“At Pega, we had conducted a survey in early 2021, where we spoke to over 1,000 consumers in India on their views about AI” – By, Mr. Suman Reddy, Managing Director, Pega India

Managing-Director-Pegasystems-India-Suman-ReddyHow is AI aiding organizations to scale business and innovations in the new normal?

AI has been a major stimulant in the digital transformation journey of many enterprises and global economies with an accelerated role during the pandemic. Today, every organization is required to exhibit far greater agility by challenging the traditional concepts of collaboration and innovation, while also ensuring a seamless and dynamic customer experience. This has unlocked promising opportunities for enterprises to utilize AI-powered tools for higher productivity at lower operating costs and simplifying employee and customer engagement.

To this effect, Pega recently announced a new set of platform capabilities, Pega Process AI, that enable enterprises to optimize their business and customer operations in real time. Pega Process AI infuses self-optimizing AI and intelligently triages millions of incoming customer requests, transactions, and other events at an enterprise scale.

Specifically, it also allows enterprises to scale and automate processes that would previously have required employee interaction and intelligence, and provide these to end clients in self-service mode.

Living in a world where digital solutions will play a significant role in determining the survival and growth of organizations, we are anticipating a greater democratization of AI in the coming years. Leveraging Artificial Intelligence (AI) for automation has opened myriad possibilities for enterprises and we are well on our way to accept AI as the currency required for thriving in this era.

What are the major factors enabling AI and empathy to augment and optimize successful business operation?

For businesses to excel, it is imperative that they provide superior customer experience, as a competitive advantage. Currently, empathy is a major element in customer service because emotions are running so high. AI is the only technology that can enable businesses to take this into account and apply that context to their interactions. Skills like persuasion, social understanding, and empathy will determine the competitive edge for businesses going forward. This is where Artificial Intelligence comes in to provide a potential means to achieve that level of intimacy.

At Pega, we had conducted a survey in early 2021, where we spoke to over 1,000 consumers in India on their views about AI. About 84% of the respondents believe that AI has the potential to drive better customer experiences, improve brand reputation, and increase customer loyalty. The study further reported that 60% of the respondents are more likely to tell the truth to an AI system or chatbot as compared to a human. This could be because engaging with a neutral bot would ease people’s concerns about the embarrassment of saying the wrong thing or creating a misunderstanding given the huge variety of cultures, subcultures, and multiple systems of beliefs across the country.

Thus, with AI becoming pertinent for driving customer engagement, organizations need to concentrate on combining AI-based insights with human supplied ethical considerations. It is now a prerequisite for them to use data to understand the customers’ needs, wants, perceptions, expectations, and frustrations. Leveraging AI can give them the power to change how companies affect customers’ perceptions of a variety of things.

However, empathy also goes beyond understanding client needs, emotions and context. Most fundamentally it requires enterprises to act in the best interest of the customer, not just the company, in every interaction or process. Next to implementing intellectual intelligence (IQ) and emotional intelligence (EQ) we also need to implement central moral values. Not just a central brain, but almost a central ethical conscience as well.

It is important for enterprises to therefore possess the ability to control their own AI for impact and empathy. The only way for businesses to change the conversation and comfort level with AI is to take control of it, prove its value through responsible applications, and direct its power toward improving outcomes.

This approach not only gives businesses control as well as visibility into how analytics are used and decisions are made but also allows them to leverage AI-based decisioning to engage in a contextual, relevant, and personalized way across any channel, creating outcomes that are mutually beneficial to the customer and the company.

How would you demystify the concepts of RPA vs AI and India’s roadmap in actual adoption?

In the race to digital transformation, robotic process automation (RPA) is often heralded as a quick and easy way to streamline critical processes, often extending the life of legacy systems. In fact, according to Gartner, global robotic process automation (RPA) software revenue is projected to reach $1.89 billion in 2021, an increase of 19.5% from 2020. Despite economic pressures caused by the COVID-19 pandemic, the RPA market is still expected to grow at double-digit rates through to 2024. While RPA furthers the overall path to digital transformation, organizations need to focus on a long-term intelligent automation strategy to automate repetitive yet critical business processes. This can be done by leveraging AI-enabled, adaptive RPA to automate control identification and integration of processes.

