- Graham Wilson
Can you easily use AI to make better decisions?
Updated: May 5, 2021
When it comes to business decision-making, an increasing number of companies are adopting a “data-driven” approach. However, data is only king when it’s utilised the right way. It’s a common misconception that while data can improve decision-making, we need to entwine it with a human process that can evaluate the data.
Cue machine learning and artificial intelligence. AI refers to a machine’s ability to replicate the cognitive functions of humans, including learning from data and solving problems. Utilising AI in business decision-making can not only help you obtain better, faster, and more accurate solutions but can also significantly reduce decision fatigue. According to a survey conducted by Tech Pro Research, only 24% of businesses currently implement or have plans to implement AI to drive their decisions. But those already doing it have realised significant improvements in their decision-making process.
PwC put together massive amounts of financial data from the US Census Bureau to create a large-scale model of US consumers’ financial behavior. This model helps companies providing financial services better understand their potential customers and anticipate customer behavior by simulating “future selves”. The result? Business decisions can be validated within seconds in real-time.
AI can be exceptionally powerful when it comes to driving marketing decisions. A good grasp of the ever-changing consumer behavior is of the essence when it comes to making those—both in the short and the long term. Let’s take CRM, for instance. An organisation utilising AI can identify an individual consumer’s lifetime value and source and process immense amounts of data within minutes to drive long-term business decisions.
AI can be especially helpful when it comes to recommendations. Recommender system (engine) is a technology that recommends certain products or services to users based on explicit or implicit feedback. This can significantly reduce bounce rate and ensure your customers receive more targeted content.
Algorithms you design within AI learn from data. The first step is ensuring you have the right data. While AI isn’t as bias-prone as a human observer or processor, biased data can still skew the results. Using biased data might result in the AI “learning” and subsequently finding relationships that are not really there.
Cleaning your data before you feed it to the AI or ML (Machine Learning) algorithm is essential to its success as well. There are instances in which the data might be incomplete or contain irrelevant information. If dealing with sensitive or personal consumer data, you might need to anonymise certain attributes before the data is ready for AI processing.
When you’re confident you have the right, cleaned data, the next step is ensuring it’s in the right format—this means structured, in a useful scale and sometimes with specific features the ML algorithm might need. Implementing a pre-processing pipeline in your business infrastructure can save you a significant amount of time, ensuring you yield the right insights from AI by fulfilling the first condition: giving it the right data to drive smart, accurate, and tailored business decisions.
So in short the answer is: yes, AI can absolutely help you make better decisions when it comes to running your business. The key is developing systems that can deal with the massive amounts of data generated by human behavior, but also ensuring you feed your machine learning algorithm the right type of data.