Focus Question: How is Artificial Intelligence (AI) supporting/affecting the Application Architecture within Enterprise Systems?
The expansion of artificial intelligence (AI) in today’s technology awakens a new era of possibilities for enterprise architecture; however, with that comes caution. Automating routine tasks, enabling predictive analytics, enhancing customer experience, and enabling intelligent decision-making can bring efficiency and lower costs to organizations. As noted by researcher Mehran Rowshan, with organizations, “decisions to manufacture, distribute, price, promote… [are] carried out in information black holes often powered by gut instinct, static rules or, in the best of circumstances, through historical analysis.” AI can transform this through precise analysis by evaluating historical trends and future predictions, helping mitigate business risk and reduce lost opportunities.
The challenge Enterprise Architects face is dealing with the constant change and adaptation of new technologies within enterprise systems. Most often enterprise architecture teams see to identify certain applications that will provide overlapping capabilities to eliminate duplicative capabilities, while improving business processes and enhancing employee productivity. Utilizing the right applications across the organization can also establish governance and standardization to support business strategies and outcomes. When making such decisions within an organization, architects must consider several factors such as cost, productivity, security, and efficiency to adapt their business models. However, AI is changing how we can utilize and integrate applications within enterprise systems today.
AI can manage multiple application layer components in enterprise technology, but for this blog, we will highlight the integration of application development and maintenance. Some examples of things AI can help with is:
- AI-powered coding assistants can help developers write cleaner and more efficient code by analyzing code and providing suggestions.
- AI can help automate the testing process. This would speed up the testing phase, improve test coverage and enhance overall software quality.
- AI can help with quick bug detection, vulnerability assessment and troubleshooting for developers.
Overall, AI can streamline and enhance application development and maintenance processes within enterprise architecture.
Figure 1: Architecture Layers. (n.d.). Enterprise Architecture
References:
Architecture Layers. (n.d.). Enterprise Architecture. https://enterprisearchitecture.harvard.edu/domains
Brown, A. (2021, November 9). How Enterprise AI Architecture Is Transforming Every Industry From Commerce To Wealth Management, And Beyond. Forbes. https://www.forbes.com/sites/anniebrown/2021/11/08/how-enterprise-ai-architecture-is-transforming-every-industry-from-commerce-to-wealth-management-and-beyond/?sh=1d6f48cc782d
Settle, M. (2023, May 20). Managing enterprise application architectures in 2020: the game has changed! CIO. https://www.cio.com/article/219765/managing-enterprise-application-architectures-in-2020-the-game-has-changed.html
Top 3 Trends in Application Architecture That Enable Digital Business. (2019, October). Gartner. https://www.gartner.com/document/3970797?ref=d-linkShare