What is artificial intelligence?
By Katrina Wakefield, Marketing, SAS UK
In the past, mention "Artificial Intelligence" and people would assume you were talking about a science fiction movie. But the fact is that artificial intelligence (AI) has been around for decades, six in fact, whilst the roots of the concept can be found in ancient Greek myths.
The term AI first became widespread when it was coined in 1955 by American computer scientist John McCarthy, a giant in the field of computer science and AI. McCarthy defines AI as 'the science and engineering of making intelligent machines'.
McCarthy and others spearheaded the development of modern AI, working on papers on robot consciousness, new programs, computer time-sharing and networking. And, in the six decades since then, we have made considerable progress in the development of intelligent robots.
Today, AI is comprised of multiple fields, each pertaining to a different area of AI focus - machine learning, natural language processing, computer vision, cognitive computing, robotics, deep learning, automation, strong AI and much more. The application of AI-based technology has become common in the business space - and has penetrated the consumer space as well.
Voice-activated personal assistants, such as Apple's Siri and Amazon's Alexa, represent progress in the field of natural language processing. Meanwhile, businesses are utilising machine learning algorithms to enhance business operations, improve customer experiences, automate processes and support security protocols.
We are quickly moving towards an increasingly AI-driven world, one where powerful AI-based solutions are being used in conjunction with human operators to drive efficiency. The advent of big data - including the amount of data available and our ability as humans to process it - has prompted the need for solutions to not only tackle the data, but to make use of it.
As a result, more and more businesses are using AI-based solutions to deal with the scale of information and the need to address consumer requirements in real-time to keep pace with the competition.
AI-enabled businesses in the future
As it stands, AI is used across a number of industries to improve business processes, enhance service delivery and deliver better value to customers. Employed across retail, finance, security, marketing, manufacturing and much more, AI has quickly become a ‘must have’ for the modern business. And yet, while AI is increasingly used across industries, we have only scratched the surface of its potential applications and capabilities.
According to Accenture, AI is poised to double economic growth (40%) by 2035, solving key business challenges such as slow growth, low productivity, falling capital efficiency and an aging workforce. With intelligent automation, capable of operating at scale and learning from experience, driving innovation, businesses can reach new levels of productivity, achieving significantly more, with much less.
In the future, AI will likely be employed across the business infrastructure, functioning in key, data-driven areas of the business where the scale and complexity of data is far too much for human operators to handle.
Not only will AI free up precious human resource, which can then be dedicated to value-adding areas of the business, such as consultancy, face-to-face meetings and other personal touches, it will also continue to learn from the data provided, generate insights and help to optimise processes further.
Applications of AI-based solutions
Currently, there are a number of AI-based solutions being applied to business processes; one of the most prominent is machine learning.
With machine learning algorithms, businesses can utilise a variety of analytical methods to assess big data - unstructured, diverse and high volume data - to generate new insights.
In retail, machine learning algorithms can analyse customer behaviour and purchase decisions at scale to understand how, when and why customers are buying products. The retail business can then optimise its supply cycle to meet the need of customers at the right moments.
In fraud detection machine learning improves the ability to assess data more accurately, distinguishing individual values within large data sets to identify irregularities. As fraudulent activity is hard for a human operator to spot, due to very slight variances in data, some activity may go unnoticed. However, with machine learning, large data sets can be analysed quickly and effectively. This process can then be automated across the entire operation with incredible accuracy.
From a perspective of security, facial recognition technology could be utilised alongside CCTV and machine learning algorithms to recognise faces and help prevent crime. And where cybersecurity is concerned, machine learning can be used to assess real-time data and taught to flag anomalies in a business' security infrastructure. Once threats are identified, data can then be fed back to the machine learning algorithm to improve its detection capabilties. Abnormal network behaviour can then be readily identified and enhance existing security defences.
Finally, in marketing, AI-based solutions will be used to better segment audiences, create more personalised nurturing campaigns, and truly automate the business-to-consumer relationship, delivering timely interactions and improving the overall experience.
What does AI mean for the consumer?
Ultimately, artificial intelligence will bring a variety of new experiences for the consumer - as well as enhance existing operations. As we move to an increasingly data-orientated world, businesses will want to access big data to gain better insight and visibility into what's working - and what isn't - for their business. In industries such as Finance, Retail and Marketing, where consumer insight will ultimately drive business campaigns, AI-based technology will be used to bring more personalised experiences, map behaviour at scale to understand overall interactions and analyse activity in real time.
Of course, many might feel that technology is replacing human involvement - it is not. In order to get the best quality insights from artificial intelligence, it needs to work alongside human operators who can teach the solutions progressively. At SAS, we provide enterprise-grade analytics solutions for businesses looking to understand their data and develop actionable insights. Our solutions are powerful and comprehensive, but simple to operate, taking the complexity out of the process and enabling businesses to utilise AI-based solutions to truly drive operational