Artificial intelligence is an essential thing for companies looking to automate processes, reduce the cost of operation, or fuel innovation. However, successful AI adoption requires clear strategies and a lot of effort. Many companies are rushing to adopt artificial intelligence, but the path to deployment isn’t always smooth.
Andrew Ng, associate professor at Stanford University, and one of the most recognizable names in the machine learning community has launched a company called Landing.ai to bring AI to the manufacturing industry. Today, as part of the company’s initiative, he announced the launch of the “AI Transformation Playbook” an authoritative guide for business leaders looking to create AI-first companies.
As he mentions in the blog post, the playbook contains lessons drawn from his experience leading Google Brain and Baidu’s AI Group. According to Andrew, this playbook can serve as support for any company. He says that “many of the biggest untapped opportunities in AI lie outside the software industry” and expects this playbook to help all kinds of companies.
Divided into five parts, each describing one step of the AI transformation, the “AI Transformation Playbook” provides a roadmap for any company to transform into a great AI company. According to the playbook, the AI journey starts with smaller pilot projects to gain momentum. Here are the five steps or rules to follow for a successful AI transformation:
1. Execute pilot projects to gain momentum
2. Build an in-house AI team
3. Provide broad AI training
4. Develop an AI strategy
5. Internal and external communications
“Building strong AI capabilities for your company will require a long-term investment, but it is feasible for most enterprises. “ – says Andrew Ng, encouraging companies to take a step forward and invest in the AI transformation. Because of this, he mentioned that the playbook is primarily intended for larger enterprises (with a market cap from $500M to $500B).
The AI Transformation Playbook is available and can be downloaded as pdf here.
