Tackle data challenges effectively to ensure durability of investments in GenAI: Arun Kumar Parameswaran, Salesforce

In today's data-driven landscape, organizations grapple with the complexities of managing vast amounts of data scattered across disparate systems and silos. By implementing robust data management strategies and leveraging innovative technologies, such as data integration platforms and AI-powered analytics tools, businesses can streamline data processes, enhance data quality, and establish a single source of truth. This unified data ecosystem not only lays the foundation for accurate AI modeling and decision-making but also fosters trust in AI-generated insights and recommendations.  Additionally, prioritizing data governance and compliance ensures that data remains secure, compliant with regulations, and ethically utilized, further bolstering confidence in AI solutions. In a conversation with Dataquest, Arun Kumar Parameswaran, senior vice president and managing director, Salesforce revealed that by tackling data challenges head-on, organizations can unlock the full potential of GenAI, driving transformative outcomes and competitive advantages in the digital age.

DQ: Can you provide an overview of how generative AI is impacting businesses, what business leaders' views are on its adoption, and what the adoption and implementation process looks like for organizations today?

Arun Kumar Parameswaran: Let's take a step back and discuss the broader perspective of GenAI. Initially, there was concern about job losses across various industries due to this technological update, a common fear with every major technological shift in the past three decades. However, a recent IDC study on the AI-powered economy revealed a promising outlook. The study suggests a net gain of almost 11 million jobs globally by 2048, along with nearly $2 trillion in business revenues driven by AI. This aligns with my belief that technological transformations tend to be net positive, despite an initial adjustment period.

While acknowledging the temporary dip that often accompanies such transformations, it's crucial to recognize the overall positive impact. Now, every CEO, company, and board is eager to understand the role of AI investments in strengthening customer relationships, enhancing productivity, and fostering innovation.

Reflecting on Salesforce's decade-long investment in AI, including predictive models like Einstein, it's evident that AI isn't new to us. We've been proactive, even investing in generative AI before it gained widespread attention. Our focus has always been on staying ahead of customer needs and market trends.

Moving forward, the effectiveness of AI implementations hinges on two foundational elements: data and trust. Many companies struggle with siloed data, hindering their AI model's accuracy. Our innovation in the Data Cloud addresses this challenge, enabling seamless integration and data accessibility.

Moreover, establishing a trust layer is essential, particularly in sensitive areas like B2B interactions. Customers need assurance that AI responses are authentic, unbiased, and respectful of privacy. In terms of practical applications, we've integrated AI capabilities across our entire product portfolio, notably in Customer 360. This comprehensive AI-powered CRM platform empowers users across sales, service, marketing, and beyond, providing a unified solution for their generative AI needs.

While some organizations may view AI as a means to cut costs, others see it as a strategic investment for gaining a competitive edge. Despite initial cost considerations, those investing in AI now are poised to reap long-term benefits, especially as technology costs decline over time. In India, unique economic factors influence AI adoption, requiring tailored approaches to maximize value. The convergence of structured and unstructured data presents both challenges and opportunities, particularly concerning scalability.

Overall, the journey towards AI integration involves navigating complexities while prioritizing trust, data integrity, and strategic use cases. By leveraging AI responsibly and innovatively, businesses can unlock unprecedented levels of personalization and efficiency, setting the stage for transformative outcomes in the years ahead.

DQ: Can you elaborate on the current sentiment among IT professionals regarding the rapid implementation of generative AI?

Arun Kumar Parameswaran: There seems to be a gold rush mentality prevailing, wouldn't you agree? Everyone, regardless of their role, is striving to be recognized in the realm of AI. The trend is to attain some form of AI certification or acknowledgment. Take, for example, software developers. Why bother with mundane coding tasks when AI can automate them, freeing up valuable time for more strategic endeavors? The key question remains: How can I deliver tangible value to my business?

Consider the insightful perspective shared by our president of engineering. In any organization, there's a vast talent pool, with a core group at the center and a long tail of contributors. AI promises to shift capabilities leftward, empowering individuals to focus on higher-value tasks by automating routine responsibilities. This shift has the potential to drive productivity and efficiency on a broad scale, both locally and globally.

For IT professionals, the impact of AI is palpable. Take Slack, our divisional HQ at Salesforce, for instance. From managing expenses to approving leave requests, Slack streamlines various tasks, consolidating multiple functions into one platform. The ability to receive morning recaps summarizing overnight activities further enhances productivity, saving valuable time previously spent sifting through numerous channels.

