Introduction

As enterprises continue their digital transformation journeys, the complexity of managing software supply chains has increased dramatically. Software Bills of Materials (SBOMs) have become critical tools for transparency and security, but their management presents significant challenges. This report explores how open-source low-code platforms and AI application generators can potentially simplify SBOM management while maintaining robust security practices.

Understanding Software Bill of Materials (SBOM)

A Software Bill of Materials (SBOM) is a comprehensive inventory that details all software components used in an application, including source code, libraries, packages, and modules, along with their corresponding version numbers, licenses, and other relevant metadata. The purpose of an SBOM is to ensure transparency and traceability within the software supply chain, allowing organizations to identify and address potential security vulnerabilities and compliance risks.

Modern applications are complex assemblies of third-party software and proprietary code, with as much as 80% of code coming from third-party sources. This complexity makes SBOMs essential for maintaining visibility into the development environment, especially as software supply chains become an expanding attack surface.

SBOMs have gained significant importance following high-profile supply chain attacks like SolarWinds, prompting the US government to mandate their use as an industry-standard solution. Organizations that effectively implement SBOM practices can better manage vulnerabilities, improve compliance, and strengthen their overall supply chain security posture.

Regulatory Requirements and Importance

As of 2025, SBOM generation has become a core development step that teams must complete to build and ship software safely. Regulations across multiple sectors and geographies increasingly require detailed software inventories or SBOMs. These regulatory requirements reflect growing concerns about software supply chain security and the need for greater transparency in software composition.

Challenges in SBOM Management

Creating an SBOM is only the first step in maintaining software security. Organizations face several challenges in managing SBOMs effectively, particularly for large software portfolios:

Complexity of Modern Software Supply Chains

Modern software development involves numerous dependencies, making it difficult to track all components used in applications. As noted by the National Security Agency (NSA), organizations need a comprehensive approach to SBOM management that encompasses integration with other systems, supporting access to data sources, and maintaining a scalable architecture.

Accuracy and Maintenance Challenges

Identifying all software components and keeping track of updates and patches requires a systematic approach. SBOM management involves generating, storing, analyzing, and monitoring SBOM documentation throughout the application lifecycle. An SBOM has little value when “left dormant within the build directory where it was generated”.

Open-Source Low-Code Platforms as a Solution

Low-code platforms offer a potential solution to simplify SBOM management by reducing the amount of custom code that needs to be tracked and secured.

Leading Open-Source Low-Code Platforms

The open-source low-code ecosystem has matured significantly by 2025, offering several robust options:

1. Appsmith: A platform with 35.2k GitHub stars that enables rapid development of internal applications through drag-and-drop widgets and inline JavaScript customization. It supports integration with diverse databases and APIs and provides 256-bit encryption for security.

2. Budibase: Considered the best open-source, low-code app builder, Budibase allows businesses to create applications by merging databases, spreadsheets, and APIs, with on-premise hosting options using Docker and Kubernetes.

3. ToolJet: With 33.7k GitHub stars, ToolJet provides a drag-and-drop interface for building custom internal tools with JavaScript and Python support. It allows developers to reuse React components easily and offers security, scalability, and multi-environment support.

4. Saltcorn: A fast, free, open-source low-code solution enabling users to create web and mobile applications with a drag-and-drop builder.

5. Additional Options: Other notable platforms include Frappe, Corteza, ILLA, Noodl, and Lowcoder.

SBOM Benefits of Low-Code Development

Open-source low-code platforms can simplify SBOM management in several ways:

1. Standardized Components: Low-code platforms typically use standardized libraries and components, reducing the variety of dependencies that need to be tracked.

2. Transparent Supply Chain: Since these platforms are open-source, their components are more transparent and can be more easily included in an SBOM.

3. Reduced Custom Code: By enabling rapid development with less custom code, low-code platforms can potentially reduce the overall complexity of an application’s dependency tree.

AI Application Generators and Their Impact on SBOMs

AI-driven code generation offers another approach to simplifying SBOM management while accelerating development.

Automated Project Setup and Dependency Management

AI code generators can automate project setup, configuration management, and dependency installation, potentially creating more standardized and secure applications. They can:

1. Automate Project Setup: Generate full project scaffolds with pre-configured directory structures for frameworks like React, Next.js, Django, and Express.js.

2. Manage Configurations: Create configuration files like .gitignore, .env templates, and linting rules automatically.

3. Handle Dependencies: Install dependencies automatically based on project type, resolve version conflicts, and detect security vulnerabilities in libraries.

Benefits for SBOM Management

AI-driven code generation and optimization offer several benefits for SBOM management:

1. Pattern Recognition: The ability to automatically identify patterns, dependencies, and best practices in code can significantly improve the quality and efficiency of generated code.

2. Standardization: AI models can analyze large codebases and learn from existing examples to generate code that adheres to industry standards and best practices, ensuring generated code is of high quality.

3. Optimization: Machine learning can optimize code for specific hardware architectures or performance constraints, leading to better overall system performance and resource utilization.

4. Dependency Reduction: AI can potentially help identify and eliminate unnecessary dependencies, reducing the SBOM complexity.

