Key Takeaways
- Have you heard about AI software engineering?
- AI software development companies are spearheading the software development services in the last quarter of 2024.
- Read our latest LinkedIn Newsletter to witness the power of AI software development services and understand how you can use AI for software development.
2024 has emerged as the Era of AI with its wide applications across various industries and business operations.
When AI has entered every domain possible, then how can software development be left behind?
And thus AI for Software Development is emerging as a viable option that is beneficial for all the stakeholders be it the developers, the business, and the users.
In this LinkedIn Newsletter, we will help you understand the vitality of AI for Software Development and the evident 2025 trend in software development.
If you are a business owner, a software developer, an AI engineer, or a tech enthusiast, then this newsletter is going to prepare you for 2025 and give you the competitive edge that you have been looking for.
A few facts about AI for Software Development
- The global AI market is expected to reach USD 1,811 billion by 2030 at a CAGR of 37.3%.
- AI is expected to contribute more than the combined economies of India and China by 2030!
- AI will be benefiting the most in China, followed by North America by 2030.
- AI has grown at a rate of 109% in India from 2018 and is expected to cross the USD 11,781 million mark in 2025.
- As per a study conducted by Visual Capitalist, ChatGPT is most used in India around 45%, followed by Morrocco (38%) and the UAE (34%)
What is AI Integration in Software Development?
AI integration in the software development process refers to the total infusion of AI features and functionalities in various stages of software development.
As software development projects are inculcating the latest tech & trends to develop software faster and with fewer budgets, the traditional software development model is facing the brunt of it.
While with AI features like,
- ML or machine learning,
- NLP or natural language processing,
- Computer Vision,
- Neural Networking,
- Deep Learning,
- And more, the software development industry can change for the good!
This will be the biggest leap ever, both in the AI and software development industries.
What will be the impact of AI on the future of software development?
When a business has to get software developed, be it a website, an app, or custom software, they rarely have enough time and budget in their hands!
When such a rushed-up software development project comes to a software development company, they face one more challenge along with reduced time-to-market and budget, i.e., integrating the latest features & functionalities to ensure a competitive edge for the business in the future.
Accenture’s 2024 “Reinvention in the Age of Generative AI” Report shows that 46% of companies have accelerated their AI-driven transformation strategies, and these organizations (called “Reinventors”) have seen revenue growth that is 15% higher than their peers. The report predicts that this gap will widen, with Reinventors expected to achieve 37% greater revenue growth by 2026, largely thanks to generative AI innovations​
The only way to achieve all three and deliver even more is via AI for software development using AI for application development, AI for website development, or AI for custom software development!
What are the key benefits of using AI in software development?
Here are the important benefits of using AI for software development:
Augmenting Efficiency
You can easily automate redundant tasks while preventing human errors by using AI for software development.
Boosted Code Quality
Since your code now gets developed after considerations shared by the ML model, it will perfectly garner solutions to the problems that are faced by the target audience of the business.
Plus, it will get debugged faster, as well!
User Personalized Experiences
Using the ML model, you will have to-the-point information of what your ideal user needs and prefers so that the final software will cater the best possible user personalized experiences.
Faster Development Cycles
Since all the heavy lifting is being done by AI, the developers are free to focus on bringing in much more creativity using less programming, which will lead to faster development and modification cycles.
In short, reduced time to market and budget requirements are evident, when using AI for software development.
How to Integrate ML Model in Software Development?
You must have heard of ML, or machine learning, whenever you see AI in two three consecutive sentences.
Do you know what ML stands for?
Well, it is the power via which an AI or artificial intelligence stays intelligent. Just like us humans, AI needs to constantly learn too, and ML helps in achieving the same.
Now let us see the positive impact of ML in software development. But before that, one must know the basics of the traditional software development lifecycle.
Requirements
Before starting a development project, clearly stating all the requirements, such as business goals, end user catering, and technical specifications, is crucial.
Design
In this stage, designers and developers collaborate to create an idea of how the software would look in real time to help the stakeholders visualize it and make suggestions accordingly!
Development
Now the actual development starts, and the developers compile codes in two versions, namely Alpha and Beta.
