Is There a Risk on Manual Testing due to Artificial Intelligence & Machine Learning?

The intervention of new technologies like the Internet of Things, Augmented Reality, Artificial and Machine Learning have changed the course of human life towards rapid progression. However, this intervention also gives birth to a very high scope of job losses and a negative impact on the manual testing community.

It is being estimated that the evolution of Artificial Intelligence and Machine Learning could wipe out nearly 73 million US jobs by 2030 and almost 44% of workers are prone to get affected. The above figures clearly show that it’s important to asses the impact and to clarify whether the rapid technological progress and innovation can really threaten the manual testing community.

The impact AI & ML is definitely being felt across the global economy and industrial usage has increased rapidly over the period of the past few years. This makes it a well-known fact that AI, ML, intelligent robotics and other forms of ‘smart automation’ are advancing at a rapid pace and have the potential to transform the digital ecosystem. However, it’s also true that since it is the biggest digital evolution since inception it also has the potential to offer outstanding benefits by boosting the economy, reducing the time-to-market, increased accuracy and improved rate of production.

The manual testing industry has been completely disrupted by the AI based software test automation and it would be an interesting thing to see that whether this flux will create a job threat or will create new opportunities for the existing workforce. These ongoing achievements and advancements in intelligent robotics, ML and AI are defining the new age of automation based software testing services. By leveraging the technology the machine are becoming even more capable and have started outperforming the human counterparts across a range of activities, which earlier required manual capabilities.

 

Effect on Automation Testing

Continental cuisine or Thai food? Luxury sedan or spacious SUV? This is just a matter of choice and is exactly the same when it comes to choosing between manual testing and software automation. The intervention of artificial intelligence and machine learning in automation simply means intelligent automation with less human interference and maximum capability. 

Automation through machine learning and artificial intelligence gives rise to smart automation. This newly derived intelligent automation executes faster, is trained to detect flaws, suggests solutions and makes a pipeline for the next series of software test automation services to be followed. This not only makes software test automation quicker but also more precise. This AI based automation testing approach improves the quality of the tests.

 

Advantages of AI

Zero unattended errors – With AI’s intervention, manual testers can relax and let AI take control on all defects, leaving no scope for unattended errors. As soon as a bug is detected the tester gets notified for the same, with a suggestion to fix the potential error.

High accuracy – To err is human. Manual testers are prone to make mistakes and there is always a scope of missing out on something important. Accuracy was one of the top most reasons why AI became popular in the software testing industry in such a short span of time. With machine learning and AI, the task gets performed exactly as intended by the tester even in a repeated mode with zero scope of errors.

Continuous feedback in DevOps – AI & Machine Learning detects errors at the primitive stages and suggests necessary fixes in the form of actionable messages for continuous delivery in DevOps. The findings can then be transferred to the DevOps team to ensure flawless functioning.

Effect on Security Testing

It is expected that the global cybersecurity market is expected to rise by an additional USD$ 248.26 Bn by 2023. The figures directly indicate the scope of artificial intelligence in digital security. Security is undoubtedly the most important concern due to the vastness of the digital ecosystem. Proper security implications have the scope to reshape the digital future and with the complexity of modern software architecture and its adaptability, artificial intelligence is certainly the best option to safeguard the system.

Security testing, also known as penetration testing, is an important part of the network architecture when it comes to comprehensive cybersecurity. AI with automation involved significantly helps in pen-testing at a continuous rate. This helps organizations to actively safeguard and efficiently take care of their digital infrastructure.

Advantages of AI

With white hat techniques and AI powered security tools, security testers can execute smart hacking techniques to identify the loopholes in their product. The most effective techniques are a combination of threat intelligence, vulnerability scanning with human expertise and artificial intelligence which identifies the severity of the breach through attack simulations. These techniques are quite popular in the testing community as it increases the overall effectiveness of the system.

Effect on Performance Testing

With the increasing complexity of the modern-day applications, performance testing and application monitoring has found a huge scope in improving the effectiveness of the test with AI. A standard performance testing scenario starts with the analysis of the architecture, which is then followed by the virtual load hitting the CPU indicating the response time, memory usage, CPU utilization etc. AI at this point acts as the brain which takes the overall control including the test design, scripting and execution. This saves time for the engineer to focus on other aspects of the testing such as UI design and more.

AI also helps in creating codeless automation test scripts so that performance test scripts can leverage natural language processing (NLP) which makes the process easier. The combination of AI-ML also helps in reducing the overall time taken by making the system learn the data without programming. The AI based testing thus develops advanced capabilities such as automatic healing and intuitive dashboarding. The recorded test sessions thus derived can be used to test the next set of data with minimum or no coding required.

 

Is AI really a threat?

No, in fact it’s a boon for the manual testing community. It is projected that by 2020, AI will create 2.3 million more jobs. By effectively leveraging AI, QA testers will transform the overall testing process, enhance their skills and will effectively contribute towards increasing the ROI. 

The AI based app testing services is definitely projected to be promising and more effective. The QA testers would surely improve logical reasoning, business intelligence, mathematical optimization, algorithmic analysis and gain new skills while working in-sync with the technology. This impact will ensure higher investments on skill development by the market leaders. Thus, the manual testers will eventually move to the leadership roles where they will teach and monitor the technology. Artificial intelligence would be a smart assistant to its human counterpart.

To conclude, we feel that we’ve answered the raging ‘threat question’ and confidently state that the appropriate use of AI & ML in the testing industry will definitely help the young testing community to improve, progress and innovate and if you are a hark working professional nothing can disrupt your way to success. To quote “Our intelligence is what makes us human, and AI is an extension of that quality.” -Yann LeCun, French-American Computer Scientist, Vice President, Chief AI Scientist at Facebook.