Navigating the software landscape in the GenAI era

IN BRIEF:

• Traditionally, the choice between custom and packaged software was straightforward — each option presented clear pros and cons aligned with specific business needs. However, the rise of Generative AI (GenAI) has blurred these lines, altering the decision-making process for business leaders.

• GenAI, with its unprecedented capabilities in generating code, creating unique content and personalized user experiences, has added to the dilemma for enterprises on whether customized solutions continue to create a unique competitive advantage.

• Businesses must continue to evaluate the need for customization against the benefits of AI-enhanced packaged solutions.

The rise of GenAI is reshaping the software industry, enabling new ways to create content, automate tasks, and tailor user experiences. Businesses now face a critical decision: should they invest in custom software that is specifically designed for their needs, or should they choose off-the-shelf solutions that are enhanced by GenAI add-ons like customized content and task automation? This choice has significant implications for how software is selected and implemented across enterprises.

For example, the insurance and finance sectors, traditionally reliant on custom-built software for their complex operations, are now moving towards standard, packaged solutions driven by GenAI. Given the need for agility, cost-effectiveness, and digital service demands, this shift showcases the challenges and opportunities in modernizing software systems. Their experiences offer valuable lessons for other industries contemplating similar transitions.

As leaders navigate this decision, they must consider the long-term impact on their business strategy and operations. This article explores the considerations and implications of choosing between bespoke and off-the-shelf software solutions in the age of GenAI.

THE EVOLVING DECISION MATRIX
Custom software is tailored to meet the specific needs of a business, offering a high degree of personalization and flexibility. On the other hand, packaged software provides a ready-made solution that is generally more cost-effective and quicker to deploy but may not cater to every unique requirement.

Traditionally, the choice between custom and packaged software was straightforward — each option presented clear pros and cons aligned with specific business needs. However, the rise of GenAI has blurred these lines, altering the decision-making process for business leaders. The integration of GenAI into software development and deployment processes introduces a new complexity, requiring a more strategic approach to software selection. Like the late 1990s shift in production and manufacturing companies, which moved from proprietary systems to standardized ERP (Enterprise Resource Planning) and CRM (Customer Relationship Management) systems, today’s businesses must consider the automation and cost advantages that such a transition could bring.

CUSTOM SOFTWARE IN THE GENAI ERA
Custom software development, once a time-consuming and costly endeavor, is being transformed by GenAI. AI-driven development tools can now assist programmers in generating code snippets, produce functional and test specifications, and reduce the overall development life cycle. Empirical evidence shows that the appropriate use of GenAI in coding tasks can double the gain in developer productivity. This mirrors the automation of important business functions seen in other industries, such as one-touch customer billing or automated supply-chain planning, which have reaped significant cost advantages from shared services.

However, the challenges of integrating GenAI into custom software cannot be overlooked. It requires a depth of technical expertise and raises ethical questions about data usage and AI-generated content. Additionally, custom solutions demand a focused approach, often necessitating the hiring of specialized developers and heavy investment in IT infrastructure and licenses. This is akin to the banking and insurance sectors, where upgrades to core systems are lengthy and risky due to complex, heterogeneous products and decades-old IT systems.

PACKAGED SOFTWARE AND GENAI
On the other side of the spectrum, packaged software providers are also incorporating generative AI into their products, offering advanced features that were once only possible with custom development. This democratizes access to powerful AI tools, making them available to a wider audience.

This change also makes advanced AI tools more accessible to a wider range of businesses. With these enhanced off-the-shelf products, companies can quickly implement sophisticated solutions and tap into the knowledge of a large user base. However, the generic nature of packaged software may not suit all business requirements. Depending on vendors for updates and new AI features could also lead to potential risks and limitations.

NAVIGATING THE NEW SOFTWARE LANDSCAPE
The age of GenAI is reshaping the software industry, blurring the lines between custom and packaged solutions. Custom software, now more accessible with AI assistance, offers unparalleled customization and competitive advantage. Packaged software, enhanced by AI, provides a cost-effective and quick-to-deploy alternative with a wealth of community support. Businesses must carefully assess their needs, considering factors such as the level of customization required, budget constraints, and the strategic importance of AI in their operations. Whether opting for a custom-built AI-driven platform or an AI-enhanced packaged solution, the goal remains the same: leveraging the transformative power of GenAI to drive innovation and success in the digital age.

As the software industry evolves with the integration of GenAI, businesses are faced with choices that mirror those made by banks and insurance companies. The move towards standard software, driven by the need for new digital services and customer demand for online products, suggests a similar path for businesses across all sectors.

By examining the success factors identified in the transition from proprietary to standard systems, such as technology selection, transformation leadership, team composition, timing, and transparency, companies can navigate this new era effectively. The lessons learned from other industries serve as a guide for businesses to make informed decisions in adopting new software solutions that harness the power of GenAI.

This article is for general information only and is not a substitute for professional advice where the facts and circumstances warrant. The views and opinions expressed above are those of the author and do not necessarily represent the views of SGV & Co.

Rajiv Kakar is a technology consulting principal of SGV & Co.