Security Considerations for Citizen Development

While low-code platforms democratize development, they also introduce potential security risks that must be addressed to maintain SBOM integrity.

Risks of Citizen Development

The rise of “citizen developers” – business users creating applications without traditional programming skills – introduces several privacy and security risks:

1. Compliance Issues: Citizen developers may not be aware of regulations like GDPR, HIPAA, and CCPA that require protection of personal data.

2. Data Leakage: Non-technical developers may inadvertently expose sensitive data through misconfigured access controls or by sharing data with unauthorized users.

3. Security Vulnerabilities: Citizen-developed applications may lack proper security measures, making them susceptible to common vulnerabilities like SQL injection, cross-site scripting, and cross-site request forgery.

4. Third-Party Component Risks: Low-code platforms often rely on third-party components whose lineage and security posture are unclear, emphasizing the need for a robust SBOM to understand dependencies.

Mitigation Strategies

Organizations can address these risks while still benefiting from low-code development:

1. Training and Awareness: Require training programs to educate citizen developers about privacy and security best practices.

2. Secure By Design: Involve security professionals to provide guidance and design security into low-code applications from the start.

3. Access Controls: Implement robust access controls and permissions commensurate with data sensitivity and regularly review them.

4. Integration with IAM: Integrate low-code platforms with Identity and Access Management systems, such as implementing Single Sign-On with Active Directory.

5. Centralized Governance: Establish a governance framework to centralize control over citizen-developed applications, including approval processes, version control, and compliance checks.

SBOM Management Best Practices in Low-Code Environments

Implementing effective SBOM management in low-code environments requires a structured approach:

1. Generate SBOMs for All Applications

Organizations should generate an SBOM for every application during the build process. This creates an audit trail that helps identify which components are in specific versions of applications, useful when new vulnerabilities are discovered in older components.

Automating the SBOM creation process ensures every build has a corresponding SBOM for compliance purposes. This is particularly important for low-code applications, where the underlying components may change with platform updates.

2. Properly Store and Manage SBOMs

SBOMs should be stored in a centralized repository like Sonatype SBOM Manager, rather than leaving them in build directories. This provides centralized storage for both internally developed and third-party applications.

Organizations should be cautious about sharing SBOMs publicly, as application composition can contain sensitive information. SBOMs can be run through Software Composition Analysis tools to create a list of vulnerabilities in applications.

3. Integrate with Security and Compliance Tools

By analyzing SBOM data across the organization, teams can identify trends such as repeated use of outdated or end-of-life components. This analysis can drive a smarter Software Composition Analysis (SCA) strategy.

While SCA tools are optimized for active development environments and run against build-time artifacts, SBOMs take software transparency further by allowing organizations to track the evolving security posture of software long after release into production.

4. Address the Full Component Scope

When creating SBOMs for low-code applications, organizations should consider multiple layers of components:

1. Language-level dependencies

2. Dependencies of language dependencies

3. System dependencies

4. The operating system

5. External cloud services

6. Compilers

The FDA guidance suggests including “upstream software dependencies that are required/depended upon by proprietary, purchased/licensed, and open-source software,” which typically means the first four categories.

5. Automate SBOM Generation

Several tools are available to automate SBOM generation, which is especially useful for low-code environments:

1. Commercial options: FOSSA offers a paid version with a free tier that is often sufficient for first submissions and includes vulnerability monitoring.

2. Platform-specific tools: GitHub supports generating SBOMs automatically, and Amazon Inspect can produce SBOMs from EC2 and Lambda instances.

3. Container-specific tools: Syft or Docker Scout can generate SBOMs from container images or filesystems.

4. Integration tools: The Zenity SBOM solution seamlessly integrates with all Low-Code/No-Code development platforms, performing automatic scans of applications and generating comprehensive inventories of all components.

The Role of AI in SBOM Generation and Management

AI can significantly enhance SBOM generation and management, particularly for low-code applications:

Automated Dependency Analysis

AI systems can analyze application code to automatically identify dependencies and generate comprehensive SBOMs, potentially with greater accuracy than manual methods. This is particularly valuable for low-code platforms, where dependencies may not be as explicit as in traditional development.

Vulnerability Prediction

Beyond simply identifying known vulnerabilities in dependencies, AI can potentially predict which components might be vulnerable in the future based on patterns and characteristics. This predictive capability could help organizations proactively manage risk.

Intelligent Component Selection

AI can recommend safer alternative components when potential security issues are detected, helping developers make more informed choices about the libraries and frameworks they incorporate.

Conclusion

The intersection of open-source low-code platforms, AI application generators, and SBOM management represents a promising approach to addressing the growing complexity of software supply chains in enterprise environments.

Key Takeaways

1. Strategic Value: SBOMs are no longer optional but essential components of software development, especially as regulatory requirements increase.

2. Simplification Through Low-Code: Open-source low-code platforms can reduce the complexity of software supply chains by standardizing components and reducing custom code.

3. AI Augmentation: AI-driven code generation and analysis can further enhance the efficiency and security of application development while potentially simplifying SBOM management.

4. Balanced Approach: Organizations must balance the benefits of citizen development with proper governance and security measures.

