With the evolution in technology, implementing artificial intelligence in enterprise applications plays an indispensable role in powering businesses of all sizes and domains. Approx. 84.7% of software development projects revolve around the creation and enhancement of enterprise applications, according to recent industry statistics.

However, despite their undeniable significance, the path to successfully developing and maintaining enterprise applications is loaded with challenges that demand innovative solutions like AI. Here we will discuss the top 10 challenges that developers and organizations face in enterprise application development and their solutions.

1. Lack of Appropriate Resources and Expertise

App development failure often comes from developers lacking knowledge, poor user understanding, communication gaps, resource shortages, and mid-project workforce changes.

These challenges can lead to app performance issues, poor user experiences, project delivery delays, misaligned app expectations, and budget overruns.

Solution: To address these challenges, developers should adopt a process-oriented approach augmented by the strategic integration of AI to conduct market research to align with user expectations. AI tools can facilitate smart resource allocation and provide invaluable insights onto user preferences.

2. Security and Authorisation

Enterprise mobile app development faces a critical challenge in maintaining robust security. Shockingly, Q2 2021 alone saw the detection of over 800 thousand mobile malware installation packages detected in Q2 2021 alone. Furthermore, 77% of mobile finance apps contain serious vulnerabilities that could lead to data breaches and substantial business losses.

Solution – Shift critical code and libraries to the server, implement robust security measures within the mobile app, and invest in AI-driven threat detection or trusted security providers for thorough testing. Employ innovative, AI solutions for encryption techniques and ensure that the chosen enterprise mobile app development company prioritises security at every development phase.

3. Integration with back-end resources

Integrating enterprise mobile apps presents unique challenges. Even with a fully functional app, enterprises may need custom coding to add mobile functionality and integration capabilities.

Integration issues can lead to redundancy, a subpar user experience, poor app performance, and customer dissatisfaction, ultimately resulting in app failure.

Solution – Incorporate AI strategically for early communication of integration needs. Opt for flexible platforms using AI for intelligent data mapping, ensuring seamless integration with diverse APIs. This enhances adaptability, optimizing app performance and user satisfaction for long-term success.

4. Scalability Issues

Enterprise-level organizations have diverse and critical scaling requirements. They need apps that can adapt to industry disruptions and incorporate emerging technologies with minimal effort and resource investment.

Failing to address scalability can result in a s strained app hardware infrastructure, app failure due to an inability to accommodate increased usage or users, limited growth opportunities, poor user experiences, and diminished app monetization.

Solution:

Minimize scaling efforts by selecting popular platforms, flexible AI technologies, and app functionalities that align with future expansion goals. Implement horizontal scalability to facilitate future expansion. This approach enables the app to grow seamlessly in response to increased demand of resource requirements.

5. User Experience complexity

In the realm of enterprise mobile apps, user interface (UI) and user experience (UX) are critical differentiators between success and failure. While both are vital, user experience takes precedence as a key engagement driver, converting users into loyal clients.

Solution – Aim for a simpler and user-friendly design that enhances usability. Use AI to create appealing themes and high-resolution graphics to create an attractive interface and make the app interface interactive to engage users effectively. Make the app interface dynamically interactive through AI features. Conduct AI-enhanced research to identify and address user pain points.

6. Data encryption

Safeguarding sensitive data on user’s smartphones through encryption is a critical challenge. Privacy concerns are on the rise, and apps requesting private data face scepticism.

Approximately 81% of Americans believe that the risks of app data collection outweigh the benefits. 97% per cent of companies recognize the competitive advantage of privacy investment.

Solution – Integrate AI for enhanced data security, use AI-driven encryption in secure servers. AI authentication for adaptive security can be a good option. Invest in AI data privacy techniques and security providers to enhance user data protection.

7. Low cost and return on investment

Enterprise application development is a substantial investment that encompasses planning, development, costs, and ongoing maintenance expenses, including regular updates. It becomes disheartening when this significant expenditure fails to deliver the expected results.

Solution – Leverage AI to optimize ROI by identifying and analysing key performance indicators (KPIs). Whether tangible (e.g., frequency of use, time saved) or intangible (e.g., improved employee morale, competitive differentiation), AI-driven insights provide crucial guidance. Incorporate AI in development efforts to tailor the enterprise application based on these indicators, ensuring a more impactful and effective solution that maximizes returns or the initial investment.

8. Big Data

For enterprise-grade organizations, harnessing the power of vast data reserves is crucial, and Big Data is the linchpin for this endeavour. While big data implementation may be a minor issue for enterprise mobile applications in the cloud due to cloud benefits, data management and security have become formidable tasks.

Solution – Utilize Artificial Intelligence tools to ensure data safety in on-premises and cloud stores. Employ AI-driven strategies to keep critical data separate for faster responses and enhanced security. For inactive data, leverage AI analytics to optimize performance, considering third-party Big Data solutions to reduce operational overhead. This ensures efficient and secure handling of large datasets in enterprise mobile apps.

9. API Strategy

Selecting the right robust API strategy is among the most formidable challenges in enterprise mobile app development. This challenge arises from the need to choose specific APIs for specific functionalities within an enterprise app. This can lead to a suboptimal customer experience, hinder B2B collaboration and introduce security issues with business data and resources.

Solution – Leverage AI from informed API decisions. Define business goals and start with small AI-driven API projects for iterative learning. Evaluate existing infrastructure against AI-optimized assessments of chosen APIs, ensuring alignment, and mitigating challenges. This AI-driven approach ensures an adaptive and effective API strategy.

10. Interoperability

Achieving seamless integration between sub-systems, or interoperability, is crucial for the smooth functioning of enterprise systems. To enable effortless sharing and usage of data, enterprises must adhere to interoperability standards. Careful design is particularly necessary in heterogeneous environments that involve disparate systems.

Solution – Consider implementing AI to enhance established Enterprise interoperability frameworks such as the Europeans Interoperability framework or ATHENA interoperability framework. These frameworks complemented by AI address various approaches and barriers in Enterprise Interoperability, ensuring that your Enterprise Application achieves seamless interoperability.

Conclusion

As we’ve explored the top 10 challenges and their solution above, it’s clear that the future of enterprise application development holds incredible promise with the implementation of AI. The path ahead will continue to be shaped by technological advancements, evolving user demands, and a rapidly changing business environment. AI-enhanced Enterprise applications are poised to play an even more critical role in business automation, eCommerce, and beyond. So, in case you are planning to develop an enterprise application, make sure you take care of the above challenges and deal with them with AI implementation smartly.