Executive Summary: ISG Provider Lens™ Next-Gen ADM Solutions - Global 2023
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Adoption increases for low-code/no-code development platforms and AI across various use cases
About two-thirds of the application development paradigm is expected to be associated with low-code/no-code (LCNC) development platforms. These platforms are not restricted to internal development purposes by enterprise users; service providers also use them for application development within their firms and clients. Professional developers at enterprises and service providers utilize LCNC platforms for application development that may not require efforts to develop applications from scratch. Integrating these platforms for add-on app development services has allowed users to deliver applications at a reduced time to market. The ease of use of these platforms has also allowed an exponential increase of citizen developers with minimal coding knowledge to build apps using simple drag-and-drop techniques. The ease, time to market and flexibility in integrating the platforms with existing applications has led to the democratization of the application development domain.
Depending upon the complexity, the time taken to develop an application varies. A basic application with limited functionality and straightforward requirements can be developed and deployed within a few hours or minutes. This could include small utility apps or PoC prototypes that can automatically evolve into more sophisticated versions. Some more complex applications involving business process improvements include developing and deploying applications for specific business processes, such as inventory management or order processing, and this may take a few days to a couple of weeks. These applications typically involve moderate complexity and integrations with existing systems. Much more complex applications, such as e-commerce platforms or customer service portals designed to enhance customer journeys, can take several weeks to months for development and deployment. These applications often require complex workflows, integrations with multiple systems and user interface customization. The IT teams handle the data integrity and security aspects to ensure the users access the right data set for building these applications. Improving processes and data are interlinked within an organization. Some LCNC platforms allow building apps that drive agility and alignment across the organizations.
AI has primarily driven LCNC platform adoption. AI makes it easier for developers to utilize prebuilt frameworks and code blocks. Some vendors offer easily customizable, prebuilt components, templates and prompts for developing desired applications. ISG sees this trend increasing with vendors developing AI-based platforms, enabling easier application building. Some LCNC testing platforms use AI to build knowledge maps across the IT landscape for multiple use cases, including application management. There is also increased integration with generative AI (especially ChatGPT) to support NLP-driven assisted development across various facets, from planning to code generation to quality assurance. The ease of building applications using AI-based services and platforms has driven an exponential increase of users developing applications using AI or AI-based ready templates. This trend is expected to grow multifold across multiple use cases.
Data integration has been an important area of concern while developing applications through LCNC platforms. With multiple users in an organization accessing organizational data for building applications, it becomes imperative for firms to have a data management strategy. The LCNC development platforms allow the implementation of these accesses while configuring the development platform for the end user. Typically, the IT team within the enterprise gatekeeps these access controls to data, allowing specific data on which the citizen or professional developer would intend to develop an application. With data being one of the major aspects, the ability to join multiple legacy systems through a virtualized data layer will be crucial in creating the functionality that users need to develop the applications using the platform. LCNC platforms build access controls interwoven with this data fabric to allow data management across the firm with multiple users using the same development platform.
Multiple use cases have emerged over the last year for LCNC development platforms. Developing applications, monitoring and management across various use cases have been most adopted by enterprises and service providers. Process optimization has also undergone LCNC platform adoption, with some apps integrated with the existing automation initiatives to deliver process improvements. Improving customer journeys and building automated reporting tools are other use cases widely adopted for LCNC development platforms. Using AI and analytics to enhance platform adoption is an area that is expanding. With the built-in analytics engine, users can also utilize features such as conversational analytics, automated insights, smart interpretations and predictive analytics that directly feed into improving the use cases across the enterprise.
With flexible infrastructure and ease of deploying the platforms, there is an evolution in IT models within organizations to democratize software adoption and development at scale. Many organizations are testing central IT functions with federated local champions to support the changes reflected in the industry.
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