The software market: 4 trends in custom enterprise software development

The enterprise segment dominates the global software market, according to Statista, and is expected to reach almost $376 billion by 2028. Here we dive into emerging technologies that custom enterprise software developers use to keep solutions up-to-date and efficient

The continuous growth of the enterprise application market, even in recession periods, is the main evidence that software solutions have become essential for companies’ operational efficiency and profitability. However, due to their central role, enterprise solutions should be adapted to the evolving needs of organizations and technology market trends.

AI and generative AI

Generative AI represents one of the most dynamic trends in enterprise software, revolutionizing how businesses approach problem-solving and innovation. At the heart of this trend is the ability of AI to generate new content, ideas, or data-based insights that can streamline various administrative processes and customer interactions.

AI-powered natural language processing is also applied to automating and personalising customer interactions by generating human-like responses. In content creation, it empowers marketers to produce varied and engaging material at scale, from email campaigns to social media content.

While there are concerns regarding the quality of the output, it is predicted that in 99% of cases, AI-generated visual content will be indistinguishable from the real one by 2030.

Another significant application of AI is predictive analytics, where generative AI models forecast market trends and consumer behaviour, enabling businesses to make data-driven decisions quickly. AI-driven computer vision solutions can automate inventory tracking, enhance enterprise building security by monitoring suspicious activity, or help automate data entry tasks, processing forms, or identity validation.

Real-life example

Gucci utilizes the Salesforce Einstein tool to streamline customer communication by generating user-friendly, consistent, and editable replies to customer inquiries based on internal data. The solution helps personalize customer interactions and onboard new support agents by educating them on the brand’s voice, history, and products. With the help of Einstein and several more business automation tools, Gucci has already conducted more than four thousand AI interactions and saw a 30% increase in conversions.

RPA

The 2023 world recession pushed businesses to search for cost-effective yet high-performing solutions, leading to the growing adoption of robotic process automation (RPA) technology.

RPA automates simple manual tasks, allowing employees to focus on more strategic and complex problems. Applied for repetitive and time-consuming operations, like payroll, claims or email processing, sales order updates, or inventory management, RPA allows businesses to cut labor costs, increase operational efficiency and accuracy, and improve customer experience.

Like many other technologies, RPA is currently merged with AI to create intelligent process automation solutions. In contrast to traditional rule-based process automation, IPA leverages AI capabilities to manage and automate complex business tasks that require a strategic approach. For instance, an IPA-enabled system can utilize NLP and predictive analytics mechanisms to interpret text and decide how, when, and with whom to share the information it holds.

Real-life example

Deloitte leveraged the capabilities of IBM’s Robotic Process Automation tool to streamline the generation of monthly management reports, travel expense calculations, accounts receivable, and currency exchange rate monitoring. Now, in one hour, an RPA bot completes reports that previously took from five to eight days of manual work, freeing up employees’ time.

Cloud applications

Statista reports that more and more companies are moving away from expensive on-premises enterprise software and that by 2027, over 60% of organizations will have adopted more cost-efficient cloud solutions.

Hosted on a provider’s cloud infrastructure and accessed over the Internet, cloud-based applications offer small and medium-sized businesses quick deployment, minimized upfront expenses, and scalability without needing a large IT team.

Businesses that are building applications from scratch opt for a cloud-native development approach. Since most cloud-native applications leverage microservices architectures and CI/CD practices, cloud-native applications can be quickly deployed and regularly updated. Designed to run in the cloud environment, applications offer easy scaling, resiliency, and efficient resource utilization, which makes them ideal for dynamic businesses in competitive markets.

Real-life example

Airbnb’s monolithic architecture hindered the company’s growth and ability to introduce new features. So, Airbnb decided to break down the existing architecture into microservices and adopt cloud-native technology to its platform. This allowed Airbnb to increase its deployment frequency and developer productivity, making its services more reliable.

Edge computing software

About 83% of C-suite executives consider edge computing essential for enterprises to remain competitive in the future. Edge computing relies on cloud computing capabilities and brings computation and data storage closer to where data is produced and mainly needed. Also, due to local data processing, edge computing helps improve data privacy and security, as well as network reliability and resiliency.

Despite several concerns regarding the complexity of edge device management, edge computing, especially when coupled with AI and 5G, is becoming a critical component of modern enterprise solutions, particularly those relying on real-time and near-real-time processing.

Real-life example

As part of a broader strategy to integrate technology into its business model, Walmart plans to turn its superstores into edge computing centers by implementing edge computing to handle the vast amount of data generated by IoT devices like smart shelves and inventory tracking systems. Processing data locally allows for real-time insight generation and decision-making, such as restocking shelves and efficiently managing inventory.

Wrapping up: Understanding software market trends

Most modern technology reports prove that to remain competitive, companies should keep up with technology trends like AI, RPA, cloud, or edge computing that drive innovation and make business processes efficient. Still, the very technologies that promise a competitive edge can also introduce potential risks such as data breaches, operational failures, or compliance issues.

That is why, as companies embark on this transformational journey, they need detailed technology transformation strategies that they can create themselves or with the help of third-party consultants.