QA or Quality Assurance
To ensure that the quality of the developed software exceeds the required limits, proper software testing is conducted via manual and automated testers (somewhat AI).
Delivery
After the testing is done, an RC or release version is crafted, which acts as the deliverable software that can be presented to the stakeholders and then users.
Maintenance
Now, when your software hits the market, it is bound to have some changes and suggestions via user feedback. Thus, it is vital to have post-launch support to fine-tune your business software for the world after its launch.
As you can see, there is a lot of scope for mistakes (human errors) at each stage, any mishap will only lead to negative publicity & possible shunning of the brand form the market by the consumers.
Fret not, because we got the next best thing, aka Machine Learning or ML Development model, for your future software development projects.
With the ML Model, AI for Software Development has become the latest fad!
Here’s how it is used:
Goal Defining
Humans or stakeholders just highlight the problems, and the requirements are found out via an ML model using NLP, or natural language processing, i.e., understanding the human language and deciphering it for AI’s understanding.
Data Collection
The ML model needs to learn about the problem and its possible solutions, so it collects data that is controlled and managed by the AI software developers.
Data Curation
Raw data is not at all helpful, and thus it needs to be segmented into data sets made up of AI-friendly data formats along with proper prioritization of the same.
Model Learning
Now that your data is ready, the ML model can start learning from it. Ensure that you give enough learning time to get more than accurate results.
ML Model’s Deployment
After the ML model has gained enough insights, it is ready to be deployed to bring in AI for Software Development.
Apt Management
This stage is somewhat similar to the maintenance stage, where you ensure that the software is kept in the best shape via regular upgrades.
In the ML Model, though, auditing of the current software is done via ML and AI for Software Development using advanced AI methodologies like the deep learning neural network.
So, to simplify the above information, the ML model for software development helps in taking care of research, designing, and post-launch maintenance, while the knowledge gathered by it is used by AI for Software Development!
Although using AI for Software Development is different, it can garner top-notch results in a short time period, so it is worth-it for developers to learn the intricacies of AI-based software development.
AI for Software Development: Best Practices for AI-Powered Development Tools
This next heading will help you in knowing all the best practices that must be followed along with the utilization of specific development tools in AI for Software Development.
AutoML for Model Training
AutoML developed by Google helps in training your ML and AI for Software Development while using minimum effort from its human handlers.
It is designed for developers with no or little ML experience and is helping the software development companies that wish to venture into AI-powered software development.
Data prep is handled by BigQuery platform (Google), or you can upload data in CSV or .Text files!
Then the developers can follow simple training instructions displayed on a graphical interface to train their ML and AI models for software development.
AutoML is paid software, but it’s worth every penny!
TensorFlow for Seamless Deployments
Google created one more tool to facilitate AI for Software Development using TensorFlow!
TensorFlow is free and open source AI tool that delivers better results via constant improvements to its main function.
It helps in training, model tracking, and then appropriate re-training of your AI & ML models.
It is being used for the development of web apps, mobile apps, and even custom software designed for specific business functions.
AI for Software Development: Choosing the Right ML-Lifecycle Management Model (h3)
Now let us talk about the management stage in the ML model deployment for software development and the tools that can help.
Management stage in a ML model is quite essential as it keeps your software up-to-date!
Here are some of the best ML management solutions:
It is an overall ML as well as deep learning development solution from Amazon.
Microsoft is not far behind in catering a cloud environment for apt tracking and management of ML models.
In case you have already decided to use Google’s AutoML and TensorFlow, then Google’s Cloud AI can help you with accurate management of your ML models.
With these best practices, no doubt even your first attempt at AI for software development will be successful!
How to Develop APIs using AI for Software Projects?
API development is an important aspect of any software development project, and since you are getting most of the work done by AI, then why leave API behind?
Google’s Test Analysis API helps in developing APIs by using the best possible NLP techniques.
It helps the DevOps teams to easily process the data shared by the ML models via,
- Syntax analysis to figure out the key areas,
- Entity analysis to figure out important information in the raw data, and
- Sentiment analysis to determine the mood and tone behind the words.
