To scale the benefits of AI-innovations, companies need to stop thinking of AI tools and applications — such as natural language processing or computer vision — as standalone solutions. Otherwise, the opportunity cost could be as large as 41% of revenue by 2023. Companies that see AI as components of next-generation enterprise IT systems stand to grow revenues by as much as one-third over the next five years. And as systems evolve, so must the IT workforce. Companies will need multidisciplinary talent that can bridge infrastructure, development tools, programming languages, AI, and machine learning. They’ll also need to combine human talent with a growing army of smart machines to create entirely new kinds of hybrid IT roles. And they’ll need to develop new ways to continuously evolve their workforce, using ongoing learning and organizational transformation to adapt to the relentless pace of systemic AI advances.
Today, some 80% of large companies have adopted machine learning and other forms of artificial intelligence (AI) in their core business. Five years ago, the figure was less than 10%. Nevertheless, the majority of companies still use AI tools as point solutions — discrete applications, isolated from the wider enterprise IT architecture. That’s what we found in a recent analysis of AI practices at more than 8,300 large, global companies in what we believe is one of the largest-scale studies of enterprise IT systems to date.
To scale the benefits of AI-innovations, those companies need to stop thinking of AI tools and applications — such as natural language processing or computer vision — as standalone solutions. Otherwise, the opportunity cost could be as large as 41% of revenue by 2023. By comparison, leading companies in our research that see AI as components of next-generation enterprise IT systems — what we call “future systems” — stand to grow revenues by as much as one-third over the next five years.
Companies building future systems are harnessing vast amounts of data, ubiquitous computing power, and complementary technologies like cloud, data lakes, 3D printing, the Internet of Things (IoT), and advanced workforce reskilling platforms. And they are implementing AI in a systemic way that captures growth today — but also anticipates change for growth tomorrow. Here’s how your company can do the same:
Reimagine the “IT Stack” for the Age of AI. The conventional IT stack — spanning applications, data, and infrastructure — has reached its practical limit. It simply wasn’t built for today’s complex, ever-changing world containing billions of devices, petabytes of data, and decentralized AI applications scaling for millions of users. Moreover, the conventional computer processing chip is now stretched beyond capacity due to the exponential growth of AI.
In place of the standalone application, leading companies are starting to reimagine their IT stacks as boundaryless systems of complex machine, employee, consumer, partner, and competitor interconnections. For example, although applications in the cloud may seem like yesterday’s news, cloud-enabled AI with its almost limitless power and elasticity is a mandatory foundation for boundaryless systems. And for most companies, there is still much to do to truly exploit the transformative combinations of AI and cloud services.
Consider how Alibaba Group’s financial arm, Ant Financial, is using the cloud and AI to offer a wide variety of services in mobile payments, banking, insurance, and wealth management. Ant’s cloud uses an open-source platform for automating deployment, scaling, and management of containerized applications. As a result, Ant is able to scale cloud-based AI-driven innovations extensively. For instance, the company has developed an AI system that assesses credit risk in seconds, targeting loans to underserved people who lack bank accounts.
