Source | www.abhijitbhaduri.com | Abhijit Bhaduri |Keynote speaker, Author and Columnist
China is becoming the world’s AI Superpower. 3 out of 7 AI giants are in China. What can others learn from their strategy.
Becoming an AI Superpower
Artificial Intelligence will be the next electricity. Take healthcare. The market for healthcare artificial intelligence tools is expected to surpass $34 billion in the next 18 months. AI will drive $8.6 billion in annual revenue by 2025, contributing to the $34 billion total in software, hardware and consulting.
AI is changing how we consume media. Google reported that Hindi Voice Queries are growing 400% YoY. AI is unifying Video, Visuals and Voice to create unique possibilities. Imagine being able to read a story to your kid and your AI powered TV shows the appropriate visuals and sound effects that enhance the experience. Imagine what this could do in a classroom.
Artificial Intelligence systems begin to control safety-critical infrastructure across a growing number of industries. Microsoft has recently announced the use of AI models to dramatically improve fraud detection rates and detection times for banking> This uses a behavioral-based AI approach and can be much more responsive to changing fraud patterns than rules-based or other approaches.
IDC estimates the potential corporate market for AI software, hardware and services to be almost $58bn by 2021.
3 Lessons from the AI Superpower – China
China is determined to lead the world in AI. China will add $7 Trillion of the $15.7 Trillion of the world’s GDP by 2030.48% of the world’s AI funding comes from China. The result is that three out of the seven AI giants is in China (Baidu, Alibaba and Tencent) China has 168 unicorns valued at a staggering $628 Billion.
What can you learn from China’s strategy?
There are three big ideas your business has to focus on:
- Creating a data strategy
- Tools to turn data into insights
- Talent who can turn insights into action
1. AI is all about data
Your customers and employees and suppliers browsing habits and smartphones create vast amounts of data. As your watch and toothbrush gets connected to the internet, they will create a more granular profile that will allow providers to individualize their offerings, just the way Netflix does. Self-driving car will generate 100 gigabytes per second.
WeChat in China combines the power of WhatsApp and PayTM. Their one million Monthly Active Users alone is more than the population of Europe.Since all the data is in one place, it is easy to turn data into insights.
2. Tools to turn data into insights
GM may have sold 2.3 million cars and Tesla may have sold a few thousand. But each of the cars that Tesla has sold is a data generating machine. It changes the nature of competition. Amazon knows which product is gaining traction and can buy out the manufacturer. By providing barriers to entry and early-warning systems, efficient use of data. Each time you pause, rewind and watch a movie, the Netflix algorithm makes a note. Netflix will spend $12bn-13bn this year—more than any studio spends on films.It is currently making programmes in 21 countries, including Brazil, Germany, India and South Korea.
3. AI talent to take action
If you think Netflix is going to need talent to make or acquire the 700 new or exclusively licensed television shows, wait till you see the mayhem that is taking place in AI. According to Gartner, lack of AI skills is the biggest challenge say 54 percent of CIOs looking to adopt AI, according to Gartner. Here is a course in AI that companies are encouraging their employees to take. <click this>
Chinese AI researchers are at par with US. At AAAI’s 2017 conference, an equal number of accepted papers came from US- and China-based researchers. Companies have to try unusual tactics to bridge the talent gap. <read more>. Talent is boundaryless. You can tap into this decentralized network of AI professionals across the world. Companies have to be build AND buy talent. It is not a choice between the two.
The ideal candidates organizations need must have an academic background, specifically in mathematics or statistics and understand the tech tools used to build machine learning systems. Oh yes, the candidate must be brilliant in communication and soft skills. If you are one of them, the gold rush is on.
The last word
This is no longer about doing one of the three strategies. All three have to be done. They have to be done fast.