THE BOOM OF GENERATIVE AI
Digital transformation is the bleeding edge of business resilience. For years, it was underpinned by the adoption of cloud and the modernisation of the IT platform. As transformation is an ongoing process, enterprises look to innovations and cutting-edge technologies to fuel further growth and open more opportunities. Notably, organisations are now turning to Generative AI to navigate the rapidly evolving tech landscape.
Albeit emerging recently, the potential applications of GenAI for businesses are significant and wide-ranging. Businesses are rapidly implementing AI-driven tools into their daily workflows to save valuable time. A recent McKinsey study estimated that automation integrated with Generative AI could accelerate 29.5 percent of the working hours in the US economy. Generative AI can help businesses achieve faster development in two main areas: low/no-code application development and mainframe modernisation.
GENERATIVE AI & LOW/NO-CODE
As Generative AI and low-code technology are increasingly merging, businesses can unlock numerous opportunities while using them in tandem:
- Shared spotlight with non-IT experts: Generative AI allows “citizen developers” to take advantage of the opportunities in development with minimal software training and skills. Developers can create and modify applications independently, reducing the burden on IT teams to focus on more strategic and complex tasks.
- Streamlined coding process: Generative AI provides real-time information on available functions, parameters, and usage examples as the coder types. Specifically, embracing Generative AI can save an average of 38 percent development time, allowing organisations to optimise the time-to-market.
- Faster app development: By leveraging Generative AI, companies can automate documentation generation, improve software reusability, and seamlessly integrate AI functions such as chatbots and image recognition into low-code applications. As human error is one of the most time-intensive parts of the development cycle, Generative AI allows fewer feedback loops.
- Compliance with best practices: AI can verify compliance with coding best practices and recommend optimizations to enhance performance. This proactive support simplifies the coding process, resulting in more organised codebases.
GENERATIVE AI & MAINFRAME MODERNISATION
Generative AI also plays a role in assisting organisations with the transformation and modernisation of their mainframes, which continue to be in wide use in key sectors such as retail, banking, and aviation.
Research from IBM found that 93 percent of companies still use mainframes for financial management, 73 percent for customer transaction systems, and more than 70 percent of Fortune 500 companies run business-critical applications on mainframes.
However, mainframes are a challenging prospect for transformation because the applications they run are highly complex and difficult to change. Over time, these applications become outdated, the associated cost becomes higher, and operational disruption can occur due to maintaining and updating the system.
Organisations are shifting workloads to hybrid cloud environments while modernising mainframe systems to serve the most critical applications. However, this migration process may involve data transfer vulnerabilities and potential mishandling of sensitive information and outdated programming languages. A poorly structured approach to application modernisation also potentially leads to data breaches.
Hence, organisations are turning to Generative AI to mitigate these risks, bolstering reliability and efficiency in the areas where human error might create vulnerabilities.
By leveraging AI, engineers can quickly generate the code they need for an application migration exercise, ensure its quality, and create the necessary documentation. Even after migration, AI can help generate test cases, maintain and add more features to existing legacy systems, as well as evaluate the similarity between mainframe functions and migrated functions.
Given the scarcity of experts in legacy languages like Cobol – on which many mainframe applications are built – Generative AI also provides the bridge that allows a broader range of engineers and coding experts to tackle modernisation and migration projects. It equips developers with the necessary knowledge, improving developer efficiency, rapidly resolving issues, and easily maintaining and modernising enterprise systems of various industries.
For instance, FPT Software has recently introduced the development of Masterful AI Assistant or Maia, a special Generative AI concept of an agent specifically assisting with highly complex processes. Its vision is to be the co-pilot and co-worker for developers and engineers, boosting productivity and making the development process more enjoyable and fulfilling.
Through its conversational interface, Maia will deliver guidance and domain know-how along with automating code documentation and co-programming. Maia is also expected to analyse the complexities of legacy systems to ensure accuracy, generate missing documents and suggest suitable modern architecture during the assessment phase, and generate test cases during the testing phase.
WHAT TO LOOK FOR IN AN AI PARTNER
While the benefits of embracing AI are significant, maximising those opportunities requires extensive expertise. There are three key considerations that companies need to consider in strategically collaborating with an AI partner:
- Proven Skills and Expertise: Having a sector-by-sector understanding of how to best capitalise on the opportunities of AI is one of the critical areas. The AI partner needs to demonstrate technical proficiency, industry-specific knowledge, and past successes.
- Training and Support: An ideal AI partner should offer comprehensive training programs to facilitate knowledge transfer to your team, ensuring they can independently manage and understand the implemented AI systems.
- Collaboration to unlock AI Potential: Effective collaboration is paramount for successful AI integration. The partner will be able to assist with customising solutions to the specific business outcomes for the enterprise, integrate with existing systems seamlessly, and foster scalability.
To this end, the IT service provider FPT Software is currently adopting an ecosystem and partnership approach, covering various areas from research and solutions development to responsible AI, to propel innovation and the practical application of AI.
Particularly, FPT Software, in collaboration with Mila, a Canadian research institute specialising in machine learning, have formed an AI Residency program in which resident researchers work directly with leading academics while participating in real-world projects, assisting organisations to build a suite of products backed by a strong R&D base.
Both organisations have successfully promoted Responsible AI to support sustainable growth, human development, and social progress. This agenda is further strengthened on a global scale with FPT Software joining the recently established AI Alliance, a pivotal initiative formed by leading organisations like IBM and Meta.
The IT firm also partners with visionary partners to develop impactful solutions. A few highlights include its collaboration with Landing AI to develop a computer vision quality inspection solution with visual prompting to shorten labeling time from months to minutes or partner with Silicon Valley’s Aitomatic to expand the provision of advanced industrial AI solutions, integrating Open Source Small Specialist Agent (OpenSSA) technology.
CLOSING THOUGHTS
Generative AI helps companies accelerate their digital transformation and empower their entire workforce to engage with technology while running the risk of human error.
To successfully harness the power of AI, a partner-led approach is highly critical in navigating potential AI challenges. With the right partner, the results of this next wave of transformation will be remarkable.
Explore how FPT Software’s AI solutions can accelerate your digital transformation.
