How AI is driving the future of technology

How AI is driving the future of technology

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Since the first computer was created in the mid-20th century and Apple’s first iPhone debuted in 2007, technology and the software development that comes along with it have revolutionized our world and daily life.

And the challenges of the global pandemic and its aftermath have accelerated the need for these technology solutions at a pace never seen before.

While the need is increasing, software development has become enormously challenging; in some respects, we are at the extent of the cottage industry architecture it has been built on. The Great Resignation has hit this industry hard.

For example, in India — a primary source of the world’s tech talent — attrition rates rose above 30% in 2021 while wages surged more than 50%. Simultaneously, the war in Ukraine has essentially cut off 450,000 workers in Russia and Belarus from western economies. 

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So where do we go from here?

Adaptable systems and processes

This accelerating pace of technology coupled with major socio-economic and political shifts are dictating that we not only build differently, but also build with intelligence. We need more systems and processes that can adapt, learn and apply these learnings to address the changing needs of businesses and consumers — and not just today but tomorrow. 

Artificial Intelligence (AI) has already become a main driver of emerging technologies, from big data to robotics and IoT. Based on user history, experiences and current usage pattern displays, AI can quickly and efficiently address the demands of multiple users and usages, based on learning principles and natural language processing (NLP) techniques.

This technology enables systems to access and deploy huge amounts of data and processes without the need for heavy human intervention. And as more intelligence is built, AI cannot only drive enhanced results, but predict and plan for future implementation. 

Today, AI is further transforming the software development space and making it easier for businesses of all sizes to simply build. Thus, AI opens more opportunities for both small businesses and enterprises to develop software more quickly and efficiently, and ultimately grow and engage through intelligence. 

But how?

Intelligence and decision-making

Intelligence is gathered and decision-making is driven through an AI-powered assembly line. Much in the same way a traditional assembly line works, technology development can benefit from what came before.

This new assembly line brings together learnings from frequently used features to build more affordable software and applications at speed and scale. Coupled with human talent, software can be delivered at 6X the speed and one-quarter of the cost. 

AI’s functionality is further amplified in coding, a process wherein even a missing parenthesis or semicolon can cause a serious error. AI systems can be trained to automatically spot these mistakes (and more grave ones!) and suggest replacements, saving hours of human time that would otherwise be spent debugging. These are hours humans can spend on what we do best: Thinking creatively about how to solve problems.

This reimagined assembly line has emerged as the most strategic way to automate development tasks that otherwise involves layers of human intervention and can drastically impact ROI.

Intelligence and efficiency

Any software developer knows that countless maintenance hours and dollars are spent on managing redundant features on the backend. But AI can reference data across multiple sources to identify these redundancies, which streamlines ongoing maintenance while saving work hours and limiting spending.

For example, AI can predict the code that a developer is going to write, which can cut down keystrokes by as much as 70%. Reusing code through AI can save businesses a significant amount of time and money.

AI is taking testing to the next level in terms of both accuracy and speed, catching most errors before software goes to the test phase. By running more variable tests, issues that could occur when programs are fully operational are more likely to be caught.

Intelligence and the human touch

Many software projects are scrapped before they ever see the light of day because user demands are not being met. Development platforms are under pressure due to high demand, rising costs and a shortage of competent developers.

The process of gathering, tracking and validating what users need is labor intensive. With AI, developers don’t need to sift through pages of analytics and lines of code to become more effective. AI can help showcase user behaviors and needs, making it easier for developers to fulfill those needs.

But the human touch remains essential. At the end of the day, machines are built to serve humanity’s intentions. The ability of AI to comprehend and convert human intentions into software instruction is what will make the next generation of no-code software development an eventuality.

With AI managing the vast swathes of repetitive and often mundane workstreams related to app development, humans can then be free to create, innovate and problem-solve. 

Sachin Dev Duggal is CEO and cofounder of Builder.ai



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