses have the ability to utilise artificial intelligence to conduct everyday tasks, from sales communication follow up, to data analysis. On the larger side, the developments are even more exciting.
- Manufacturing businesses can improve their supply-chain management through utilising AI to manage inventory and streamline operations.
- In large scale customer service centres, developments in natural language processing have meant businesses are now starting to replace their customer service representatives with systems that respond to conversational prompts. This level of automation can free up resources giving capacity back to already stretched teams.
While some show hostility towards the use of artificial intelligence, there have been numerous studies that show real benefits for businesses. As the development of artificial intelligence continues, and its use becomes ever more present, AI laggards may eventually have no option but to adopt systems in order to stay competitive. The adoption of artificial intelligence systems, however, is not as simply just switching from human operated processes. Businesses must consider a number of aspects before being able to reap the benefits;
As the collection of personal data over the years increased, so did the concerns over privacy. Up until recently, there were little regulation stopping the collection and use of personal data. However, new legislation has or will be brought in, in order to mitigate these privacy concerns. The most notable being the General Data Protection Regulation (GDPR) that will be in place as of next year. This will directly affect organisations that currently, or plan to, use Big Data analytics. To receive valuable insights from Big Data, a large data set must be present. With the increase in regulation, it may be harder for organisations to retrieve and use a large collection of data.
It is common knowledge that artificial intelligence requires data in order to learn, but it is often overlooked how much data is required. To truly receive the benefits of an AI system, hundreds of thousands times more data needs to be provided than can be processed by a human. The first issue is obtaining the data in the first place and secondly, being certain of the robustness of the data. AI is only as good as the information it is fed, if false data is provided it could take the systems learning on a tangent which in turn could provide incorrect outcomes.