In today’s digital age, companies are looking for faster and more efficient ways to adapt to technological changes without compromising quality or scalability. The focus on low-code development platforms and artificial intelligence (AI) has gained ground, promising to optimize return on investment (ROI). However, the successful implementation of these technologies is not without its challenges. Below, we explore the main challenges and opportunities that companies should consider to maximize ROI in this technological era.
Challenges in the adoption of Low Code
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Fragmented development
The use of low code platforms allows business users to develop solutions autonomously, without the need for in-depth knowledge of software architecture. However, this can lead to fragmented developments that are difficult to maintain in the long term. The lack of technical expertise can generate an accumulation of “technical debt”, affecting the sustainability of the solutions.
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Scalability limitations
While low code enables rapid developments, its ability to handle large volumes of data and complex processes is limited. As companies grow, solutions developed on these platforms may require more robust infrastructures to ensure adequate scalability.
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Technical debt
The simplicity of low code can lead to underestimating key aspects such as security, performance and governance. This increases “technical debt”, a risk that can compromise the ability of companies to grow efficiently and sustainably.
AI in Business Applications: Intelligent Automation
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Purposeful Automation
The adoption of AI has brought with it the promise of large-scale automation. However, many companies integrate these technologies without a thorough analysis of their real benefits. It is crucial that AI not just improve processes for the sake of it, but that it is aligned with clear strategic objectives.
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Misalignment between AI and KPIs
For AI to be truly effective, it is necessary to have a robust data infrastructure and models trained on high-quality data. Lack of alignment between AI implementation and enterprise KPIs can result in poor decisions or poor ROI.
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Costs and benefits
Adopting AI involves considering operational and implementation costs, but it is also vital to align these expenses with strategic objectives. AI should drive improvements in customer experience, reduce operational costs or generate new revenue streams.
Governance and Change Management Challenges
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Governance and scalability
As companies grow, the governance of low-code platforms becomes increasingly complex. The lack of adequate tools to manage these solutions can lead to performance issues and affect the user experience.
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Rapid evolution vs. resistance to change
Platforms such as Dynamics 365 and Power Platform are constantly being updated, offering new functionalities that allow companies to be more agile. However, resistance to change within organizations remains a significant challenge that limits the full utilization of these applications.
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Complexity in the software lifecycle
Accumulated technical debt and the rapid evolution of low-code platforms present additional challenges in managing the lifecycle of enterprise solutions. Existing governance tools are often not sufficient to handle this complexity efficiently, resulting in messy ecosystems that are difficult to manage.
AI and Low Code: Opportunities for Transformation
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Integration with Legacy Systems
One of the biggest challenges in the implementation of AI and low code is the integration with legacy systems. These systems, often outdated and poorly documented, make it difficult to integrate seamlessly with new technologies such as Copilot. However, through custom APIs and the use of Azure Functions/Azure Logic Apps, companies can connect their legacy systems with new platforms, optimizing their performance and ensuring more efficient operations.
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Mass automation and scalability
Companies that handle a large volume of automated processes may encounter performance bottlenecks. However, combining Power Automate with more advanced tools such as Azure Logic Apps makes it possible to handle these volumes efficiently, ensuring optimal response times and increased processing capacity.
Maximizing ROI in the era of Low Code and AI
To maximize ROI in the adoption of low code and AI, enterprises must proactively address the above challenges. The key lies in strategic planning, effective governance and investment in robust infrastructures that enable long-term growth. Only then will they be able to fully leverage the transformative potential of these technologies.
In conclusion, while low code and AI offer tremendous opportunities for process optimization and ROI improvement, it is critical that companies are prepared to manage the associated challenges. Alignment with strategic objectives, attention to governance and scalability, and effective integration with legacy systems are critical factors for success in this new technological era.
As Ismael El Aichouni Jouied, Team Lead of the area at Bravent, explained during his presentation at the BizzSummit 2024 event, companies that address these challenges proactively and strategically not only maximize ROI, but also position themselves at the forefront of innovation. His speech highlighted how proper management of low code and AI can completely transform workflows and improve business results.
