Application enablement in an AI world
One of the key routes to digitizing businesses is securely deploying applications at pace and in response to immediate customer needs. Application enablement can help achieve this by enabling organizations to deploy services and solutions with high levels of security, reliability and scalability, all while reducing the risk of disruption to existing IT infrastructure.
This process all comes down to forging key partnerships with cloud-centric telecos with the tools to make that happen, known as application enablement platforms (AEPs). In the age of AI it’s more important than ever to know which platforms and providers are best geared to offer the benefits that the latest AI services are guaranteed to reap. This technology is fast-becoming the most impactful for industries across the entire global economy and intelligent enterprises of the future will be those that take advantage of it in all facets, including networking operations with AEPs.
What is application enablement?
Historically, telecom providers have focused on the network itself, with the key priority being the quality of service in the context of availability, quality, and reliability of connections. With the shift to greater web-facing capabilities and customers expecting much higher bandwidth, as well as the expansion of internet-facing devices, attention has turned to AEPs.
AEPs provide a comprehensive suite of tools and services that allow businesses, in partnership with providers, to develop, deploy, and manage IT applications at pace across networks. Usually based on the software as a service (SaaS) model, they comprise components including device management, connectivity and data analytics, as well as interface design and workflow management.
Together, these elements combine to accelerate the development and deployment of applications. This way, businesses can avoid having to dedicate massive amounts of time and resources into building the appropriate infrastructure required to power the building and deployment of an application. They can also deploy it much quicker than they would otherwise have done.
This is all based on a serverless infrastructure, on which is built authentication, object storage service, databases, middleware, and more. Layered upon this infrastructure is a cloud application engine, which serves as an app orchestration model. This infrastructure allows businesses to tap into audio and video functions, data processing, IoT, AI apps, web apps, mobile apps, and so on.
Some of the core benefits of buying into the application enablement model are freedom from the stranglehold of operations and maintenance costs, much faster rollout for applications, transitioning from weeks into days, and scaling in milliseconds.
How AI fuels application enablement
The rise of AI has taken many forms, ranging from machine learning models to large language models, but in terms of application enablement, it stands to support the aims of enterprises by vastly increasing productivity and improving outcomes. Platforms that integrate AI offer additional functionality to boost intelligent network capabilities, including increasing computing potential while overcoming bottlenecks in energy efficiency or computing power. There are also autonomous generative networks that can dynamically self-optimize and perform operations and maintenance autonomously based on real-time service needs.
An intelligent distributed computing infrastructure with AI-enabled application enablement also leads to a lower latency and much higher bandwidth, offering computing and network convergence services to end-users. AI agents can process multi-modal inputs, including images, gestures, and voice, to facilitate a closed-loop of service tasks. They can also offer more personalized experiences with agents dynamically scheduling network resources based on user need. They can finally also resolve complaints and respond to alerts with the use of natural language processing and AI inference.
The AI engines found in some telecom providers’ suites represent a massive transition away from legacy processes and towards an AI-powered regime of network management and rapid application development. Enterprises need to consider, however, how best to utlitize these new tools and whether integrating them into the development cycle through an AEP ties in with core business objectives.
Application enablement in 2025 and beyond
Industries across the economy are tapping into application enablement to build new services and solutions for customers, and deploy these at pace. These systems can be particularly beneficial to industrial organizations – including companies in sectors like oil and gas, energy, transportation, and chemicals – but they also have uses in public utilities, the public sector, finance, and even retail businesses.
Some specific uses of AEPs include predictive maintenance – using platforms to analyze data and create solutions that can predict when equipment will need maintenance – or in remote asset monitoring, where companies can monitor industrial equipment from a distance and identify issues faster.
By tapping into new and emerging solutions that integrate advanced AI functionality, enterprises can finally realize an array of benefits including faster deployment, lower costs, improved security, and high scalability. If businesses analyze their needs and assess all the potential integration challenges in adopting application enablement solutions, they stand to benefit tremendously by rapidly responding to customer needs. This is all the more possible if they take advantage of new AI functionality, like autonomous agents, to optimize network resources and fuel greater efficiencies.
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