6 Ways Artificial Intelligence (AI) Revolutionizes Business
If you clicked on this article by reading the headline you've probably heard of Artificial Intelligence. Stephen Hawking has said, “Every aspect of our lives will be transformed [by AI],” and it could be “the biggest event in the history of our civilization.” We’re not quite there yet, but it’s only a matter of time. So what would AI mean for business and leadership, and how does analytics come into play? AI is here and not just the movie companion to Tony Stark, real AI has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage but that doesn't mean its widely or even accurately understood. Let's unpack the technical capabilities of AI from the perspective of what it CAN do and HOW it will change the way we do business activities.
So what exactly makes Artificial Intelligence so revolutionary?
- AI automates repetitive learning and discovery through data. But AI is different from hardware-driven, robotic automation. Instead of automating manual tasks, AI performs frequent, high-volume, computerized tasks reliably and without fatigue. For this type of automation, human inquiry is still essential to set up the system and ask the right questions.
- AI adds intelligence to existing products. In most cases, AI will not be sold as an individual application. Rather, products you already use will be improved with AI capabilities, much like Siri was added as a feature to a new generation of Apple products. Automation, conversational platforms, bots and smart machines can be combined with large amounts of data to improve many technologies at home and in the workplace, from security intelligence to investment analysis.
- AI adapts through progressive learning algorithms to let the data do the programming. AI finds structure and regularities in data so that the algorithm acquires a skill: The algorithm becomes a classifier or a predictor. So, just as the algorithm can teach itself how to play chess, it can teach itself what product to recommend next online. And the models adapt when given new data. Backpropagation is an AI technique that allows the model to adjust, through training and added data, when the first answer is not quite right.
- AI analyzes more and deeper data using neural networks that have many hidden layers. Building a fraud detection system with five hidden layers was almost impossible a few years ago. All that has changed with incredible computer power and big data. You need lots of data to train deep learning models because they learn directly from the data. The more data you can feed them, the more accurate they become.
- AI achieves incredible accuracy through deep neural networks – which was previously impossible. For example, your interactions with Alexa, Google Search and Google Photos are all based on deep learning – and they keep getting more accurate the more we use them. In the medical field, AI techniques from deep learning, image classification and object recognition can now be used to find cancer on MRIs with the same accuracy as highly trained radiologists.
- AI gets the most out of data. When algorithms are self-learning, the data itself can become intellectual property. The answers are in the data; you just have to apply AI to get them out. Since the role of the data is now more important than ever before, it can create a competitive advantage. If you have the best data in a competitive industry, even if everyone is applying similar techniques, the best data will win.
DNV GL has opened an Artificial Intelligence Research Center as it seeks new solutions to enhance its services. With the AIRC we aim to develop new solutions based on AI technology, such as computer vision (whereby a computer can carry out tasks that require high levels of visual recognition), at the same time as creating future assurance schemes for the complex algorithms associated with AI.
DNV GL is already utilizing disruptive technology to challenge operations that have remained largely unchanged for decades; for example, the company recently undertook the first set of remote surveys whereby inspections on board ships are carried out virtually using cameras, rather than in person. Blockchain has also become an integral technology to the company’s assurance operations, and Italian winemakers are amongst the first to use My Story?, an application that uses blockchain to track the whole supply chain. DNV GL has explored how AI could improve safety in the oil and gas industry. We're in the business of trust and more and more, trust is being developed through digital technologies. Whether thats Blockchain, Big Data, AI or VR, we've made the necessary investments to equip the world with a trusted and digital future.