You can craft two types of APIs on the lines of Web Service Rest APIs, and they are,
- Public APIs
They can be used by anyone to benefit from your AI-powered software development features added in that API.
- Private API
It is for your internal usage to help analyze the data and collect KPIs’ (key performance indicators) information.
Depending upon the future usage of your AI models for software development, you can make your APIs!
How does iPaaS, an API management platform, help in AI software development?
APIs need to be constantly audited even after deployment to ensure they are working in tandem with the latest features & functionalities and are able to handle the diverse user demands and requests.
DreamFactory’s API management platform, by the name of iPaaS, can help you with appropriate API management.
Just FYI, a 14-day free trial is available, so go experiment freely!
What are some of the practical applications of AI usage in software development?
Here are a few appropriate examples of using AI for software development in various industries:
Healthcare Software
The healthcare industry is benefiting a lot from AI usage as it helps in streamlining the overall operation by
- Fetching historical medical records,
- Detecting various diseases,
- Possible Drug resistance and reactions,
- Personalized Drug creation
- And more.
E-commerce Software
E-commerce industry is one of the most advanced and user-centric industries that helps users buy products online!
If an e-commerce software can,
- Detect users’ preferences across all digital platforms,
- Catering the products that users are most likely to buy,
- Suggest possible combinations (apparels),
- Allowing virtual try-outs via AR and VR technologies, and
- Provide payment options that are preferred by the users using AI, then it will be the users’ favorite in no time!
Financial Software
Finance companies need to know beforehand about possible frauds, risks, insider trading, and more.
This is only possible if the financial software comes along with the vast predictive analysis power of AI.
Smarter Manufacturing
AI is revolutionizing the production sector as well via,
- Sustainable practices adoption.
- Human error prevention by computer vision to monitor the crucial work stages.
- Analyzing consumer and market trends to improve the products accordingly.
- Health and Safety compliance.
- Blockchain inclusion to provide real-time tracking and thus pin point troubles in the assembly lines.
So, businesses might not know it yet, but they can do way better by using software that is built and maintained using AI!
AI for Software Development: Challenges and Considerations
AI for software development comes along with its own unique challenges and considerations as well.
Here they are,
Data Privacy & Security
Since AI will be using ML to predict user preferences and future trends to maintain the software & more, there are a lot of scenarios when AI will have access to user data.
Thus, users should know beforehand that their data can be used for AI training and betterment. If possible, user permissions can also be gathered.
Skill Gaps
To aptly use AI for software development, your developer team must be skilled to use AI.
If not, then you need at least one AI expert in your developer and DevOps team to ensure that AI can still be used for the best software development and maintenance.
Ethical Considerations
As AI is also built by humans, trained by human-approved data, and then modified by humans, it can always have biases that trickle down from the morality as well as the mentality of the said humans.
Thus, AI should be constantly audited in a regular and impromptu manner to root out any biases that hamper its universal coverage.
Which tools can help you incorporate AI in Software Development?
Here are some tools that can help you utilize AI in software development projects:
It can debug your code and find vulnerabilities in it to make your software top-notch.
It helps with code analysis, bug detection, and even rectifying the code.
It helps in predictive maintenance to ensure secure and reliable software.
It helps in the creation and deployment of AI features for various software applications.
It caters an automated server for CI/CD and general software optimization.
Choose the right mix of AI tools for the best possible implementation of AI for software development!
What are the future trends of AI in Software Development?
According to Deloitte’s 2024 “State of Generative AI in the Enterprise” Report 67% of organizations are increasing their AI investments in generative AI, with notable gains in productivity and cost savings. AI is driving growth in key areas like marketing, supply chain, and service operations, often leading to revenue increases of over 5%. However, issues around data governance and risk management remain critical challenges​ that highlight the need for robust frameworks​.
Now that you are almost ready to use AI for software development, let us share some emerging AI trends that users will be looking for in 2025!
AI & DevOps Integration
If AI is also integrated with DevOps, then it will also help in future collaborations between the development and operations teams.
This will facilitate quick user feedback inculcation and proactive upgrades needed in your business software to ensure its spot as your customer favourite.
