AI Myths Vs Reality

Artificial Intelligence has taken the world by storm. Be it industrial automation, chatbots, virtual assistants on various websites, self-driving cars, spam filters, voice assistants, healthcare management assistants, social media analysts, etc. The pandemic years of 2020 and 2021 saw a further surge in the demand and usage of AI in various industry segments. As per the study conducted by Gartner Inc,

It took decades of evolution for artificial intelligence to reach where it is today and there is still a long way to go. Here is a simple representation of the timeline of AI evolution.

Historically, it is a well-known fact that anything that generates hype and is not fully understood by the majority of people is deemed a threat to humans. Of course, sci-fi films like “The Terminator”, “The Matrix”, “Eagle eye”, etc add to such misconceptions. Humans are naturally resistant to significant changes and acceptance is not that easy. Humans tend to weave myths around things that they don’t understand.  AI is a victim of such myths. Many misconceptions about AI are floating around, and we are addressing 5 of them here. Reach out to us if you wish to add more to the list.

Myth #1: Artificial Intelligence, Machine Learning, and Deep Learning are The Same

Artificial intelligence is the superset of machine learning and deep learning.

Machine learning’s prime focus is learning and aiding in decision-making with the help of pattern recognition technology and predefined algorithms. Pattern recognition and ML algorithms help to understand, learn, process, infer and predict, based on past data and new information. AI improves as ML improves.Deep Learning is also called scalable machine learning. It helps machine learning algorithms by extracting zeta bytes of unstructured and unprocessed data from data sets.

Myth #2: AI will Jeopardize The Future of Human Labor

AI enhances productivity by assisting and reducing human efforts by automating the repetitive process and freeing them up for other tasks.

AI has replaced the “tasks” not “people”.

We have explored AI and Human involvement in software in detail. Read our blog “Will AI completely eliminate human involvement in testing?”

AI needs a certain level of human involvement. For example, AI engineers write complex algorithms and keep upgrading them. Also, even though it appears that a machine is learning on its own and generating results, in reality, experienced data scientists collate datasets for the algorithm’s consumption.
There is a rising need for skillsets related to AI. Current skills need to be upgraded to match the requirements. For example, besides the obvious need for AI engineers and data scientists, there is a demand for analysts, information architects, content experts (like dialog designers for voice assistants), user experience analysts, etc.
Therefore, the rise in AI has changed the roles and created new ones.

Myth #3: AI is Smarter Than Humans

Erik Brynjolfsson, the director at the MIT Initiative on the Digital Economy, has talked in detail about humans and AI. You can read it by clicking here.

Any AI system is as smart as its algorithm and depends on the quality of data it relies on to learn, analyze and generate results.

The training data that is fed to any AI system should be of high quality, structured, and free from irrelevant information. And, who writes the program that works on this data? A human.
That calls for a niche skill set further substantiating our claim that AI will evolve the nature of skills and jobs.

AI is of course faster, precise, and more consistent than humans and it does not suffer from work fatigue.

Myth #4: AI Systems are Very Complex and Extremely Difficult to Integrate With Current Operations

Conceptualizing, designing, and building an AI system from scratch can be an expensive, complex, and time-consuming process for some organizations. However, there are ready-to-plugin tools already available in the market. There are multiple options to pick from ranging from open-source tools to customized ones. It is up to you to make the wise choice keeping in mind the long-term ROI. Webomates CQ offers superior test execution and test management services. Read our blog “How to choose the right test automation tool” which can help you in making the right decision.

Myth #5: Not Every Company Needs AI

Many organizations have a misconception that investing in AI-based systems is not worth the effort and is not cost-friendly. Some may think that their process or problem at hand is not complex enough to be solved by AI. That is where they are wrong.

AI can work on a range of processes and problems by simplifying them and making them more efficient and faster. They help in resource management by easing off the load from your human resources, which can then be redirected towards other productive tasks.

Knowingly/unknowingly AI-based tools have infiltrated all domains. It is omnipresent in different fields like defense, medicine, engineering, software development, data analytics, etc.

How AI has Changed The Testing Landscape

The introduction of artificial intelligence in software testing opened doors for faster and more reliable testing solutions which helped in delivering high-quality end products. DevOps augmented with AI is a perfect solution to improvise and speed up CI/CD/CT pipeline. AI-Ops has improvised the overall software testing scene as depicted in the following figure.

Isn’t this an impressive list that entices you to start considering the options for the testing needs of your organization?

The market today has a plethora of tools that offer AI-based testing services. But, how do you know that you are making the right decision in picking a tool?

• Does it truly tap the potential of AI and harness its benefits to provide a “complete” testing solution?
• Will it be easy to integrate without disrupting the existing CI/CD pipeline?
• Are there any hidden costs? What if the team needs an extra skill set to use it?
• What if the overall cost of maintenance starts growing with time?
• How tangible are the results? Will we be able to provide detailed analysis to business stakeholders to justify the investment?

Put your fears to rest.
We at Webomates have developed a revolutionary AI-based automation testing tool that can be integrated seamlessly with a customer’s CI/CD pipeline within a matter of hours.Webomates CQ leverages the power of 14 AI engines and provides the following services at different levels of the software testing process.

Webomates has a competitive edge over many others with its patented intelligent automation and analytics tool, which provides value for money to its customers. Additionally, we provide service level guarantees to all our customers.

Partner with us and reach out at info@webomates.com.  To know more about our services click here and schedule a demo.If you liked this blog, then please like/follow us Webomates or Aseem.

Tags: Agile, Ai Myth, AI Testing, AI Testing Myth, Artificial Intelligence, DevOps, Intelligent automation, Test Automation