The businesses of today are going through a tremendous digital transformation lead by artificial intelligence (AI) more than any other technology. AI arguably has been the most exciting and ambitious proposition out there for businesses and researchers alike. With IDC forecasting the AI market’s worldwide revenue crossing $300 billion by 2024 with a five-year CAGR at 17.1 per cent, the future certainly looks bright. Though COVID-19 has slowed market pace; the work from home scenario will further catalyze AI’s adoption.
As per the 2019 Mckinsey Global Survey, there has been an approximate 25 per cent year-on-year increase in the use of AI in business operations. Also, a significant number of respondents have agreed on witnessing increased revenue in the AI applied areas of business and 44 per cent believe that it helped reduce costs. The AI market is witnessing this spur of growth owing to the adoption of big data and cloud-based applications, growing investment by tech leaders, and wide applicability and benefits of these AI-led solutions. Similar factors have worked positively in the increased usage of BI tools.
In 2019, the software category contributed 39 per cent to the AI global revenue. Companies are now discovering the historical data mines they hold, collecting new data from various sources including IoT devices, and looking to utilize this via advanced data analytics. The growing need to derive predictive insights from this data has induced the demand for an AI-based analytics platform.
AI helps take the BI game leaps and bounds ahead with machine learning and deep learning. It empowers BI with the ability to analyze data coming from multiple sources, learn from this data in real-time, and provide accurate granular predictive insights for faster business growth. AI always stays one step ahead of humans in terms of analyzing large data sets at scale with speed and accuracy. The influence of AI is simply not limited to analytics but also to data engineering. Data coming from multiple structured, unstructured, and semi-structured sources, needs to be transformed from silos to unified data. AI can accelerate and automate this process creating a single view and saving data analyst’s time and providing much-needed independence for business users.
AI-powered NLP bots take BI altogether to the next level by enabling users to extract insights via voice or chat using any language. For example, these BI bots can easily answer questions like ‘What is the sales forecast for the next two quarters?’ With this, business users can skip any complex query and leave it up to the bots to process the analysis.
It helps drive innovation and overall efficiency in businesses by optimizing resource utilization and automating various processes. Business leaders are now able to make data-driven futuristic strategies with intelligent trend forecasts and actionable insights. From identifying market gaps and business opportunities to streamlining tasks to improve employee productivity, AI-driven analytics can be truly valuable for any business.
Let’s have a closer look at how machine learning is driving success in multiple industries.
Retail
Retail perhaps has the widest utility for machine learning powered BI. With customers interacting and generating data on multiple channels, BI can present a unified view with predictive modeling correlating various data points. It enables retailers to analyze consumer behavior in depth, foresee purchase trends, predict needs, identify at-risk customers, and personalize offerings. Retailers can enhance customer segmentation and targeting, test campaigns, improve conversion rates, and induce customer loyalty. With machine learning, retailers can provide dynamic pricing in real-time by analyzing data like the weather forecast, purchase history, inventory levels, competitor pricing, and more. It does not just forecast sales, but also enhance inventory management and streamline the supply chain by predicting demand and identifying which product will sell faster and which may result in deadstock.
Manufacturing
Manufacturers are utilizing AI-based analytics tools on a day to day basis to optimize every aspect of their business. They are analyzing historic consumption data and other external factors to accurately predict demand and enhance inventory management by producing only the products in demand, based on the season or any other trend. With predictive maintenance, production units can be optimized by forecasting any equipment fault and triggering alerts based on the analysis of available data and save breakdown costs and prevent machine downtime. They can achieve maximum production quality by tracking device efficiency and save losses due to product quality deterioration. Also, with unified analytics, producers can have a single view of the whole operation.
Healthcare
Within healthcare, predictive analytics positively affects everyone right from patients, physicians to administrators. Using ML, high-risk patients can be identified, risk scored for potential health issues, and preventive care can be provided, and readmissions can be avoided. The appointments can also be streamlined by predicting patient utilization patterns and resources can be optimally deployed for a better experience. Also, clinical trials are being accelerated with accurate outcomes predictions and precision medicine development has further eased.
The benefits of AI-powered analytics are not just limited to these sectors but are extremely widespread for all industries. For example, AI enables predictive analysis of public data like social media and provides brands with the opportunity to do sentiment analysis of the audience, whereas financial institutions can predict frauds and prevent them.
It can be easily said that AI with its various underlying technologies is and will keep accelerating businesses. AI is transforming the way businesses are done, customers are shopping and how products are being manufactured and marketed. It may now be a factor of competitive advantage, however, as the technology, businesses, and data grow, AI will become imperative for continuous success.