Anmol: Welcome to the Unthinkable Tech podcast, the go-to source for the pulse on technology that’s shaping our future. I’m Anmol Satija, and today we’re diving into the digital currents that are transforming our world. Imagine a world that anticipates your needs before you even voice them, a realm where convenience is not just expected, it’s embedded into the very fabric of our digital experiences. This is not the stuff of science fiction; it’s the reality unfolding around us, thanks to the relentless evolution of artificial intelligence in our digital platforms.

How AI moved from research labs to everyday experience?

Anmol: AI has moved from the backrooms of research labs to the forefront of user interaction, revolutionizing the way we shop, socialize, and streamline our lives. But what does this mean for the future of digital platforms? How is AI reshaping the landscape of technology, business, and even our own human behavior? Today, we will peel back the layers of this digital evolution, and to help us navigate this complex terrain, we are joined by Shubhang Malviya, lead of AI center of excellence at Unthinkable Solutions.

Shubhang: Thank you, Anmol.. Thanks for the invitation. It’s great to be here to talk about this exciting topic.

Product evolution: From human instinct to AI-driven decisions

Anmol: Let’s jump right in. Shubhang, We’ve seen software product evolution move from human intuition to data-driven strategies, and now AI is at the forefront. What’s your take on this evolution?

Shubhang: You know, it’s been quite the journey for software development. I remember the good old days when it was all about that human gut and expertise. CTOs and product managers were like artists, using their intuition and experience as their paintbrush, crafting products that they believed users would love. It was personal, it was hands-on, but let’s be real—it had its limits. Bias could sneak in, and let’s not forget, we’re only human; there’s only so much data we can process before our brains go numb.

CTOs realized that not all gut decisions could help them make their software products stand out from the competition and win markets. They needed real user data to make better decisions. So they started capturing the data through. You know, different tools and mechanisms.

This led to the data revolution! Suddenly, companies had access to mountains of user data. It was like striking gold for product development. But (and there’s always a ‘but’), we were kinda like kids in a candy store—overwhelmed by the choices and not quite sure what to do with all that sweet, sweet data.

And now, we’re in the age of AI, where the game has changed once again. AI is like having the world’s smartest expert who is always available to analyze data at scale.

Let me share a real business situation here. So that everyone can relate

We had this customer from the oil and gas industry, who was using sensors to detect anomalies in order to prevent downtime of their oil refinery. The downtime would cost them millions of dollars. The sensors were collecting a vast amount of data every second, however, hiring a specialized person to analyze and take necessary action within time using that data was a costly and time-consuming affair.

We developed a predictive analysis solution using AI and ML algorithms, which could analyze data in real-time and detect anomalies before they even occurred. This eventually resulted in an 80% reduction in unplanned downtime.

So what I mean to say is that AI crunches numbers like anything, spots trends that we would normally miss, and even predicts what users might want next. It’s revolutionizing how we build products, making things more efficient, more objective, and let’s face it, it’s pretty damn cool.

Businesses should ensure AI is fair, transparent, accountable, and respects privacy, consent, with human oversight and regulatory compliance.

Building ethical & responsible AI systems

Anmol: Absolutely, what a fascinating evolution it has been. And the example you gave of the oil & gas industry use case. Really does exemplify the transformative power of AI in decision-making.  However,  with the growing role of artificial intelligence, how can we avoid biases or creating ethical dilemmas?

Shubhang: Absolutely, that’s an important issue to talk about. To make sure that AI doesn’t accidentally pick up any unfair biases or create tricky ethical situations, we need to feed it with a really varied bunch of data. 

It’s like making sure it gets a holistic essence. You know, At the same time, we as businesses should also ensure AI is fair, transparent, it is accountable, and respectful of user privacy.

Again, let me quote a real-world instance related to this. We recently happened to develop an automated speech recognition solution for court proceedings in Nigeria. It is a known fact that the modulation, dialects, or certain words in one’s speech can have negative or positive annotations. In order to make sure that the AI system understands the modulations and behaves ethically, we trained the system with a diverse set of accents, dialects, and voice modulations to prevent bias arising from parts of the speech.

And that is why, When we’re talking about AI behaving ethically, we’ve got to stick to some core values such as being open about how it works, making sure someone can answer for its actions, treating everyone fairly, and keeping people’s private stuff private.

It’s also super important to get different kinds of experts in on the AI-making process. Like, having ethicists and social scientists around can be a game-changer. They’re the ones who can spot potential ethical headaches early and help us figure out how to avoid them. 

We cannot miss one important aspect that human oversight is needed at every stage this can be done by setting up correct monitoring, especially when it is making big decisions that can really impact people’s lives. We need to create an explainable AI ecosystem that helps us trust it more.

Speeding up product innovation with artificial intelligence

Anmol: I really appreciate that comprehensive breakdown. Your insights are spot on. It’s essential to cultivate an AI landscape that’s rich in diversity, not only in the data.

Moving further, I want to ask how AI can enhance the speed of product innovation.

