Artificial Intelligence and Machine Learning in Business
By Katrina Wakefield, Marketing, SAS UK
Artificial Intelligence (AI), once a notion confined to Sci-Fi novels, movies and research papers, is now making a tremendous impact on society.
Today, there are numerous applications of artificial intelligence in the consumer and business spaces, from Apple’s Siri to Google’s DeepMind. Siri, for example, uses natural language processing (NLP) to interpret voice commands and respond accordingly. Google’s DeepMind, on the other hand, uses deep learning. It is capable of making connections and reaching meanings without relying on predefined behavioural algorithms, instead learning from experience and using raw data as its inputs. In fact, by applying findings from DeepMind, Google was able to improve the efficiency of its own power centres, reducing the energy used for cooling by 40%.
In the business world, artificial intelligence is enabling businesses to work smarter and faster, doing more with significantly less. As technology and society continue to advance, more organisations are looking for powerful, sophisticated solutions that will improve and streamline operations.
But it’s important to appreciate that artificial intelligence is an umbrella under which a number of different technologies reside. Machine learning, deep learning, robotics, computer vision, cognitive computing, artificial general intelligence, natural language processing and knowledge reasoning are just some of the main branches of artificial intelligence.
The current state of artificial intelligence
However, many of the applications of artificial intelligence we see today are considered to be ‘weak AI’ because we have yet to release their true potential. Weak AI, also known as ‘narrow AI’, is non-sentient artificial intelligence, which focuses on one task alone. The applications of artificial
intelligence that are currently available need to be taught or directed in order to provide the insight a user needs.
Strong AI, on the other hand, refers to artificial intelligence applications that can readily formulate their own decisions without human input, apply intelligence to multiple problems, and function and behave more like a human. We are quite some way off strong AI.
Yet despite current AI solutions not being ‘true’ artificial intelligence, the benefits and capabilities they provide are extraordinary – and many industries have already incorporated some form of artificial intelligence into their day-to-day processes.
Current industries applying artificial intelligence to day-to-day operations
In some industries, AI is capable of automating business intelligence and analytics processes, providing a holistic end-to-end solution. In others, computer vision is being deployed to map and navigate terrain, contributing to the development of smart, self-driving cars that are learning to drive as humans do. Below are just a few examples of how AI is being used to improve efficiency:
- Banking and Finance – fraud detection
Many banks use the various applications of artificial intelligence to detect fraudulent activity. The AI software is given a very large sample of data that includes fraudulent and non-fraudulent purchases and is trained to determine whether a transaction is valid based on data. Over time, the software becomes incredibly adept at spotting fraudulent transactions based on what it has learned previously.
- Retail – online customer support
Many websites now offer some form of ‘chat’ functionality where you can talk to a customer support representative or sales representative. In most instances, it is some form of automated AI that begins these conversations. As these AI chat bots are capable of understanding natural language, i.e. human conversation, they can readily assist customers in finding out what they need to know, extracting information from the website, and directing them to the appropriate web page or person for further support.
As cyber-attacks increase in frequency and more sophisticated tools are used to breach cyber defences, human operators are no longer enough. Top firms across the world are investing heavily in cybersecurity to ensure their data is protected. Real-time threat detection, mitigation, and ideally, prevention, are what’s needed for businesses – and AI can deliver. Using machine learning algorithms and feeding those algorithms great quantities of data, IT and security experts can teach the AI solution to monitor behaviour, detect anomalies, adapt and respond to threats and issue alerts. AI has quickly become a key component in a business’ cybersecurity infrastructure, providing a multi-layered security strategy that is robust and sophisticated.
Preparing for the integration of AI-based solutions across departments
Organisations that respond rapidly to opportunities in artificial intelligence application will have the advantage in the landscape of the future. But, because AI is evolving rapidly, the challenge is to ensure that the business has the necessary strategies and plans to support AI capabilities as they become available, and the right technical infrastructure to support AI implementation. For many businesses, it’s not a question of if but rather when to adopt AI. On that basis, monitoring the development of AI technology and planning far in advance is necessary to adopt AI successfully.
The optimum strategy is to observe, learn and experiment with current AI. Investing too much into AI which turns out to be ineffective will be damaging for the business’ adoption and utilisation of future AI-based solutions. Instead, try to determine how your business can benefit from AI – and how it can be built into core processes to drive efficiency. Start with the outcomes you want to achieve to modernise your IT environment. Remember, AI won’t necessarily replace human operators any time soon, but it will empower organisations to do much, much more.