Areas where executives can use AI capabilities in business include pattern recognition, prediction, image recognition, cognitive search and natural language.
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How AI Can Help
MANILA, 16 March 2018 — Business intelligence and analytics firm SAS wants executives to integrate artificial intelligence into their analytical strategy.
In particular, SAS cites some areas where executives can use AI capabilities in a business context. Specifically, they include pattern recognition, prediction and classification, image recognition, and cognitive search and natural language functions.
For pattern recognition, businesses will be able to understand typical trends or behaviors for customer financial transactions. Moreover, with AI, businesses can spot anomalies in an account’s spending data to identify potentially fraudulent behavior.
As for prediction, businesses can capture short- and long-term variability in data to improve forecasting of energy consumption. For classification, business can examine animal track images and group them by species type to support wildlife conservation efforts.
Healthcare businesses can apply AI in image recognition, determining if nodes on a raw CT scan are malignant or benign.
Business AI: Speech to Text
For cognitive search, businesses can offer personalized recommendations to their online shoppers. They can then match shopper interests with other customers purchasing similar items.
Using speech-to-text AI functions, businesses can transcribe customer call center voice messages to verbal text. This is to easily detect customer sentiment for further analysis.
Finally, using natural language interaction features, business can command a software application to generate a report on sales revenue predictions.
AI Application in Industries
For banks, automated financial advisers provide fraud detection, credit and risk analysis, and market recommendations. For government or federal contractors, they use AI in sensor fusion for smart cities, or facial recognition for law enforcement.
As for health and life sciences industries, they can process data from past case notes, biomedical imaging, and health monitors. Hence, the aim is to advance the use of predictive diagnostics and improve response times in patient care.
For manufacturing and energy companies, they can apply AI in optimizing the supply chain, automated detecting of defects during production, and energy forecasting.
And for communications and retail businesses, AI can improve chat bot functionality, personalize shopping experiences, and customize recommendations.
To be effective, the AI strategy must feed into the larger business strategy, considering the people-process-technology convergence.
With humans as the most important organizational resource, businesses must invest in data scientists, systems engineers, and solution architects, among others.