As the adoption of RPA continues to increase in the coming years, fast, reliable, and resilient automation that works invisibly behind the scenes will become critical for business applications. Instead of manually searching and identifying every control, the newest versions of RPA will automate this process. At Pega, we use a capability called X-ray Vision, which automates at the application object-level for faster and more accurate automations.

The role of RPA in employee and customer experience is significant and having RPA bots work without interruption will be critical for RPA to meet its business objectives with self-healing becoming the next-gen RPA experience.

However, you also need to move beyond tactical RPA solutions that just resolve some tactical issues and provide strategic orchestration platforms that can orchestrate work across many different departments and value chains. These platforms should not just automate straight through processes, but also be able to orchestrate work across processes, bots and people. Also these platforms should not just work automation capabilities, but also artificial intelligence, to make these processes smarter.

Classical robotic platforms are lacking this strategic orchestration layer, as well as the depth in terms of decisioning and intelligence.

How can predictive intelligence technologies can play a critical role in digital transformation?

Digital Transformation has become pivotal for providing value added services to customers across all industries, especially in this highly competitive and constantly changing business environment. With emerging technologies like Artificial Intelligence (AI), Machine Learning, etc coming into play, tools like predictive analytics have become even more streamlined and precise, transforming the data collected into valuable insights. Even the simplest businesses need the advantage that data offers to foresee the demand and how to offer the right products to the right clients.

For enterprises to become more innovative, more efficient, more customer-centric, and more resilient in a time of constant disruption, predictive analytics can be used to help forecast outcomes based on historical data and analytics techniques such as machine learning. Predictive analytics is used to determine customer responses or purchases, as well as promote cross-sell opportunities thus helping businesses attract, retain, and grow their most profitable customers. Predictive algorithms can be investigated to determine new possible features for smartphones by combining and transforming existing features and testing them to see which one’s boost performance. Predictive analytics helps organisations leverage their digital transformation strategies to gain smarter and more accurate insights at a faster pace than their competitors to translate those insights into actionable deliverables thus improving the overall business growth.

However, merely predictive analytics will not cut it. You can to be able to translate predictions into actionable decisions and outcomes, by combining many predictions with business rules, strategies and policies to capture real world trade-offs, constraints and knowledge.

To this end, Pega’s Next-Best-Action technology utilizes predictive analytics and real-time decisioning to recommend the interactions that will return the most value to both customers and the organization. Pega incorporates this technology in its CRM products for industries such as insurance (predictive analytics for insurance) and finance (predictive analytics in banking).

Please tell us about the current industry trends that you are witnessing.

Since the pandemic hit, digital transformation had a renewed role in delivering measurable business outcomes. Organisations who have made significant strides to digitize their business at scale have fared well in weathering this storm. It is more prudent than ever to crush business complexity, increase agility, enable better decisions making processes, and get things done more effectively.

Since the pandemic hit, digital transformation is critical to delivering measurable business outcomes. Organisations who have made significant strides to digitize their business at scale have fared well in weathering this storm. It is more prudent than ever to crush business complexity, increase agility, enable better decisions making processes, and get things done more effectively.

  • AI Imperative: Given growing consumer queries, distributed workforces, and increased challenges, there’s going to be more demand for automation in AI and close monitoring of those AI interactions. Hyper-automation will help streamline workflows in the post-COVID era, but businesses will still need to understand what their AI is doing to predict it and monitor it, so they don’t disenfranchise any of their customers.
  • Responsible and Trustworthy AI: As AI becomes more pervasive, more and more stakeholders are waking up to the potential problems it introduces for the public. In response, organizations everywhere will be expected to deliver AI systems that are responsible, transparent, and unbiased.
  • Intelligent automation:With the proliferation of internet of things (IoT) devices and the increased adoption of 5G fuelling this trend, computing power at the edge will grow and the ability to leverage AI at the edge will grow too. Dramatic advancements in AI, machine learning, and Natural Language Processing (NLP) have led to iterative improvements in developing smarter intelligent virtual assistants with better capabilities for understanding questions and replying accurately.
  • Deploying AI solutions via ModelOps: Much like the way DevOps has given structure to the way applications are deployed, ModelOps will reach a tipping point in 2021 as a way for mainstream businesses to better develop and operationalize their AI models. This will give them a more systematic way to develop, test, and deploy AI models more efficiently via the Cloud quickly and responsibly.

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