5. Automation First: Automating SBOM generation and management is critical, especially as software complexity increases.

As enterprises continue their digital transformation journeys, the strategic integration of open-source low-code platforms and AI application generators with robust SBOM practices will be essential for maintaining security, compliance, and transparency in software supply chains.

Organizations that successfully implement these approaches will be better positioned to address emerging threats, meet regulatory requirements, and deliver secure, high-quality software at the speed demanded by modern business.

Introduction

Proprietary license software refers to computer programs developed, owned, and distributed by a specific company or organization that retains exclusive rights to the source code. Unlike open-source alternatives, proprietary software restricts users’ access to the underlying code, limiting their ability to modify, redistribute, or customize the software according to their specific needs. This comprehensive analysis examines proprietary software licensing and its role across various enterprise contexts, including AI applications, low-code platforms, and business technology solutions.

The Nature and Evolution of Proprietary Software

Proprietary software, also known as closed-source software, emerged as a distinct business model in the late 1960s. Before this period, computers were expensive machines primarily leased by companies, with software included at no additional cost. The turning point came in 1969 when IBM began charging for its software separately. The legal foundation for proprietary software was established in 1983 through the court ruling in Apple Computer, Inc. v. Franklin Computer Corp, which recognized software as intellectual property protected by copyright laws.

Proprietary software is characterized by several key elements:

• Restricted access to source code, kept confidential by the developing company

• Distribution under specific licensing terms that govern usage rights

• Legal protection through copyright and intellectual property laws

• Payment models including one-time purchases, subscriptions, or usage-based fees

• Development and maintenance exclusively controlled by the software owner

Proprietary Software Licensing Models

The proprietary software license serves as a legally binding agreement between the software vendor and the end user, defining the terms and conditions under which the software can be used. These licenses typically restrict copying, distribution, and reverse engineering while specifying the conditions for legitimate use.

Common Types of Proprietary Licenses

1. Perpetual License

A perpetual license grants users the right to use a specific version of the software indefinitely. This traditional model typically involves a one-time payment, providing ongoing access to the licensed version, though it may not include future updates or support without additional fees.

2. Subscription License

Subscription licenses allow users to access and use the software for a specified period, usually on a recurring basis (monthly or annually). Users pay periodic fees to maintain access and receive updates, support, and any additional features included in the subscription package.

3. Volume License

Volume licenses are designed for organizations requiring multiple software licenses for their users. These arrangements offer flexibility and cost-effectiveness through a single agreement covering multiple installations or users within a specific organization.

4. Named User License

Named user licenses grant specific individuals the right to use the software. The license is tied to the person rather than the machine, allowing designated users to install and use the software on multiple devices as needed.

5. Floating License

A floating license enables multiple users within an organization to share a limited number of software licenses simultaneously. These licenses are dynamically allocated to users as needed, ensuring efficient use across a larger user base.

Proprietary Software in Enterprise Systems

Enterprise Resource Planning (ERP) Systems

In the context of Enterprise Resource Planning, proprietary software offers several distinct advantages compared to open-source alternatives:

• Comprehensive integrated solutions designed specifically for enterprise needs

• Professional implementation services and dedicated support infrastructure

• Enhanced security measures and compliance capabilities

• Regular updates and enhancements based on industry trends

However, proprietary ERP systems often involve higher costs and potential vendor lock-in concerns that organizations must carefully evaluate. The licensing model significantly impacts the total cost of ownership and long-term flexibility for businesses implementing these systems.

AI Applications and Platforms

The artificial intelligence sector has developed specialized proprietary licensing approaches:

• AI enterprise solutions with specific licensing models for GPU-based deployments

• Proprietary AI platforms offering enhanced security and data protection features

• AI-specific licensing frameworks governing the use, distribution, and modification of AI models

For example, NVIDIA AI Enterprise utilizes a per-GPU licensing model, with subscription options that include technical support services and specific deployment rights. Microsoft’s Copilot offers enterprise-level access to generative AI with varying levels of data protection depending on licensing tiers.

Low-Code Development Platforms

Low-code platforms represent a significant category of proprietary software in the enterprise landscape:

• Licensed low-code platforms provide enhanced security, scalability, and ease of use for application development

• These platforms enable rapid development and deployment, helping organizations bring applications to market faster

• They typically include built-in integrations with other enterprise software tools, enabling smoother interoperability

• Many are specifically designed for citizen developers and business technologists with limited technical expertise

Proprietary low-code platforms often contrast with open-source alternatives, offering more robust security and dedicated support but at higher cost points. This trade-off is particularly relevant for enterprise-scale deployments where reliability and support infrastructure are critical considerations.

Key Users of Proprietary Enterprise Software

Citizen Developers

Citizen developers represent an important user segment for proprietary software in enterprise settings:

• They are business users who can create and run automations with minimal coding knowledge

• Citizen developers typically have strong business process understanding but limited technical skills

• They benefit from the simplified interfaces and guardrails provided by proprietary platforms

• Proprietary solutions designed for citizen developers often restrict access to advanced features to provide a streamlined experience

Specialized Citizen Developer licenses are designed specifically for business users such as marketing analysts, HR managers, and accounts managers who need to create and run automated processes within their specific domains.

