Blog
May 9, 2019
On 25 April 2019, Microsoft passed the trillion-dollar market cap threshold and passed Apple as the most valuable company in the world.
Almost a year earlier, Satya Nadella, Microsoft’s CEO, talked about a new world vision that has helped propel the organization’s cloud and revenue growth. “It's amazing to think of a world as a computer,” Nadella said, referring to a planet filled with smartphones, Internet of Things devices and cloud computing.
And in a world that is a computer, Nadella has put AI at the heart of Microsoft’s business strategy: “AI is the run-time which is going to shape all of what we do going forward in terms of applications as well as the platform.”
The three dominant cloud vendors—Microsoft, Amazon and Google—are all aggressively selling AI offerings to enterprises today, weapons providers for a technology arms race. And by the looks of Microsoft’s latest earnings report for the second quarter of 2019, the strategy is working, led by phenomenal 76 percent Azure revenue growth.
Where Companies Embarking on AI Projects Fall on the AI Maturity Model
Today, product teams can quickly take advantage of natural language processing (NLP), image recognition, machine learning, deep learning and a range of other AI services available in all the major clouds. Companies can add these technologies to their web sites, internal operations, applications and products—all imbued with the limitless speed and scalability of modern clouds.
With so much focus and availability of AI technologies, it’s important to understand how companies are positioned when it comes to AI—perhaps the most disruptive technology wave since the internet itself.
Companies embarking on AI projects and opportunities can be classified according to an AI maturity model.
Key Levels of the AI Maturity Model
At Level I, companies run AI programs that drive operational efficiency. These are the “dabblers” – companies that drive tens of billions in revenues a year but save only a couple million using AI to automate tasks previously done by human employees. Level I companies generally apply AI to internal opportunities with a clear cost-benefit analysis, like call center automation, and use AI services like NLP along with robotic process automation (RPAs) to eliminate manual repetitive work.
At Level II, companies run AI programs to drive significant earnings or revenue impact. These are the “practitioners.” They layer machine learning through their businesses and use it to transform user experience and customer value. They reimagine digital and even physical products with AI services, adding value and improving interactions at every turn.
At Level III, companies run AI programs that drive industry change and transformation. This is often the domain of big tech—the “experts.”
Facebook determines what we see in our feeds with AI. Apple uses AI and AI chips to power marquee iPhone features like Face ID and Siri. Microsoft, Amazon and Google sell their AI services to arm the rest of the world.
But companies in every industry have an opportunity to remake their worlds with AI technologies. Here are some questions to ask when you look at your internal AI initiatives to determine your level of AI maturity:
- Are you applying AI to a practical, internal project, with a clear target benefit? Then you are operating at Level I.
- Are you layering AI throughout your business, making a material difference in user experience, growth, revenues, or earnings? Then you are operating at Level II.
- Are you designing products that will redefine the future of your industry? Then you are operating at Level III.
If you haven’t started AI programs at all, you are at Level 0, and already falling fast behind the rest of the world.
In 10 years, the leading companies in nearly every industry will have taken full advantage of AI technologies to redefine their industry and solidify their positions. Companies need to use AI to drive disruption or will have competitors drive them to disruption.
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