The simplest route to an AI-driven enterprise

The simplest way to discover your artificial intelligence (AI) potential is to analyze areas of the business with the largest intelligence gaps. Prioritize areas by their potential to improve the company. Then, begin filling the gaps with AI.

The simplest way to build an AI application is to follow the scientific method: Form a hypothesis; model the problem domain; build, train and test the algorithm; predict the business impact; and monitor the results. Decide on the minimum functionality you need to deliver business value. Gather just enough data to model the business domain and run an experiment.

Treat AI platforms as commodities. Design the AI applications so that platform components can be plugged into and swapped out of the existing legacy infrastructure. Choose technologies capable of running AI as widely available, reliable services.

Bias, ethics and fairness are big risk factors in AI. The simplest way of protecting against these risks is to check the results. Part of a standard checklist for protecting against ethical violations with AI is to build AI forensics tools, use those tools to profile the algorithm, use the profile to anticipate behavior, and discuss the anticipated behavior with a diverse risk-mitigation team. 

Remember that the nature of applying AI is experimental. You won’t know ahead of time which technologies and applications will be the most useful. Avoid biting off large AI projects all at once. Instead, run small experiments that make it easy for you to learn from mistakes. Create a portfolio of hypotheses about what you think might make a real difference. Test those hypotheses using small experiments. Learn and adjust as you go.

Continue reading the position paper, Embed advanced analytics into every aspect of your digital business.