Business Technologists

Business technologists are professionals who work outside traditional IT departments but focus on crafting technology-based solutions:

• They apply innovative technology to enhance and streamline business operations

• They focus on improving efficiency, driving growth, and facilitating informed decision-making

• Business technologists often rely on proprietary platforms that provide pre-built components and simplified development environments

• They bridge the gap between technical capabilities and business requirements

These professionals typically work with three types of technology in business settings: operational technology (OT), information technology (IT), and communication technology, often utilizing proprietary software solutions across all three domains.

Enterprise Architecture Teams

Enterprise architecture teams leverage proprietary software to design and implement comprehensive business systems:

• They create blueprints providing holistic views of organizations from business perspectives

• These teams align strategy, processes, information, and technology components

• They utilize proprietary tools for modeling and managing enterprise architectures

• Their work involves integrating various systems into cohesive enterprise information frameworks

Advantages of Proprietary Software in Enterprise Settings

1. Reliability and Technical Support

One of the primary benefits of proprietary software is the comprehensive support infrastructure:

• Dedicated development teams and technical support ensuring reliable performance

• Regular updates, bug fixes, and assistance for issues encountered during usage

• Professional implementation services and training options

• Established support channels with defined service level agreements

2. Advanced Features and Functionality

Commercial software typically offers extensive capabilities developed for enterprise needs:

• Wide range of advanced features based on extensive research and user feedback

• Industry-specific functionalities tailored to particular business requirements

• Regular feature enhancements driven by market demands

• Integrated workflows designed for enterprise-scale operations

3. Integration and Compatibility

Enterprise environments benefit from the integration capabilities of proprietary software:

• Seamless integration with other proprietary tools, systems, or hardware

• Built-in connectors for major enterprise systems and data sources

• Proprietary low-code platforms often include built-in integrations with significant software tools, enabling smoother interoperability with existing systems

• Compatibility with industry-standard protocols and data formats

4. Enhanced Security Measures

Security considerations are paramount in enterprise settings:

• Robust security measures protecting against vulnerabilities and unauthorized access

• Regular security updates and patches addressing emerging threats

• Compliance with industry regulations and standards

• Data protection features safeguarding sensitive business information

5. Tailored Customer Support

The support ecosystem surrounding proprietary software provides significant value:

• Personalized customer support options tailored to specific business needs

• Specialized training programs for different user roles

• Dedicated account management for enterprise customers

• Escalation paths for critical issues

6. Optimized for Specific User Types

Proprietary software is often designed with specific user personas in mind:

• Solutions optimized for citizen developers with simplified interfaces

• Features tailored for business technologists who need to create solutions without deep technical expertise

• Enterprise-grade capabilities packaged for accessibility to non-technical users

Challenges and Limitations of Proprietary Software

Despite its advantages, proprietary software presents several challenges that organizations must consider:

Cost Considerations

The financial aspects of proprietary software can be significant:

• Higher initial purchase costs or ongoing subscription fees compared to open-source alternatives

• Additional costs for support, maintenance, and upgrades over time

• Potential for unexpected price increases during renewal periods

• Costs scaling with organizational growth as additional users or modules are added

Vendor Dependency and Lock-in

Organizations using proprietary software often face dependency issues:

• Reliance on the vendor for updates, security patches, and bug fixes

• Difficulty migrating to alternative solutions due to proprietary data formats or processes

• Potential business disruption if the vendor discontinues the product

• Limited negotiating power once deeply invested in a proprietary ecosystem

Customization Limitations

The closed nature of proprietary software restricts customization options:

• Inability to modify the source code to address specific needs

• Dependence on the vendor for customizations, often at additional cost

• Adaptation to the software’s workflow rather than adapting the software to existing processes

• Limited ability to implement organization-specific features independently

Proprietary vs. Open-Source: A Comparative Analysis

The choice between proprietary and open-source software represents a fundamental decision for organizations:

Development and Ownership Model

• Proprietary: Developed by a single company that maintains exclusive control

• Open-source: Collaboratively developed by communities with shared ownership

Source Code Access

• Proprietary: Source code is closed and inaccessible to users

• Open-source: Source code is freely available for viewing, modification, and distribution

Cost Structure

• Proprietary: Typically involves licensing fees or subscription costs

• Open-source: Core software is free, though support and services may have costs

Customization and Flexibility

• Proprietary: Limited to vendor-approved customizations or extensions

• Open-source: Highly customizable with unlimited modification potential

Support and Maintenance

• Proprietary: Professional support services provided by the vendor

• Open-source: Community support with optional commercial support services

Security Approaches

• Proprietary: Security through obscurity, with vendor-managed updates

• Open-source: Transparent security model with community scrutiny

Emerging Trends in Proprietary Software Licensing

The landscape of proprietary software licensing continues to evolve, with several notable trends:

Subscription-Based Models

There has been a significant shift from perpetual licenses to subscription-based offerings, with software vendors focusing on recurring revenue streams rather than one-time purchases. This model typically integrates continuous updates and support services into subscription packages, changing how organizations budget for and consume software.

Hybrid Licensing Approaches

Many software products now combine proprietary and open-source elements within single offerings. These “mixed-source” software distributions incorporate both models, with vendors maintaining proprietary control over core components while leveraging open-source elements for other aspects. Multi-licensing strategies are also emerging, offering different terms for different user segments or use cases.

