Co-founder of Google Brain and former Chief Scientist at Baidu, Andrew Ng, has unveiled an AI Transformation Playbook. The guide to successfully adopting AI in enterprise draws on insights gained from leading AI teams at Google and Baidu.
Andrew Ng claims that, “it is possible for any enterprise to follow this Playbook and become a strong AI company.” However, it is primarily intended for larger enterprises with a market cap/valuation from $500 million to $500 billion.
The AI Transformation Playbook is distributed freely on the Landing AI website. Under Ng’s leadership as Chairman and CEO, Landing AI helps enterprises develop and execute cohesive AI strategies.
Five key steps form the backbone of the guide:
- Execute pilot projects to gain momentum
- Build an in-house AI team
- Provide broad AI training
- Develop an AI strategy
- Develop internal and external communications
Unsurprisingly, pilot projects are emphasised as vital to identifying appropriate use cases for AI in business scenarios and gaining momentum within a company. As Andrew Ng explains:
They should be meaningful enough so that the initial successes will help your company gain familiarity with AI and also convince others in the company to invest in further AI projects; they should not be so small that others would consider it trivial.
The guide maintains that it should be possible for a new or external AI team to build AI solutions that start showing traction within 6-12 months, feasible with existing technology, and have clearly defined and measurable objectives that creates business value.
The former Google Brain head provides an example from his work with the Google Speech team – while not a key aspect of Google’s business at the time, by improving Google’s speech recognition technology, Ng was able to convince other parts of the company of deep learning’s potential, thereby giving it vital momentum.
With this method, the Google Brain team developed a model for successful AI pilots and was able to repeat this with Google Maps and other projects – getting internal customers onboard in the process.
In-house AI teams
The AI Transformation Playbook stresses the importance of an in-house AI team for long-term success. While outsourcing can offer greater initial momentum, keeping the work in-house can boost efficiency and provide unique competitive advantages.
“In the AI era, a key moment for many companies will again be the formation of a centralized AI team that can help the whole company. This AI team could sit under the CTO, CIO, or CDO (Chief Data Officer or Chief Digital Officer) function if they have the right skillset. It could also be led by a dedicated CAIO (Chief AI Officer).”
Ng also highlights the current war for AI talent, and the difficulty in hiring people with the required skills. Part of the solution, he says, is to utilise the recent boom in digital learning. Coursera, a platform co-founded by Andrew Ng, being one example.
Andrew Ng’s Deeplearning.ai recently announced “AI for Everyone”, a non-technical course, coming to Coursera in early 2019, that will help participants understand technologies like machine learning and deep learning, and spot opportunities to apply AI to problems in their own organisations.
Delay AI strategy-making
Many companies see developing an AI strategy as a natural first step when it comes to adopting the technology. However, Ng recommends waiting until your company has had some experience with AI.
When you do come to outlining your AI strategy, you should then look to create a advantage specific to your industry sector, and become an AI leader in your particular niche.
AI can also be employed to create network effects and platform advantages, says Ng:
Platforms with network effects are highly defensible businesses. They often have a natural ‘winner takes all’ dynamic that forces companies to either grow fast or die.
“If AI allows you to acquire users faster than your competitors, it could be leveraged into building a moat that is defensible through platform dynamics. More broadly, you can also use AI as a key component of low cost strategy, high value, or other business strategies.”
Communication is key
With the sweeping changes AI can introduce to a company, the way those changes are communicated is key, both internally and externally.
This includes conveying the value AI is adding, how these capabilities are developing within your business, and approaching adoption with your employees in mind. The playbook explains:
“Because AI today is still poorly understood and Artificial General Intelligence specifically has been over-hyped, there is fear, uncertainty and doubt. Many employees are also concerned about their jobs being automated by AI, though this varies widely by culture (for example, this fear appears much more in the US than in Japan).
Clear internal communications both to explain AI and to address such employees’ concerns will reduce any internal reluctance to adopt AI.
Internet of Business says
While Andrew Ng’s AI Transformation Playbook is aimed primarily at companies with significant capital to throw behind their AI efforts, its advice is largely scalable.
Smaller business may struggle to carry out AI projects in-house, but the central message for approaching AI transformation remains the same, and is well summarised by Ng’s historical note. During the rise of the internet many companies made the mistake of believing that tacking a website onto the side of their business made them an internet company.
The same trap exists in the AI era. Adopting deep learning technology does not make you an AI company.
“For your company to become great at AI, you will have to organize your company to do the things that AI lets you do really well,” says Ng.
If a company is serious about maximising the potential of AI in their organisation, the technology must inform their entire business strategy, the products they sell and how they sell them, how they are formed, hiring and training, and communication.
The internet left no aspect of the business world untouched. AI’s influence will be just as pervasive.