How are AI and machine learning changing risk management?
Business owners across the world were trained through experience how to identify risk to their operation. Whether a competitor released a new product, the economy trended in an opposite direction, or a natural disaster/pandemic occured, leaders used experience and training to prepare their company for the future. (Also read: 10 Ways to Prepare Your Business IT For a Natural Disaster.)
Well, now you can quantify business risk through AI. Almost every scenario a business might encounter could effectively be mapped out though a model to inform the leader of outcomes. This might guide the leader to “use the data” to interpret the answer -- then steer the ship in the direction and row. But is risk really that calculated?
Humans build AI systems; and humans are flawed. If an algorithm was built to detect when a deer crossed the road, then trained on what a deer looks like, then tested against real deer, what happens when an albino deer jumps across the road? The model has never seen this and might think it’s a car or a bunny.
The point is, managing risk by AI is similar to outsourcing risk to a consultant. Sure, AI can solve infinitely more scenarios -- but are those scenarios accurate for your specific business?
A successful risk management plan should be developed by the stakeholders of the corporation that will be required to take action on the results. This involves documentation and ingesting specific business rules into the model to enforce the specific results that matter.
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Written by Andrew Amann | CEO and co-founder, NineTwoThree Venture Studio

Andrew Amann is CEO of NineTwoThree Venture Studio, a two-time Inc. 5000 Fastest Growing Company. Andrew and his team have created over 50 products and 14 startups and are the leading mobile dev agency in Boston.
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