Be mindful of not removing the human touch while Integrating AI: says Deepak, Pegasystems

Deepak discusses leveraging Gen AI, Pega's Gen AI blueprint, cultural shifts in Indian enterprises, addressing job role threats, and balancing automation with the human touch in customer interactions.

Punam Singh
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Deepak Visweswaraiah, VP, Platform Engineering and Site Managing Director, Pegasystems

Is AI here to replace job roles or enhance human capabilities? Deepak Visweswaraiah, VP, of Platform Engineering and Site Managing Director, Pegasystems, an expert in AI and automation, shares insights on how organizations can harness the creative potential of Generative AI technology, Pega's Gen AI blueprint, cultural shifts needed for Indian enterprises to embrace Gen AI, addressing potential threats to traditional job roles, and balancing automation efficiency with maintaining a human touch when interacting with customers.


Additionally, he discusses disruptive technologies like Generative AI, autonomous enterprises, and the Internet of Things that will redefine automation in the coming decades.

DQ: How organizations can harness the creative potential of Gen AI technology beyond automating routine tasks?


The potential for organizations to leverage generative AI technology is enormous, which explains its widespread adoption in the market. It can be applied across various domains, not limited to any specific one. Its potential can be harnessed in industries ranging from BFSI to oil and gas to healthcare, among many others. While automating routine tasks is a common application, the real value lies in going beyond that—using this technology for more creative endeavors. Allow me to share a few examples.

One capability is content creation, facilitated by Gen AI's access to vast data, its processing abilities, pattern recognition, and content personalization. For instance, language translation has become significantly easier; you no longer need to know French to create French content. Gen AI can provide over 90% accurate translations. Recently, it has advanced to creating videos based on user requests, such as generating a video of someone in a park on a summer morning. Hence, content creation is a significant application.

Secondly, in terms of design and innovation, leveraging Gen AI can accelerate brainstorming for design and innovation. It enables the brainstorming of new product and service ideas and helps analyze market data to create business cases or prototypes. A notable example is the "Pega Generative AI Blueprint." This tool combines Pega's 40 years of knowledge in solving complex workflows with the power of generative AI. Clients, partners, or anyone visiting our website can generate a blueprint for an application without prior knowledge, showcasing its role in design and innovation.


Thirdly, we can leverage Gen AI for training and development, or L&D. Personalizing training involves using AI to determine employees' skill needs. For instance, in edtech, personalizing materials for different user personas is essential. It can also develop interactive simulations, known as Socratic learning. An example from Pega is training customer service agents using generative AI within the application. The AI simulates a customer to train representatives on how to interact effectively. Voice AI is another valuable integration for Socratic learning. Additionally, addressing security risks and vulnerabilities is a significant use case for generative AI. While we're only scratching the surface, the opportunities are vast.

DQ: What is Pega's Gen AI blueprint? How does it align with industry practices, and what sets it apart from other products in terms of transparency and accountability?

Pega blueprint enables teams to accelerate their journey from idea to implementation. Say you have an idea, how do you take it to implementation? Pega's blueprint accelerates that process. Think of it as a tool for business leaders to transform application ideas into interactive applications.


Think of it as building a house. You don't just go out and start pouring concrete and building walls, right? First, you consider what you want in it—how many bedrooms, the kitchen layout, etc.—and jot down all your requirements. Then, you consult an architect or expert to lay it out for you. After it's laid out, you can tweak what you don't like or move things around. Now, you have a blueprint that you can give to a construction expert, who will mark things out and start building.

That's exactly how a Pega Gen AI blueprint works. It broadens access to application design, enabling our clients and partners to quickly learn how to design and optimize applications. Unlike other generative AI applications or development tools that create more code, we focus on delivering value and optimizing workflow design and decision-making. The blueprint covers all workflow stages in Pega portlets, guiding users through the entire case lifecycle. Users input initial requirements, and the blueprint generates case types, data models, data sources, and personas. It produces a blueprint in PDF format for discussion with IT experts or a JSON blueprint for import into a Pega environment. This process, which typically takes weeks, can now be done in minutes, jumpstarting application deployment with a Gen AI blueprint.

DQ: In the Indian marketplace, what cultural shift do you see as necessary for Indian enterprises to embrace Gen AI or hyper-automation?


I've always viewed India's environment and overall ecosystem from two angles. There's a segment of people who leverage generative AI and other such technologies to build products consumed by corporations within India or anywhere in the world, and the other is adopting.

In this segment, where people leverage such technology to develop things, we are doing very well, and positioned excellently, and people have embraced this path. I recently read a report stating that one in every six lines of code written in AI is from India. So, I think we are doing well in that regard. However, when it comes to adopting technology further, I think that's where we lag as a country. Here are a couple of things that come to mind regarding what we need to do in the country to be at the forefront, not only in developing technology but also in adopting it for the best use cases or maximum efficiency.