Explainable AI
As the AI progresses and becomes much more refined, then it will become much more explainable and easily understandable.
This means that AI usage will increase and reach the masses.
AI-powered CI/CD
CI/CD, or Continuous Integration & Continuous Deployment, has been on the rise and made possible by microservices architecture in software development.
AI can further boost the efficiency of CI/CD as well!
AI-powered Code Gen
Coding has always been a mundane task, even though the whole digital world is built by it!
Imagine if you can use AI to write code as per your requirements; you will just have to verify it.
This will save time and prevent any human errors in the code.
Conclusion: AI for Software Development is the apt way forward for 2025!
There are no two ways about AI usage and its positive impact on any industry.
Software development services are the most traumatised IT services that are facing the brunt of the rapid growth of the digital world.
Nowadays, users are quite aware of the various advancements & innovations in the tech industry and are choosing those businesses whose digital solutions have the latest tech & trends!
Does your software development incorporate AI or not?
Wildnet Technologies is a leading Design and Development company in India that has helped its 4100+ clients complete their 8000+ software development projects using the latest tech such as AI & ML, AR & VR and much more.
We do this via our design & development services, which cater to both web development services and app development services, along with custom software development services.
If you would like to know more,
- Wildnet Technologies: Your One Stop Digital Partner
- How to craft Mobile Apps for Global Outreach?
- Wildnet’s Digital Yum (our thought leadership’s weekly POV on the latest in the Digital Transformation industry)
Connect with us now at info@wildnettechnologies.com and experience the magic of AI for software development!
FAQs
FAQ 1. Why should I consider AI tools for my software development?
Ans: If you wish to beat your competitors in 2025, AI for software development is an essential option.
FAQ 2. What are the best practices for applying AI in software development?
Ans: Some of the best practices for applying AI in software development are,
– Using AutoML for Model Training,
– Using TensorFlow for easy deployment, and
– And choosing the best possible ML model management platform.
FAQ 3. Can you provide a few examples of AI tools used for software development?
Ans: Sure! Some tools that can be used in Ai based software development are PyTorch, Weka, Jenkins, and more.
FAQ 4. What common programming languages can AI be applied to?
Ans: Java, C++, and Python are the most commonly used programming languages for AI.
FAQ 5. How do I get started with AI software development?
Ans: By partnering with Wildnet Technologies for AI-powered software consulting and development services.
FAQ 6. What are the potential cons of using AI in software development?
Ans: Potential drawbacks such as Ethical concerns, Data safety, and Skill gaps can hamper the usage of AI in software development.
FAQ 7. How do I integrate AI into my AI-based software development life cycle?
Ans: To integrate AI into your SDLC, follow these steps:
- Identify Needs: Assess challenges and set AI use cases aligned with your goals.
- Set Objectives: Define clear, actionable AI objectives.
- Ensure Data Quality: Use high-quality internal/external data with proper rights.
- Protect IP: Safeguard AI assets with IP protection mechanisms.
- Secure Training Data: Protect sensitive data when stored externally.
- Supervise AI Code: Ensure quality and security with supervision protocols.
- Use AI in Prototyping: Validate designs and identify flaws.
- AI in Development: Automate code completion and repetitive tasks.
- AI in QA: Automate testing and improve reporting accuracy.
- ML Lifecycle Platform: Manage models with platforms like SageMaker or Azure.
Another option to integrate AI into your AI-based software development life cycle is by opting for AI experts from Wildnet via our IT staff augmentation services.
FAQ 8. How can AI be used in software development?
Ans: AI can be used for requirement identification, designing, coding, testing, deployment, and post-launch support. Thus, AI can be used in all aspects of software development.
FAQ 9. What is the difference between AI software development and traditional software development?
Ans: AI powered software development is faster, more reliable, and quicker to update (CI/CD), while traditional software development is old & thus unable to meet 2024’s business requirements.
FAQ 10. What is the difference between traditional and agile software development?
Ans: Agile software development ensures that changes can happen at each milestone; this helps in keeping changes simple, while traditional software development services inculcate changes at the end of the development, which means reworking the whole thing!
