The State of A.I. Adoption: Here Are The 6 Top Use Cases for A.I. in 20223 min readReading Time: 3 minutes
84% of businesses say A.I. will enable them to obtain or sustain a competitive advantage in 2022. And organizations will shift from short-term solutions to long-term innovation in the coming year. With that, here are the top use cases for A.I.:
1. Data Cataloging & Management
Organizations spend 70% of their time looking for data and only 30% of the time utilizing it.
Data management is the singular most important business intelligence trend of 2022. As businesses work towards creating a strong insights-driven culture, teams must understand that the models they build are only as good as the data it is trained on.
With A.I., businesses can create robust data catalogs that are organizable for queries, simplify compliance and governance efforts. And eventually, build their own models.
2. Customer Experience Management
A.I. can increase customer satisfaction scores by up to 300%
Organizations are turning to AI-powered customer experience management suites to synchronize processes across the value chain. A.I. can help enrich customer profiles and seamlessly apply real-time insights across the conversion funnel. Thus, maximizing impact.
3. Workflow Automation
80% of executives expect their companies to adopt AI-powered intelligent automation by 2027.
Businesses are increasingly investing in process automation to create hyper-efficient systems that can execute and augment repetitive tasks. This includes tasks such as moderating images and textual content, verifying identity, and processing claims. In fact, MercadoLibre, an online marketplace, was able to reduce go-to-market timelines by 50% and monetize products faster after automating the image quality assessment process with A.I.
By integrating A.I. into their workflows, teams can streamline processes, uncover inefficiencies, and deliver quicker conversion down the value chain.
90% of business leaders view personalization as critically important to their business strategies.
Enhanced customer expectations and the maturity of A.I. capabilities are causing organizations to prioritize personalization at scale in the coming year. Businesses are breaking down silos and unifying their customer data. The unified data enables them to target the right cohort of users with the right content for maximum engagement and conversion.
For instance, media houses with large content repositories can leverage personalization to improve engagement. With personalization, they can deliver the most relevant piece of content to every user at the right time.
5. Demand Forecasting & Optimization
AI-powered forecasting can reduce errors by 30-50% in supply chain networks.
Organizations are integrating A.I. into their systems to predict the demand for products. This is based on historical data and real-time user profiles. The A.I. models enable teams to identify trends, capture signals for demand fluctuation, and create accurate demand forecasts.
As a result, businesses can leverage these insights to make informed decisions. Apart from this, they can also efficiently meet demand, optimize operations and maximize profitability.
6. Churn Prevention
60% of organizations currently adopt A.I. for customer retention improvement.
It is 6X more expensive to win a new customer than retaining an existing one. Today, businesses are leveraging churn prediction models to examine every customer interaction in the conversion funnel. These models enable them to discern the precise indicators of churn.