The Role of AI in the Future of Business Intelligence

Today’s businesses leverage the power of AI in many ways, from call centers deploying AI-based chatbots to banks using deep learning to analyze countless data points in seconds and detect fraud.

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Illustration: © IoT For All

Factories deploy AI to automate complex physical tasks requiring adaptability and agility. Marketers use AI to generate individualized recommendations and automatic order fulfillment. The list is virtually infinite. A host of services taken for granted today, from credit card fraud detection to email spam filters to predictive traffic alerts to personalized reminders, wouldn’t be possible without AI.

One area where AI is used extensively is business intelligence. Enterprises leverage deep learning algorithms to spot behavioral patterns likely to lead to sales, use cues from IoT sensors for predictive maintenance and inventory optimization and do more.

However, what businesses do now is just the tip of the iceberg of possibilities.

AI Enables Live Decision Making

With the proliferation of data, several businesses run the risk of data overload. The unprecedented growth of Big Data and the obsession to analyze such data can easily gag the core operations of the business. AI-powered business intelligence software enables enterprises to break down data into manageable insights, and make sense of Big Data.

AI also has the potential to change the dynamics of analytics. Conventional data analytics focused on descriptive analytics or analyzing data to report what happened. The present generation of AI-enabled analytics tools enable predictive analytics or using data to decipher future insights. This, however, is based on “best guesses” with behavioral and historical data used to guess probabilities.

Prescriptive analytics is all set to take over in the near future. AI-powered prescriptive analytics tools would scour through vast swathes of data and enable users to prescribe various possible actions and advise viable solutions. Prescriptive analytics not just predicts, but offers sound advice as well, and explains why things will happen the way it will or does.

The shift from reactive predictive analytics to proactive prescriptive analytics improves the potency and relevance of business decisions. Live, real-time insights enable enterprises to make the best use of their operational data, making decisions based on what’s currently happening rather than based on what happened in the past. Much of the recommendations can be automated as well, with the best course of action determined by the intelligent machine based on the available inputs.

AI Brings Voice and Facial Recognition to the Centerstage

AI-powered voice-activated digital personal assistants have already enamored millennials in a big way.  The spurt in deep learning-powered applications such as speech recognition interfaces, its widespread adoption by businesses and the tremendous popularity of digital voice assistants such as Apple Siri, Amazon Alexa and Google Assistant are portents of things to come. Voice will replace the keyboard and touch interfaces as the default norm for individuals to engage with brands, cutting across industries.

Likewise, matured facial recognition technology is all set to make big strides from present levels, in the near future. AI-powered facial recognition technology may just make the highly irritating password obsolete.

AI Powers Hyper-Personalization

AI-based intelligence learns from experience, becoming better with each experience or transaction. With the next prescribed decision automatically better than the previous one, the stage where the AI model is highly matured and covers all eventualities isn’t far off.

It gets better. AI-powered systems of the future could automatically decipher the user and even the users’ emotions from the soon-to-be-commonplace voice commands, to make highly accurate recommendations or engage with them at a truly personal level. The next wave of AI-powered assistants will be capable of analyzing huge troves of data contextually, in real-time, to grasp customers’ need and priorities quickly, and do what’s required. AI is all set to make hyper-personalization the default norm, rather than a premium service as it is now.

At a macro level, enterprises would be able to collate information from various data points and make real-time live sentiment analysis. For example, an enterprise could collect live data from the customer’s engagement with the company, their social media posts and other data, to understand their thought process and emotional reaction about a product and make real-time interventions to either reinforce or change such perceptions.

AI to Encroach Into More Domains

AI is already helping industries such as financial services, healthcare, securities trading and life sciences in a big way. For instance, AI is taking over the role of the clinical assistant, helping physicians make faster and more reliable diagnoses. Such instances will become commonplace to the extent human intervention will become rare.

However, as of now, machines traditionally don’t do well when it comes to abstract tasks involving human capabilities such as empathy, creativity, judgment, inspiration and leadership. Two critical management functions, innovation and managing people, are still almost entirely with humans. This could change in the future thanks to AI systems becoming more mature. Presently, algorithms may suffer from some amount of bias or subjectivity, considering the algorithms are designed by humans after all. As training data gets more mature, such biases and negative effects will be quickly eradicated.

Artificial intelligence is here to stay. AI has the potential to transform how top executives make decisions, how marketers engage with customers, how enterprises compete with each other and how they develop overall to become more potent and powerful. The future of business intelligence will surely be driven by AI-enabled systems.