Companies know that to compete, they must keep up with the latest technology. While still relatively nascent, artificial intelligence (AI) is set to accelerate rapidly. If companies don’t embrace AI within the next five years they may not survive, according to new research from GlobalData.
AI, and its potential, has been on the horizon for decades but it has not yet been fully realised due to technological constraints.
Now, advancements in rich data sets and affordable accelerated computing mean that it is moving into the mainstream, and those who don’t keep up will be left behind.
The role of machine learning in enterprise technology
These developments have allowed an increasing number of companies to utilise machine learning, an AI technology which lets machines learn and improve by using algorithms to interpret large amounts of data.
Machine learning is used to predict outcomes and determine what is likely to succeed or fail.
Deep learning, a subset of machine learning, uses algorithms called artificial neural networks that function in roughly the same way as the human brain.
Deep learning is, possibly, the most hyped piece of AI technology, but with good reason – it has the potential to transform a range of industries, offering trillions of dollars to businesses that harness it.
A recent report from McKinsey Global Institute, titled “Notes from the AI Frontier”, predicted that, depending on the industry, applying deep learning technology could gain a company between 1% and 9% of its revenues. It estimated that the overall annual boost from AI techniques across multiple sectors was between $3.5tn and $5.8tn, making up about 40% of the value that could be created by enabling all available analytical techniques.
Several companies already place AI and machine learning at the centre of their business models, with highly lucrative results. Leaders include Google, Microsoft, Amazon, Baidu, IBM, GE and SAP. Most of these companies have also invested in other AI technologies such as voice recognition, recommendation engines, high-end processors or as a supplement to master data management.