Information security and fraud detection will continue to be the key use cases leveraging AI. Another example of mitigating risk is that insurance companies will leverage ML to explore hypothesis-driven scenarios with climate change in addition to developing pricing policies and understanding the impact of catastrophic events.
As AI is used more to automate data pipelines and accelerate the delivery of trusted data, the quality of data feeding into the AI pipelines will be as critical. The quality and consistency of data matters with ML and AI because we are training the models based on that data. The impact of using data with missing attributes, bad data, or duplicate data is exponential as the data models become biased or incorrect, hence impacting our predictions and insights. Businesses will need to develop a coherent data strategy and will increase investments in data quality and governance.
- Data enrichment and location intelligence will bring competitive advantage.
Location is increasingly becoming recognized as a linchpin that can connect data from across an organization and reveal new insights. It’s commonly stated that 80% of all data has a location component. With the explosion of mobile devices and datapoints that collect insights on everything from political and administrative boundaries to consumer behavior, physical buildings, traffic, and weather patterns, geospatial data cannot be overlooked. Location can serve as the cornerstone for enriching data with attributes such as points of interest, drive times, and demographic details fueling additional insights.
For example, climate change has been a key factor in increasing the risk and extent of wildfires globally. Local governments and insurance companies will continue to use location intelligence to understand the risks with severity and the extent of wildfires. Understanding the risks for a property requires an assessment on how far the property is from a fire station, distance from water reservoirs, and the understanding of non-traditional exposure such as the probability of embers raining down on the property.
Location data will also gain momentum in 2022 as customers’ lifestyle habits change. With the impact of COVID-19 and the resulting drastic shift in consumer behavior, companies understand the value of implementing highly relevant and engaging digital experiences for their customers now more than ever before. Businesses need to understand the customer’s entire experience with the products or services they offer, make connections between in-person and virtual touchpoints, and ensure every interaction the customer has with the brand was informed by the correct data. This includes the use of demographic data, mobility data, location, and household data to create a better customer experience—helping businesses to understand trends and deliver more personalized experiences and recommendations.
Data enrichment will be critical for just about every business—whether it is a business opening a new store or a business evaluating commercial real estate through the lens of people returning to offices in 2022. Businesses that make this type of connection will be helping to reshape our new post-pandemic world.
More Informed Decisions
In 2022, our world will not only become increasingly data-driven, it will also become fueled by better, smarter, and contextualized data. As data ecosystems grow and are bolstered by the insights derived from enhanced AI/ML capabilities, we’ll see the businesses that are investing in these technologies making more informed decisions and surpassing their competitors at an exponential rate.