Intelligent applications are software applications with behaviors and outcomes achieved through learning, using one or more artificial intelligence (AI) techniques. These applications are applicable in any domain, including core business applications such as customer relationship management (CRM), HR and supply chain management. The addition of AI-based techniques in intelligent applications enables new features through probabilistic and generative techniques that AI allows for.
Product leaders must focus on implementing intelligent capabilities to compete against the coming wave of emerging offerings. They can learn, adapt, generate new ideas and outcomes and increase automated and dynamic decision making. The impact of intelligent applications will disrupt established software markets and business models.
What are the benefits of AI making applications more intelligent
Intelligent decision making enables a systematic connection between analytics and continuous, contextual and connected decision making. Adaptive experiences, like chatbots and natural language interfaces, respond to user needs. Process augmentation and transformation increases automation and dynamic business transformation, unlike traditional business information apps.
Why intelligent applications continue to be a trend
Intelligent applications continue to be a top trend for tech providers because the emergence of intelligent applications will remain highly relevant over the next three years. Intelligent applications should be a strategic and high-priority approach for tech providers in the next two to three years for the following two reasons:
- The declining costs to create intelligent applications and services
- The recognition of business value from technology-driven disruption by intelligent applications
The increasing popularity of intelligent applications drives opportunities for product leaders
Innovation, cost and value drive the increasing popularity of intelligence applications. 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 generative AI (GenAI), are boosting executives’ confidence in AI-enhanced solutions of all kinds.
Overall, GenAI-based techniques are increasingly emerging in intelligent applications. What distinguishes the capabilities of applications using GenAI techniques is that the outcomes represent text, video and analyses that typically require extensive human resources with expertise and industry-specific insight. Generally, applications that offer GenAI capabilities are not for the replacement of headcount but rather the augmentation and improvement of human resources.
Product leaders should 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.
Jim Hare is a Distinguished VP Analyst at Gartner where he covers AI, data science and analytics and advises tech providers on how to best adapt their product and go-to-market strategy to emerging technologies and trends.