AI-Specific Licensing Frameworks

The growing importance of artificial intelligence has led to specialized licensing models for AI applications:

• Purpose-specific licenses that govern how AI models can be used and deployed

• Data usage rights and model training permissions becoming central to licensing terms

• Differentiated tiers for enterprise AI access with varying levels of data protection

Cloud-Based Licensing and Delivery

Cloud-based delivery models have transformed how proprietary software is licensed and consumed:

• Growth of cloud-delivered proprietary software with usage-based licensing metrics

• Integration of license management with cloud identity and access management systems

• Dynamic license allocation based on actual usage patterns rather than static assignments

Conclusion

Proprietary license software remains a cornerstone of enterprise computing environments, offering structured, supported solutions for complex business needs. While open-source alternatives continue to grow in importance, proprietary software delivers substantial value through reliability, comprehensive support, advanced features, and integrated security measures.

For enterprise systems-including ERP solutions, AI platforms, low-code development environments, and digital transformation initiatives-proprietary software provides the stability and support infrastructure necessary for business-critical applications. Business technologists and citizen developers particularly benefit from the structured environments and simplified interfaces that proprietary solutions often provide.

However, organizations must carefully evaluate the trade-offs between proprietary and open-source options, considering factors such as cost, customization requirements, vendor dependency, and strategic alignment with business goals. As the software landscape continues to evolve, hybrid approaches and new licensing models increasingly offer potential middle grounds between the control of proprietary software and the flexibility of open-source alternatives.

Understanding these nuances is essential for making informed decisions that align with organizational objectives, resource constraints, and future growth plans. By thoroughly assessing these factors, organizations can select appropriate software licensing models to support their enterprise architecture strategies and digital transformation initiatives.

Introduction: From MRP to AI-Powered Enterprise Systems

The journey of business solutions in information technology spans over half a century, transforming from simple inventory control systems to sophisticated AI-powered platforms that drive enterprise-wide digital transformation. This evolution reflects the changing needs of businesses and the remarkable technological advancements that have enabled increasingly integrated, intelligent, and accessible solutions. Today’s enterprise systems represent the culmination of decades of innovation, offering unprecedented capabilities for organizations of all sizes.

The Foundation: Early Business Computing (1960s-1970s)

The history of modern business solutions began in the 1960s with the development of Material Requirements Planning (MRP) systems. J.I. Case, a manufacturer of tractors and construction machinery, collaborated with IBM to create what is widely considered the first MRP system. These early solutions were primarily focused on inventory control and production planning, helping manufacturers track materials and coordinate procurement.

During this era, business computing was limited to large corporations that could afford the substantial investments required for in-house development and maintenance. These systems were expensive to create, required specialized expertise to maintain, and consumed significant physical space due to the computing hardware of the time. Despite these limitations, early MRP systems laid the critical groundwork for future enterprise solutions by demonstrating the value of computerized business processes.

The 1970s saw increased adoption of MRP systems, though they remained largely inaccessible to smaller businesses. Eventually, software providers like Oracle and JD Edwards began developing solutions to make this technology available to more organizations.

Enterprise Computing Solutions: Early Pioneers

Organizations like Comp-Ware (which would later become Enterprise Computing Solutions) emerged during this period as leaders in information technology infrastructure. These early IT service providers helped businesses implement and manage increasingly complex computing environments, facilitating technology transfer between developers and business users.

The Integration Era: 1980s-1990s

The Birth of Enterprise Resource Planning

The 1980s witnessed the evolution of MRP into more sophisticated Manufacturing Resource Planning (MRP II) systems with expanded capabilities. This period marked a critical transition as business software began incorporating additional functions beyond manufacturing and inventory management.

By 1990, research firm Gartner coined the term “Enterprise Resource Planning” (ERP), recognizing that businesses across sectors were using these technologies to increase operational efficiency. ERP systems represented a fundamental shift in business software, creating a unified database for information from across the company and integrating various business functions including accounting, sales, engineering, and human resources.

The 1990s witnessed a significant shift toward packaged Enterprise Resource Planning software that revolutionized business operations by streamlining processes and integrating functions like finance, HR, inventory management, and supply chain. This period saw the emergence of ERP as we understand it today: comprehensive enterprise systems that serve as the backbone of organizational operations.

The Rise of Business Enterprise Software

The concept of business enterprise software-applications designed to satisfy organizational needs rather than individual users-became firmly established during this era. According to Martin Fowler, “Enterprise applications are about the display, manipulation, and storage of large amounts of often complex data and the support or automation of business processes with that data”.

Enterprise systems emerged as large-scale software packages supporting a range of business processes, information flows, reporting, and data analytics in complex organizations. These systems were characterized by their ability to handle high volumes of critical data while providing transaction performance and data security.

Early Software Development Tools

Concurrent with the evolution of enterprise systems, the 1980s and 1990s saw the emergence of rapid application development (RAD) tools like Borland’s Delphi, PowerBuilder, and Microsoft’s Visual Basic-what would later be recognized as the first low-code platforms. These tools represented early attempts to make software development more accessible to a broader range of users by reducing the complexity of coding.

