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Product Management

What is your AI strategy?

Having seen data science and AI use cases in various industries in the past one and half year, I can say that Andrew has a great pragmatic advise for all the companies going AI or starting to consider the AI impact.

  1. Start small : Have a big vision but start small. As with any NEW technology out there, its is important to understand the technology and what it can do to your business. Choose a small AI project that is demonstrable within 6-9 months. This helps engineers, PMs and business teams to understand the AI terminology, what is possible, what is not possible and how to transform themselves. 
  2. Data acquisition : Having a great model doesn’t matter if there is no good data set to start with. If the data is distributed and not easily retrievable, have a data strategy to train your model and get real-time data. This means, management commitment is necessary. 
  3. Bias : Start thinking about the bias the day one. With so many recent examples on the data bias, start thinking about comprehensive data set, incorporate data audits and oversight committee. 
  4. Explainability : The biggest hindrance to AI adoption in some of the mission critical verticals/use cases is the ability for an AI outcome to explain. e.g. When a radiologist reviews an X-Ray, its easy for them to explain the result. The current AI systems are still developing to explain the outcomes in a way for doctors, insurance companies and patients to accept the system. 
  5. Vertical Industry Impact : Be it Retail, Manufacturing, Automotive, Government or others, most industry segments are already making use of the ML. Most importantly, companies are re-engineering their processes to take advantage of the ML and DS. 

As you start thinking about AI projects in your organization, make sure to get yourself familiar with the AI technology (Data, Models, ML, DS, NN, TensorFlow, Streaming Engines, …). Before expecting the technology to deliver value, understand the current business challenges, business process workflows and technical capabilities to set realistic expectations on your teams.

I highly recommend the recent AI for Everyone course if you haven’t already taken. Provides a great introduction to leaders – especially helps to get started with conversation in the right direction.

Happy AI. Make a good impact on humanity.

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About author

Suresh Krishna is a Product Management Leader at Oracle and a Startup Advisor at various start-ups.
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