Companies see Artificial Intelligence as much more than a cost savings play, looking to harness the new capabilities it can bring to their organisations and clearly understanding its vast potential.
Businesses are looking at Artificial Intelligence (AI) as a truly disruptive technology with the potential to change the way they run their organisations. Unlike many other new solutions, which are often adopted because of their potential to cut costs, companies are embracing AI so they can to bring new capabilities to their teams or to improve the support they provide to their constituents.
In a recent survey conducted by Verdict and GlobalData, 44% of respondents that invested in AI indicated that they did so in order to gain new capabilities.
Of those adopting AI, 35% made the decision in order to improve customer/patient support. These companies are entrepreneurial. They understand that AI can impact so much more than the bottom line.
This is good news, because it demonstrates that despite being in the early stages of the product lifecycle, companies clearly understand the AI’s vast potential. While many of the companies surveyed did expect to benefit from some type of cost savings – related to fewer hires, reduced training expenses, or other operational expenses – an impressive number were looking at the bigger picture.
Cleary, companies want to do more, and to do it better. And they want to harness the power of AI to help them get there. But incorporating AI can be a daunting project for many; 57% of enterprises surveyed felt they were only moderately or slightly aware of the AI solutions available in their industry.
To their credit, providers of AI solutions are taking steps to make the process easier for all involved. They are rolling out tools and solutions to encourage exploration and to speed adoption.
For example, IBM offers packaged solutions for building chatbots, incorporating visual recognition, converting audio or voice to text (or vice versa), translating text from one language to another, and understanding personality and emotions in text.
These new solutions aren’t limited to language processing or other more straightforward, horizontal applications of AI. Major players are introducing tools to encourage the adoption of foundational AI capabilities such as machine learning and deep learning frameworks. Last month, Microsoft and Amazon launched Gluon, a new deep learning library that uses high-level APIs and pre-built/modular building blocks, enabling developers to build and train their neural networks more quickly.
Google is also looking to make AI faster and more accessible with its own, supportive hardware. The company’s new Tensor Processing Units (TPUs) speed up processing and can be used for training and running machine learning models on the Google Cloud Platform. Google claims that training which took an entire day using 32 GPUs can now be done in just one afternoon using a fraction of a TPU pod.
Clearly, much is happening in the world of AI, and it is happening quickly. This explains why half of the professionals surveyed weren’t confident that they were up to speed on the latest solutions available to their businesses. But thanks in no small part to the efforts of IBM, Microsoft, Google and others, there is no doubt that they can to get there.