The Connected Enterprise: 2000s

The early 2000s introduced ERP II, which expanded traditional ERP by incorporating Customer Relationship Management (CRM) and Business Intelligence capabilities into operations. This period also saw the development of internet-enabled ERP systems and the initial adoption of cloud ERP solutions, which would later transform the accessibility and deployment of enterprise software.

The Shift to Cloud and Service Models

The 2000s marked a pivotal transition as enterprise computing began moving away from on-premises deployments toward cloud-based solutions. This shift dramatically reduced the barriers to adoption for smaller organizations while providing larger enterprises with more flexible and scalable options.

During this period, Enterprise Computing Solutions (formerly Comp-Ware) rechristened itself as Keystone Information Systems to focus on developing customized software solutions and products. This transition reflected the broader industry shift toward specialized business software solutions that could address specific organizational needs.

The Intelligent Enterprise: 2010s to Present

Digital Transformation and Enterprise Systems

By the 2010s, enterprise resource planning systems had evolved to process data in real-time, leveraging machine learning and Internet of Things (IoT) technologies to provide unprecedented business insights. Digital transformation became a central strategic priority for organizations seeking to remain competitive in an increasingly technology-driven business environment.

The roots of digital transformation can be traced to the late 20th century, but it wasn’t until the 2010s that it became recognized as an indispensable core of business strategy rather than merely an augmentation of existing processes. Modern digital transformation involves sophisticated integration of artificial intelligence, cloud computing, and IoT technologies.

The Rise of Low-Code Platforms and Citizen Developers

Low-code platforms gained significant momentum during this period, with companies like OutSystems, Appian, and Mendix capturing substantial market share. These platforms accelerated the delivery time of new applications, enabling organizations to rapidly develop and deploy solutions without extensive coding expertise.

This technology democratization gave rise to citizen developers-business users with little to no coding experience who could build applications using IT-approved technology. According to Gartner, who coined the term, citizen developers are essential to addressing the growing demand for custom business applications that traditional IT departments cannot fulfill alone.

Business Technologists: Bridging Technology and Strategy

The 2010s also saw the emergence of business technologists-professionals possessing a unique blend of business acumen and technological expertise. These individuals play a critical role in aligning business objectives with technological capabilities, effectively bridging the gap between technical and strategic aspects of an organization.

Business technologists serve as key enablers in digital transformation initiatives, driving the seamless integration of technology into various business functions. Their ability to comprehend both operational intricacies and emerging technologies makes them invaluable assets in navigating digital transformation complexities.

Modern Enterprise Business Solutions

Enterprise Business Architecture

Today’s enterprise solutions are built upon robust enterprise business architecture frameworks that provide standardized tools to assess business processes, IT infrastructure, and capabilities. These frameworks include Business Model Canvas, Balanced Scorecard, BIZBOK, and PESTLE analysis, each offering unique approaches to aligning technology with business objectives.

Well-implemented enterprise business architecture delivers significant benefits, including improved communication and collaboration across teams, enhanced organizational agility, and valuable pre-built assets that accelerate project implementation.

AI Application Generators and Enterprise AI

The latest evolution in business solutions includes AI Application Generators that enable organizations to create customized applications without coding expertise. Tools like Jotform’s AI App Generator allow users to describe their desired application through natural language conversation, then automatically generate functional applications that can be further customized through no-code interfaces.

Enterprise AI represents a category of enterprise software that harnesses advanced artificial intelligence techniques including machine learning to drive digital transformation. Unlike general AI applications, enterprise AI focuses on addressing specific high-value use cases at scale, where embedding AI into business processes can produce meaningful value.

Organizations deploying enterprise AI applications can achieve substantial improvements in business processes throughout their value chain, resulting in increased business resilience, greater efficiency, improved profitability, and reduced environmental impact.

Open-Source in Enterprise Solutions

Open-source software has become increasingly important in the enterprise software ecosystem. The open-source movement, which originated in 1983 with Richard Stallman’s ideological stance that software should be accessible to programmers for modification and improvement, has evolved into a critical component of modern enterprise solutions.

Today, many enterprise products incorporate open-source components, benefiting from the collaborative development model while providing the support and security enterprises require. Open-source principles have influenced technology transfer practices, enabling more efficient dissemination of innovations across organizational boundaries.

The Enterprise Systems Ecosystem

Enterprise Systems Group

Organizations increasingly establish dedicated Enterprise Systems Groups focused on aligning business requirements with IT systems to deliver efficiencies that reduce costs, optimize resources, and enable innovation. These specialized teams are responsible for the dynamic management of enterprise data centers, which continue to serve as the main service hubs driving innovation and business agility.

Enterprise Products

Enterprise products are defined as software or services designed specifically for businesses and organizations rather than individual consumers. What distinguishes enterprise products is their specialized sales approach, pre-sales teams that help potential customers understand the product’s benefits, customer success teams that maximize value realization, and dedicated support services.

These products are characterized by their ability to handle significant workloads, maintain robust security, and seamlessly integrate with existing enterprise systems. They serve as strategic assets that enable informed decision-making, enhanced productivity, and innovation.