Firstly, it's about a mindset shift—how we think and what we do. Many Indian companies view Gen AI or automation as a means for cost-cutting rather than value creation. Moving beyond seeing automation solely as a cost-cutting measure and focusing on how we can leverage hyper-automation and generative AI to create value makes a huge difference. It's about our ability to embrace innovation and experimentation, acknowledging the need to upskill the workforce.


Secondly, it's about collaboration and trust concerning AI systems. How do we establish a human and AI collaboration without fearing job loss? We want to foster a culture that views humans and AI as complementary forces, working together to achieve desired outcomes. To achieve this, we need to build enough trust in AI and implement the right governance models to ensure transparency, so nobody worries about leveraging AI as a technology. This is the second shift we should focus on in the country.

Lastly, I would emphasize being agile in adopting such technology. I think one area where we lag is in our agility in adopting such technology. We need to cultivate a culture of data-driven decision-making, enabling organizations to be agile and move as fast as the market.

Speaking specifically about India, we discussed language barriers earlier. When it comes to content generation, considering the multitude of languages spoken in India, Gen AI presents a fantastic opportunity to overcome some of these language barriers within the country. Furthermore, there's the potential for investment in infrastructure development to leverage such technology. In conclusion, embracing a mindset shift, fostering a culture of collaboration and trust, and prioritizing organizational agility are key factors that will help us stay at the forefront of leveraging such technologies.


DQ: As Gen AI advances, how do you address the potential threats posed to traditional job roles?

When considering threats from generative AI, the foremost question you'll encounter is, "Will people lose jobs as generative AI automates routine tasks?" With increasing complexity, repetitive and routine jobs are at risk, a well-known fact. It's important to understand the nature and location of this risk. The second threat from Gen AI concerns skill gaps. The emergence of generative AI has or will necessitate a shift in people's skills. Jobs will likely require more creativity, critical thinking, problem-solving abilities, and adaptability to complement existing knowledge. This underscores the human aspect that AI cannot easily replace—human creativity and intuition. While AI can automate repetitive tasks, it cannot match human creativity and intuition.

Software engineering heavily relies on creativity and innovation to design and architect systems at scale. I don't view new technology as something that eliminates jobs. We've undergone several technological transformations before, and they've never taken anything away from humans; instead, they've helped us perform better. So, how can we make this transition smoother? We discussed earlier how we can ensure collaboration between humans and AI. Instead of seeing generative AI as a replacement, we should view it as a tool to enhance human capabilities. We should focus on redesigning workflows, software, and operational activities to leverage its strengths. Rather than eliminating jobs, we should redesign them. We can analyze existing jobs, identify routine tasks that can be automated, and empower individuals to focus on higher cognitive skills and innovation. Building a culture of lifelong learning is essential to navigate such transformations. We need to learn the skill sets required to leverage generative AI effectively in our environments. Additionally, transparency and communication with employees are crucial. We shouldn't fear this change; instead, we should embrace it and proactively address it. Otherwise, someday, someone else will do it for us. That's the mindset we should adopt.

DQ: How can enterprises balance automation efficiency and maintaining a human touch when interacting with customers?

Deepak: Organizations today must consider striking a balance in terms of how much to automate and what to automate. In my opinion, enterprises need to be doing a couple of things.

One aspect involves leveraging automation for tasks that are repetitive or straightforward, such as data entry, scheduling appointments, or creating routine updates. This frees up human agents to focus on more complex issues. For instance, a travel website might use a chatbot to handle frequently asked questions, but when it comes to changing itineraries or addressing emotional situations, human intervention is essential. Implementing omnichannel customer engagement allows customers to seamlessly switch between channels, ensuring that human interaction is available when needed.

Companies should be mindful of not simply removing the human touch when it's necessary, especially in emotional situations. Building relationships requires human intervention, as AI isn't yet capable of developing genuine connections. Corporations must empower their employees to interact with clients, fostering relationships and ensuring seamless transitions in context. Keeping this in mind helps strike a balance between full automation and recognizing when human interaction is essential.

DQ: In the coming decades, what disruptive technologies do you think will redefine automation?

Deepak: Automation is progressing rapidly, and I believe several factors are coming together to drive its advancement and acceleration in the market. One notable phenomenon is Generative AI, while another is the emergence of low-code platforms that utilize these technologies. Although organizations have previously implemented successful low-code solutions, AI is now taking center stage, as it can significantly enhance the effectiveness of these platforms. Low-code platforms that fail to integrate AI technology may risk falling behind.

Secondly, autonomous enterprises are emerging. Just as we see cars capable of driving themselves today, I believe we'll witness the realization of autonomous enterprises in the next few years. These enterprises will feature self-driven and self-healing processes, leveraging generative AI and other AI capabilities to understand and process data patterns, thereby enhancing efficiency and productivity. Such systems will be able to automatically update their processes to optimize efficiency.

Third is IoT, the Internet of Things. With industrial IoT, there's a massive proliferation of devices generating data that, when combined, creates a vast amount of information. Humans and traditional processes struggle to process this data efficiently. This is where artificial intelligence will play a crucial role. Furthermore, we will leverage IoT devices and the data they generate to make real-time decisions and optimize processes.