Shubhang: AI is like this multi-faceted tool that is opening up a whole new world of possibilities at each stage of product evolution. However, one aspect where most businesses struggle is to identify when and where to use AI in their product evolution lifecycle. Before integrating AI, organizations need to ensure there’s a clear problem or opportunity that AI can address. 

Additionally, AI systems typically require large amounts of data to learn and make predictions. So as a business, you need to consider whether you have access to the necessary data to train your AI models effectively. Having said that, let’s discuss a few areas where AI can make an impact.

During the initial planning phase, businesses need to identify market needs, user preferences, and potential areas of innovation using appropriate tools. Analyzing historical data, customer feedback and competitor performance can inform the scope and objectives of the software project. 

Employing data-driven AB testing techniques can assist in optimizing the software design by analyzing patterns from previous design successes or failures. This can lead to more user-friendly interfaces and efficient system architectures.

How AI Streamlines the SDLC?

During the coding and development phase, AI can analyze code repositories to identify common coding patterns and suggest optimizations or flag potential issues before they become problems.

During the testing stage,  AI tools can analyze past test cases and results to predict where new software is most likely to fail, enabling targeted and efficient testing. It can also be used to generate test data and automate regression tests.

Anmol: Yeah, AI not only speeds up the innovation process but also adds a level of precision and personalization that was previously unattainable. As AI technology continues to evolve, we can expect even more sophisticated applications that will further transform the landscape of product development. It’s an exciting time for businesses to leverage AI, and those who do so effectively will likely find themselves at the forefront of their respective industries.

Strategic AI Adoption: Finding the Right Business Use Cases

So now coming to the next important question – Taking into account the diverse range of tasks in business operations, each with distinctive complexities, time necessities, and skill prerequisites, how can leaders judiciously evaluate the segments for AI integration?

Shubhang: So If businesses want to integrate AI effectively, they need to align it with their strategic objectives. It’s essential to invest in technology that adds value rather than chasing trends.

Start by evaluating your organization’s readiness: you know IT infrastructure, data organization, and team skills. 

Next, identify labor-intensive, repetitive tasks that could benefit from automation. Assess which tasks consume excessive time or require specialized skills—that’s where AI can enhance efficiency.

Another important aspect is Data, which is crucial for AI effectiveness. Leaders must ensure they have access to high-quality data. Next, businesses should Consider the return on investment when implementing AI. Begin with small pilot projects to fine-tune the approach. Monitor performance meticulously.

Let me give you an example, we once worked with a client in the e-commerce sector who was interested in understanding the sentiment around their products by analyzing mentions and reviews. 

Although it was a relatively modest project, it marked the beginning of their journey with artificial intelligence. By leveraging the insights gained from this initiative, they were able to make well-informed decisions. Consequently, they have now incorporated AI into many of their business processes.

So what I want to say is, as successes accumulate, plan for larger-scale integration, always considering the impact on infrastructure and operations. Throughout, foster a culture embracing innovation and change, preparing and supporting your team for the AI transformation.

Anmol: Absolutely Shubhang rightly said, it’s clear that integrating AI isn’t just a plug-and-play scenario—it’s a strategic move that requires thorough preparation and a strong focus on aligning with the company’s vision. And I couldn’t agree more about starting with pilot projects; they’re the perfect proving ground for innovation. And it would be interesting to see how companies would make AI their integral part.

Why people will always be the decision-makers?

Now it’s time to ask the big question that’s on everybody’s mind. Can AI completely replace human decision-making? 

Shubhang: See AI is undoubtedly amazing and has made a significant impact on how businesses work. However, Current AI systems are often designed for specific tasks and lack the broad adaptability and understanding, that You know! characterize human intelligence. 

Currently, It heavily relies on human input and supervision. And if we talk about the futuristic aspect- rather than replacement it is more about collaboration. The future lies in collaboration between humans and AI, where the strengths of both can be leveraged for mutual benefit. Taking into account all the points we have talked about earlier related to responsible AI, establishing ethical frameworks, and implementing regulations we can make sure AI serves human purposes in the most effective way. 

So I must tell you it’s not here to take over. It’s here to boost what we humans do best—create, imagine, and make ethical choices. We’re still the captains of this ship, steering it towards innovation and responsible development.

Anmol: Totally agree, your remarks truly capture the essence of the current state of artificial intelligence and its trajectory into the future. It’s refreshing to hear a voice that acknowledges both the capabilities and limitations of AI. With this, we come to the end of the episode. This has been an incredibly insightful Discussion Shubhang. Thank you for answering all the questions so patiently. You made it look so simple. 

Shubhang: Thank you, Anmol, it was a pleasure to be here. 

Anmol: And thank you, listeners, for tuning in. We hope today’s conversation added some flavor to your thoughts on how AI is revolutionizing the digital product arena. Don’t forget to subscribe for more interesting tech topics, and visit our website for more details and we’ll catch you on the next episode of The unthinkable tech podcast! Till then take care and stay tuned!