Similarly, Tableau empowers users with comprehensive insights delivered in a single dashboard, eliminating the need to navigate through multiple interfaces. Imagine the time saved by automatically summarizing lengthy meeting discussions with the click of a button. While not perfect, the AI-generated summaries significantly reduce manual effort, allowing individuals to focus on more critical aspects of their work.

Chatbots exemplify another area where AI excels, efficiently addressing customer queries and enhancing response times. Heathrow Airport's adoption of chatbots led to a remarkable 30% improvement in customer service. Furthermore, platforms like Einstein and Data Cloud are revolutionizing data management, automating mundane tasks and optimizing workflows.

The reality is clear: AI is here to stay and will continue to transform the way we work. For technology professionals, embracing AI presents an opportunity to upskill and elevate their contributions. Ultimately, AI holds the promise of fostering increased productivity, efficiency, and, hopefully, restoring the elusive work-life balance we all strive for.

DQ: Is there any disconnect between business stakeholders' expectations and IT professionals' concerns about the speed and agility of new technology adoption?

Arun Kumar Parameswaran: From my conversations, albeit limited, I haven't noticed any resistance from employees towards integrating AI into our operations. On the contrary, there seems to be genuine enthusiasm among them to embrace AI and be catalysts for change within the company. The primary challenge, however, lies in upscaling our workforce at scale. This is a multi-million-dollar question that demands urgent attention.

India, with its significant footprint in global implementations, faces a particularly pressing need for upskilling. I'm acutely aware of the importance of rescaling efforts, not only internally but also in collaboration with colleges, universities, and organizations. However, the emergence of AI poses a new and formidable challenge, requiring us to augment our existing efforts.

The skill gap, if left unaddressed, could have profound implications for India's GDP. Reports indicate that the digital skill gap alone could result in a 0.3% loss in GDP. Despite India's robust digital infrastructure, our ability to capitalize on this opportunity hinges on our capacity to rescale our workforce effectively.

This challenge isn't unique to India; it's a global concern. The nascent nature of AI technology means there's often a lag between its adoption and the acquisition of relevant skills. We've witnessed similar dynamics in past technological revolutions, such as the ERP boom of the early 90s, which spawned a proliferation of training institutes and upskilling initiatives.

As AI continues to gain momentum, we're likely to see a similar surge in upskilling initiatives worldwide. This presents both a challenge and an opportunity for individuals and organizations alike. By addressing the skill gap proactively, we can ensure that we're well-positioned to harness the full potential of AI and navigate the evolving landscape of digital transformation effectively.

DQ: What are the most significant challenges organisations are facing when it comes to implementing generative AI? How can organizations address these challenges?

Arun Kumar Parameswaran: The good news is that we have a track record of pioneering new categories. From creating CRM to delivering software as a service and introducing the concept of the cloud, we've been at the forefront of technological innovation. Five years ago, we also led the way in introducing the idea of low code and no code platforms.

The beauty of GenAI lies in its accessibility. Unlike previous technology revolutions that relied heavily on complex programming, GenAI doesn't require extensive coding skills. Take the prompt builder, for example. It's designed to be intuitive, allowing any business user to easily create and implement their desired functions.

Our goal is to empower organizations to leverage GenAI at scale, without burdening them with the need for a large team of developers and IT specialists. This means making the technology as user-friendly as possible, while still offering the flexibility for those who want to delve deeper into coding.

While India has a reputation for embracing complexity in coding, GenAI aims to simplify the process. Whether you're using Service Cloud or any other platform, the goal is seamless integration and effortless operation. Tasks that previously took considerable time and effort can now be streamlined with the push of a button.

The deployment of generative AI is set to revolutionize workflows, offering significant productivity gains without the need for extensive manual intervention. This streamlined approach is expected to result in a different adoption curve compared to previous technological advancements.

DQ: What steps should organizations take to ensure responsible and sustainable AI implementation in the face of increasing demands and challenges?

Arun Kumar Parameswaran: The good news is that we have a track record of pioneering new categories. From creating CRM to delivering software as a service and introducing the concept of the cloud, we've been at the forefront of technological innovation. Five years ago, we also led the way in introducing the idea of low code and no code platforms.