Types of Technologists in the Modern Enterprise

Today’s enterprise systems are supported by diverse types of technologists, each bringing specialized skills to address different aspects of technology implementation and management. These include:

1. Analysts who interpret complex data sets and identify trends

2. Advocates who promote technology adoption and best practices

3. Communicators who bridge technical and non-technical stakeholders

4. Business-oriented technologists who align technology with business objectives

5. Designers focused on user experience and interface

6. Facilitators who ensure smooth project execution

7. Educators who train and inspire others about technology

8. Builders who develop and construct technology solutions

9. Organizers who manage people and resources

10. Scientists conducting research to advance technology

Conclusion

The evolution of business solutions IT represents a remarkable journey from simple inventory management systems to sophisticated, AI-powered enterprise platforms. Over decades, we’ve witnessed the transformation from MRP to ERP to modern enterprise systems that integrate artificial intelligence, cloud computing, and advanced analytics.

Today’s business technology landscape is characterized by democratized development through low-code platforms and citizen developers, strategic alignment through business technologists and enterprise business architecture, and intelligent automation through enterprise AI and AI application generators. These advancements have made sophisticated business solutions more accessible while simultaneously increasing their capabilities and strategic impact.

As we look toward the future, the continued convergence of enterprise resource planning, artificial intelligence, and low-code development promises even more powerful and accessible business solutions. Organizations that effectively leverage these technologies while maintaining focus on business outcomes will be best positioned to thrive in an increasingly competitive and technology-driven business environment.

Introduction

Supply chain management (SCM) has evolved from basic logistics tracking into a sophisticated digital ecosystem where software serves as the nervous system, connecting every aspect of the modern enterprise. Today’s global supply chains depend on robust software solutions to plan, execute, and optimize the flow of goods, services, and information. This report examines how various software technologies and approaches are transforming supply chain management, creating unprecedented efficiency, visibility, and resilience.

Enterprise Systems and Supply Chain Management Integration

Enterprise systems form the backbone of modern supply chain management, providing the critical infrastructure needed to coordinate complex networks of suppliers, manufacturers, distributors, and retailers. These systems have evolved significantly to meet the growing demands of global commerce.

The Evolution of Enterprise Resource Systems

Enterprise Resource Systems (ERS) have transformed from simple inventory management tools into comprehensive digital backbones that integrate all aspects of business operations. In the context of supply chain management, these systems enable organizations to centralize data, automate processes, and manage resources in real-time. Modern Business Enterprise Software leverages cloud-native architecture to provide unprecedented levels of efficiency, intelligence, and adaptability.

The fundamental difference between Enterprise Resource Planning (ERP) and SCM software lies in their focus: while ERP systems take a holistic approach to business process automation across departments, SCM systems specifically connect manufacturing teams with the resources they use and the responsibilities they fulfill. ERP helps businesses coordinate supply chain management processes, from planning and procurement to manufacturing and distribution. This integration among ERP modules improves the flow of information between business units, making teams more collaborative and efficient.

Enterprise Business Architecture for Supply Chain Excellence

Enterprise Business Architecture provides the framework for aligning technology capabilities with business strategy in supply chain operations. Modern architecture emphasizes flexibility, scalability, and interoperability across the technology landscape. This architectural approach supports microservices that enable organizations to implement only the components they need while maintaining integration with other systems through standardized interfaces.

The Enterprise Systems Group plays a crucial role in evaluating and integrating emerging technologies while managing their complexity and security implications. Their strategic oversight ensures that supply chain software solutions align with broader business objectives while supporting specialized operational requirements.

Advanced Software Capabilities Transforming Supply Chains

The modern supply chain landscape is shaped by sophisticated software capabilities that extend far beyond basic inventory tracking and order management.

AI and Automation in Supply Chain Software

AI Enterprise solutions are revolutionizing supply chain management by shifting from passive data management to proactive business intelligence. Oracle’s AI agents for SCM provide traditional and generative AI capabilities to improve operational efficiency, automate standard transactions, and increase inventory visibility. These AI solutions can optimize processes such as maintenance troubleshooting, delivery planning, and packaging sustainability.

AI Application Generator platforms enable both technical and non-technical users to create sophisticated supply chain solutions. These platforms analyze large datasets with sophisticated algorithms to produce applications that dramatically accelerate development timelines. For example, AI can ingest enterprise and external data to build and test forecasting models, helping organizations predict demand based on a wide range of factors including history, price, seasonality, and external events.

Hyperautomation brings together technologies like RPA, IoT, and machine learning to automate multiple workflows across the digital infrastructure simultaneously. By 2025, hyperautomation platforms are expected to provide end-to-end automation with built-in analytics, aiming to cut operational costs by 40% while achieving near-100% process accuracy.

Business Software Solutions for Supply Chain Optimization

Business Software Solutions for supply chain management have expanded to include specialized capabilities such as demand forecasting, supplier management, procurement, and inventory management. These solutions provide real-time data about supply chain activities, helping businesses predict and mitigate disruptions.

Enterprise Products for supply chain management now include sophisticated tools for supply chain visibility, inventory optimization, and supplier relationship management. These products typically consist of two subsystems: Supply Chain Planning (SCP) for creating calendar schedules and modeling various scenarios, and Supply Chain Execution (SCE) for tracking and monitoring logistics operations.

