The impact that Artificial Intelligence – and Machine Learning as an extension of this – looks set to have on enterprises in the coming years cannot be underestimated.
Today, enterprises are being asked questions about how they can further harness the application of Artificial Intelligence (AI) when it comes to processing tasks and solving problems within their business. Indeed, according to a recent survey of 3,000 executives conducted by McKinsey & Co., although just a small percentage reported using AI within their core business at present, around 80% admitted to considering future deployments or experimenting with it.
Of course, in reality the ubiquitous AI has been with us for some time already, helping us with buying decisions online, when trading stocks and shares, aiding firms when it comes to tackling things like fraud and of course, assisting those at the cutting edge of cybersecurity.
Most of us are already now familiar with personal assistants such as Siri, Alexa, and Cortana. And AI within the enterprise to help with problem solving, learning and planning seems like a natural extension and fit for businesses. Certainly, the impact that Artificial Intelligence – and Machine Learning as an extension of this – looks set to have in the coming years cannot be underestimated.
What began with assistance with increasingly complex calculations, work in the field of AI has moved towards mimicking human decision making processes as businesses seek to carry out tasks in this manner. Consider the incredible growth we are witnessing in areas such as computer vision – the ability to understand images and video and apply that to the wider world and the assistance it can provide businesses with when it comes to identifying products and defects that humans would have previously had to do manually.
This brings us nicely to the two types of artificial intelligence that we see within the workplace and how they apply to today’s economy. The first, Narrow AI, represents those computers going about tasks in an intelligent fashion that aren’t specifically programmed to do so. In essence this means that such systems can only be taught specific tasks. This could be anything from virtual assistants to AI solutions for spotting things like tumours in healthcare. The other flexible form of intelligence, or artificial general intelligence in essence represents that which we seek to replicate, one with reason and the adaptable form of intellect that only humans have displayed until now. Of course, the possibilities for AI are almost limitless.
Gartner was another to recently suggest that although AI is not yet commonplace within the enterprise, almost half of CIOs plan to adopt it in the near future. Furthermore, around 20 percent of CIOs have pilot AI programs in their implementation pipelines. This is because AI, when combined with cognitive computing, enables enterprises to dive deeper when it comes to analysing data analytics, identifying patterns, improving industrial processes and of course security. When you consider the impact it can have in terms of extending personal relationships with customers and end-users, the argument for further deployments that provide more accurate, actionable data becomes even more compelling.
The cloud is another aspect helping to bring AI to the masses. With the mobile internet now delivering global networking and the associated digital technologies businesses have literally billions of potential new customers. Taking this one step further, imagine cloud-based AI and the implications this might have in terms of robotics and accelerated learning processes when it comes to sharing data across huge networks.
Right now, much of the focus has been around machine learning – where a computer system is fed huge amounts of data, which is then used to learn how to carry out a specific task – and deep learning. Such tools are already helping thousands of businesses worldwide through huge cloud-based platforms such as Azure. For its part, Microsoft is offering firms on-demand AI-powered services and access to its growing ecosystem of artificial intelligence, machine learning and deep learning technologies.
Already trusted by around 90 percent of the Fortune 500 companies, Azure is also enabling businesses to forecast trends, create real-time data, and make accurate predictions based on that data. And with machine learning these outcomes are continually improving as firms use solutions such as Microsoft Cognitive Services, Azure Bot Service, Visual Code Studio, AI toolkits and Redmond’s own specific Machine Learning Services to add intelligence to their operations. This means enterprises can drive digital transformation and continually use data new and valuable ways.