The beauty of GenAI lies in its accessibility. Unlike previous technology revolutions that relied heavily on complex programming, GenAI doesn't require extensive coding skills. Take the prompt builder, for example. It's designed to be intuitive, allowing any business user to easily create and implement their desired functions.

Our goal is to empower organizations to leverage GenAI at scale, without burdening them with the need for a large team of developers and IT specialists. This means making the technology as user-friendly as possible, while still offering the flexibility for those who want to delve deeper into coding.

While India has a reputation for embracing complexity in coding, GenAI aims to simplify the process. Whether you're using Service Cloud or any other platform, the goal is seamless integration and effortless operation. Tasks that previously took considerable time and effort can now be streamlined with the push of a button.

The deployment of generative AI is set to revolutionize workflows, offering significant productivity gains without the need for extensive manual intervention. This streamlined approach is expected to result in a different adoption curve compared to previous technological advancements.

DQ: Can you share a few case studies on how Salesforce customers are using its generative AI solutions and how are they benefiting from it?

Arun Kumar Parameswaran: Well, to start, let's consider the unique economic context of India. Here, the unit cost of labor significantly differs from that of the Western world. While a contact center employee in the West might earn $1,800,000 annually, their Indian counterpart might earn only $10,000, if they're fortunate. This discrepancy fundamentally alters the calculus of technology investment. Currently, I see two primary cases for investing in this technology: gaining a competitive edge and expanding customer base, or reaping cost benefits.

In terms of real-world applications, we've witnessed notable successes. For instance, Heathrow Airport utilizes our data cloud alongside Einstein and chatbots to decrease call volumes significantly, thereby freeing up agents to provide more personalized service to passengers. Similarly, Schneider Electric leverages the Einstein platform to streamline customer support across thousands of agents, handling millions of calls annually. These implementations include simple yet effective features like case summarization, proactive responses, automatic transcriptions, language-related solutions, and personalized messaging—all aimed at enhancing the customer experience.

Moreover, consider features like GoPilot and Prompter, which empower sales teams to engage with customers more effectively. These functionalities leverage the inherent strengths of our platform to deliver tangible value.

However, the challenge arises when attempting more complex deployments. In such cases, it's crucial to discern whether the objective is to enhance customer experience and gain a competitive advantage. This requires a nuanced understanding of the technology's capabilities and strategic alignment with business goals.

DQ:  Any final thoughts?

Arun Kumar Parameswaran: I believe the true essence of what GenAI can offer to customers often gets overshadowed amidst the chaos and complexity surrounding it. Especially for B2B organizations like ours, the reality is stark: a significant portion, ranging from 70% to 80%, of data remains trapped in silos. Achieving a unified view of data, often referred to as the "golden customer record," remains a daunting challenge for a considerable portion of our customer base, despite my over two decades of experience in the industry.

In light of this, I emphasize that addressing data integrity and trust issues takes precedence over identifying specific use cases. As a technology partner like Salesforce, we inherently integrate these aspects into our platform, alleviating the burden for our customers. Our platform's horizontal pervasiveness across industries—from financial services to telecommunications, manufacturing, retail, and consumer goods—allows us to amalgamate the best features of each sector, delivering unparalleled value to our customers.

The crux of the matter lies in our customers' ability to tackle their data challenges effectively and ensure the durability of their investments in GenAI over time. Establishing trust in data integrity forms the cornerstone of our efforts, and this is where we dedicate the bulk of our time and resources. Our message to customers is clear: focus less on the capabilities, which we assure you we can deliver, and instead leverage our platform's robust foundation to address your immediate data concerns.

Reflecting on Salesforce's unique approach, I highlight our unwavering commitment to trust and security. Unlike most software companies with multiple versions, we maintain just two: one for production and one for development. Every four months, development seamlessly transitions into production, ensuring consistency and reliability for all users, whether it's a national security agency, a global bank, or a small business owner in Bangalore. This level of trust is our hallmark, underpinning every interaction within the Salesforce ecosystem.

Moreover, it's essential to recognize that trust is not a standalone concept but intricately linked with data integrity. Without this foundational trust, even the most advanced technologies and innovative use cases are at risk of faltering. Therefore, our primary goal is to instill confidence in our customers by safeguarding their data and upholding the highest standards of trustworthiness.

In essence, while discussions around use cases, cost savings, and productivity enhancements are vital, they must always be grounded in a solid foundation of trust and data integrity. This foundational approach ensures the sustainability and success of any technological endeavor, including the adoption of GenAI.