Demand Grows for Intelligent Applications Powered by AI

Intelligent applications are augmented with artificial intelligence (AI) and infused with data from transactions and external sources. As seen with generative AI (GenAI), they learn from their interactions, improving autonomous responses over time and potentially transforming the experience of customers, users, product owners, architects and developers. And intelligent apps extend far beyond GenAI.

1. Intelligent decision making enables a systematic connection between analytics and continuous, contextual and connected decision making.

2. Adaptive experiences, like chatbots and natural language interfaces, respond to user needs.

3. Process augmentation and transformation increases automation and dynamic business transformation, unlike traditional business information apps.

• Automation: Property insurance apps that monitor weather, satellite and other data could automatically file a claim when predetermined anomalies, such as rising floodwaters, occur. Others could provide discounts to certain policyholder segments after sustained periods of reduced risk.

• Augmentation: An application that grants credits via dynamic pricing models driven by machine learning and contextual understanding of supply and demand.

• Adaptiveness: An HR employee self-management application that offers shortcuts based on what that user and their peers use most or at certain times of year, such as for compliance training and performance review updates.

• More technology providers are adding “intelligence” into applications, versus yet another function or feature, to establish competitive differentiation and drive uptake.

• Declining cost to create intelligent applications and services means more technology providers, including independent software vendors (ISVs), are entering the market. 

• Rising expectations of business value, spurred in part by the hype over GenAI, are boosting executives’ confidence in AI-enhanced solutions of all kinds.

• Identify the most impactful use cases by selecting well-known, hard-to-solve challenges across core processes and within industries and segments.

• Construct a strategic decision model to determine when your organization will build capabilities, acquire the appropriate technology company or partner with leading providers.

• Investigate revenue potential by quantifying the potential value and unique outcomes possible from within your customer base.