47% of the organizations who practice digitalization claims to follow a well-defined AI strategy (Source: Adobe). According to a blog posted by wall street journal, AI-enabled tools, by 2021, alone will generate $2.9 trillion in business value. In fact, 80% of enterprises have already invested in AI and uncovered the real intention hidden: go big or go home.
This tremendous growth of AI in different sectors of technology has already shown its colours in software development. In experts’ opinion, every aspect of the software development life cycle is likely to be benefited by AI. Right from predicting project timeline and software delivery estimation to bug fixing, coding assistance and testing, AI can assist developers in varied ways.
How many spheres are there in a Software Development LifeCycle?
The six- significant software spheres development where AI can help are- Software design, Software testing, automated code generation, GUI testing, and strategic decision making.
But How? To know more, Dig Deeper!
1. Software Design
Planning a project and designing it from the start in software engineering need developers to apply their specialized learning and come up with alternative solutions before coming down to an absolute design.
A designer begins with visualization, and after that, move back and forth on the investigating plan until they reach the desired solution. Settling on the right plan for each stage is a tedious and mistake-prone action for designers.
A few of the developments in this field have demonstrated the advantages of equipping traditional methods with intelligent specialists. The point here is that the operator acts as an individual partner to the client. This associate gives the most suitable direction and a proficient method for project designing.
The most significant role of AI in the Software Development Life Cycle(SDLC) is demonstrated in testing. AI in software testing is basically categorized into the following:
- AI-powered tools for testing
- AI-based products and other deliverables for testing
In either way, AI enables development companies to transform software testing into a robust self-driving exercise with the least manual interference. For now, most of the testing tools started incorporating AI capabilities partially in their package. For instance, both Eggplant and TestComplete tools in their recent releases included a few AI-based features. Does that mean we no longer need testing teams? Nope, not quite.
Software testers need not fear AI because technology isn’t going to replace them. Instead, they will be given tasks of finding practical ways of deploying smart technologies. This will help in bug identification and achieve better results.
Even if software companies wish to replace entire testing teams with AI-based applications, they can’t. While smart applications can deliver precise results, they lack documentation, management, performance, scalability, and security. So the middle ground is QAs Evolving to accommodate AI.
3. Strategic Decision Making
Usually, developers have to go through a long process to decide what features to include in a product. However, an AI solution trained on business factors and past development projects can analyze the performance of existing applications. It can help the engineers and business stakeholders to find optimum solutions with minimum risk.
4. Delivery Estimation
Any mobile app development company that has experience of working on numerous complicated projects can easily give a near-perfect estimate of the software delivery. Though, some factors like a lot of coding errors and accommodating client requests, can lead to unwanted delays beyond the delivery schedule. Artificial Intelligence (AI), in this respect, can give the most precise delivery time as the analytics is capable of analyzing a lot of data from similar types of projects.
5. AI-based Assistants
AI-based programming assistants have already gained popularity among experienced developers. The assistant can continuously help developers with relevant code examples and recommend related documents. Such tools can help in the reduction of the workload and improvise the developer’s focus on more essential aspects, like delivering the better user experience.
6. Sophisticated Compiler
In software development, the role of compilers is to convert the code written in a high-level programming language to machine language. An intelligent compiler while doing this doesn’t need the source code, and this makes the process faster. With AI, the code compilers can complete a task of regenerating code for the hardware in a few hours instead of months.
So How Should Engineers Prepare Themselves for this AI Culture?
In an interview, David Wood and Peter Jackson, members of London Futurists share the influence of AI on an engineer’s life and give a brief guide on adapting the AI culture.
The three skills that everyone needs to be equipped with is how to live with robots, how to work with them, and lastly, how to operate so that the man and robot interaction is better. And frankly, an Engineer needs all of these skills.
Also, the ability to figure out the right community, partners, and people will help in staying updated with the current trends.
And last but not least is the skill of emotional intelligence (EI). With the passage of time, EI is getting critical since the courage to embrace change and willingness to try something risky is going to get stuck in a rut. At times, it is known as a soft skill. But candidly speaking, for success in the future, we need this particular soft skills.
Learning how to learn instead of sticking to the old manner of working is the need of the hour. Throughout his engineering life, he has worked consistently to adapt to the changes in technology. This proves that the life of an engineer is never static. One has to keep learning new skills to match changes in the ways where developments happen. Be it software or any other sort of engineering; there will be several technological changes which will affect the course of people’s career. Hence, the job of engineers, in a kind, is to make themselves redundant.
Software engineering has seen a massive transformation over the past few years. In combination with AI, the development cycle becomes easier and more reliable. Also, the power of developers multiplies many times with its designed tools. Software Professionals who are worried owing to the transforming nature of their roles have to continuously update their skill set for staying relevant in the business areas and align their career with the changing market scenario.