Earlier, it was predicted that the majority of global businesses would support Enterprise Architecture (EA) as a distinct discipline that is essential to business planning within the next ten years. Today, EA has grown from a support function into an extremely strategic one, accountable for designing an intelligent information architecture that provisions digitalization and innovation. EA continues to progress at a rapid pace as evolving technologies lead to business disruption.
Below are three ways EA leaders can embrace emerging technologies and prove business value in the coming year and beyond.
Design For Intelligence
Traditionally, the EA led strategy implementation activities for the business. However, EA has shifted its emphasis to strategy design. By 2023, 60 percent of EA practices will design intelligence into their business and operating models to back strategy development and execution.
Businesses can use design thinking tactics to act as an internal management consultancy. They can also track and assess emerging technologies and map them back to the business model to recognize how EA can generate opportunities.
Besides, firms can add value to the enterprise through strategic technology incorporation.
Refocus On Information Architecture
The emergence of data, analytics, Artificial Intelligence (AI), and Machine Learning (ML) is swiftly reshaping organizations’ core business models. To keep up with digital business, EA leaders ought to recognize and elevate the significance of data architecture. By 2023, 65 percent of EA programs will refocus on data architecture, making it vital to all digitalization initiatives.
Leverage Intelligent Tools
As the practice of EA progresses, so will its toolset. By 2023, 60 percent of EA tools will be smart. Future EA tools will assist customer experience, ML, product design, the Internet of Things (IoT), and more.
The EA toolkit will be an element of a broader network of tools that the businesses use. It may connect to IT Service Management (ITSM), strategy and planning tools, and portfolio and product management. This feature will be a complex ecosystem of tools, models, and data that raises the worth of AI to help navigate, disclose, and offer additional insights.