The Democratization of Supply Chain Software Development

One of the most significant trends in supply chain software is the democratization of application development through low-code platforms and citizen developers.

Low-Code Platforms and Citizen Development

Low-Code Platforms have transformed how organizations approach supply chain software development. These platforms enable the creation of custom applications with minimal traditional coding, accelerating development cycles and reducing technical barriers. According to recent data, 84% of businesses use low-code/no-code platforms to reduce the strain on IT.

Citizen Developers are non-IT business users who build custom business applications without formal programming training or experience. They use low-code/no-code development platforms sanctioned by corporate IT to facilitate organizational processes. In the supply chain context, citizen developers create small-scale applications that drive automation and streamline processes, bringing significant value over time.

The low-code citizen development model contributes to ongoing business transformation while simultaneously cultivating the skills citizen developers need for future work. With proper training, citizen developers can quickly build a minimum viable product (MVP) rather than spending weeks or months on applications centered around designated requirements. This approach can slash development time by 50%-90%, increasing competitiveness and lowering costs.

Types of Technologists in Modern Supply Chain Software

Various types of technologists contribute to supply chain software development and implementation. Business Technologists are business-focused professionals with technical skills who can bridge the gap between operational needs and technological capabilities. They collaborate with IT teams to ensure that supply chain solutions address specific business requirements.

Professional developers work alongside citizen developers, providing guidance and support for more complex integration needs. This collaboration creates a balanced approach where simple applications can be developed quickly by business users, while more complex enterprise systems are handled by professional IT teams.

Digital Transformation and Open Source in Supply Chain Software

Digital transformation has fundamentally changed how organizations approach supply chain management, with open source playing an increasingly important role.

Digital Transformation in Supply Chain Processes

Digital transformation in supply chain management involves implementing technologies that enhance visibility, improve decision-making, and increase agility. Successful technology transfer in supply chains relies on robust process characterization, communication, and collaboration among multiple teams and sites.

One challenge in this transformation is the “digital data gap” that often develops after product candidate selection and prior to commercial manufacturing. Forward-looking companies are deploying cloud-based, 21 CFR Part 11-compliant, centralized data hubs as their persistent knowledge “libraries” for process and product data. This approach eliminates risks associated with technology transfer as data remains persistent and available—even as staff, partners, and facilities change.

Open Source in Supply Chain Software

Open source development practices have become a key component of software supply chains and modern software innovation1. The software supply chain itself consists of code, configurations, proprietary and open source binaries, libraries, plugins, and container dependencies.

Open source software supply chain management saves companies time and money, improves quality, delivers business agility, and mitigates some business risks. However, organizations inherit the software supply chain of all parts of their software, which can create security vulnerabilities. To address this, risk-averse businesses and governments often request a software bill of materials (SBOM) that describes part or most of the supply chain.

Enterprise Computing Solutions for Modern Supply Chains

Enterprise Computing Solutions have transcended traditional boundaries, creating ecosystems where business and technology seamlessly converge. These solutions leverage cutting-edge technologies to provide unprecedented levels of efficiency, intelligence, and adaptability.

Cloud-Native Architecture and Integration

Modern supply chain software increasingly adopts cloud-native design and API-first development approaches. This represents a significant departure from monolithic systems of previous generations, which often required extensive customization and created organizational dependencies on specific vendors.

Cloud-based quantum platforms are beginning to make it possible for enterprises to solve complex supply chain problems in minutes rather than years, particularly benefiting areas like financial modeling and order fulfillment. This technology transfer from theoretical physics to practical business applications represents one of the most significant advances in Enterprise Computing Solutions.

Edge Computing and IoT in Supply Chain Management

Edge computing has decentralized data processing by moving computation closer to data sources, while IoT creates a network of interconnected smart devices generating real-time data. This architectural approach minimizes latency by processing data at or near its source, rather than sending it to centralized cloud servers.

In 2025, the integration of business intelligence tools with edge computing enables real-time analytics and visualization at the network edge. This capability has transformed how enterprises manage distributed operations and respond to changing conditions across complex supply chain environments.

Conclusion

Software has become the central nervous system of modern supply chain management, enabling unprecedented levels of visibility, efficiency, and resilience. The integration of Enterprise Resource Systems with specialized SCM solutions provides organizations with a comprehensive framework for managing complex global supply networks.

The rapid evolution of AI Enterprise applications, combined with the democratization of development through Low-Code Platforms and Citizen Developers, is accelerating innovation in supply chain software. These trends allow organizations to quickly adapt to changing market conditions while maintaining strategic control over their supply chain operations.

As digital transformation continues to reshape supply chains, the importance of robust Enterprise Business Architecture and secure open-source practices becomes increasingly critical. Organizations that effectively leverage these technologies—through strategic deployment of Enterprise Products, empowerment of Business Technologists, and implementation of comprehensive governance frameworks—position themselves for competitive advantage in an increasingly digital business landscape.

The future of supply chain management will be defined by organizations that can effectively harness Enterprise Computing Solutions to create adaptive, resilient supply chains capable of navigating an increasingly complex global business environment.