Sachin Arora, who serves as the Partner and Head of Lighthouse (Data, AI, and Analytics) at KPMG India, brings to the forefront a significant shift in the consulting sector’s approach to generative AI. He thinks about the initial skepticism that the sector harbored towards this technology, highlighting the subsequent transformation in mindset. This evolving perspective is driving pioneering applications that hold the potential to redefine the future landscape of these industries.
In the past year, the consulting and finance sectors have undergone a remarkable shift from initial skepticism to a newfound enthusiasm for generative AI. This transformation is particularly evident in the activities of prominent players like KPMG, one of The Big Four accounting firms. KPMG has taken notable strides by developing an in-house system akin to ChatGPT, leveraging proprietary data to assist its workforce.
Moreover, KPMG’s commitment to a $2 billion expanded AI alliance with Microsoft, announced in July, underscores the company’s dedication to this technological evolution. This follows their earlier declaration in December 2019, earmarking $5 billion over five years for advancements in cutting-edge technologies such as AI.
Simultaneously, PwC has laid out plans to invest $1 billion in the next three years to propel generative AI in its US operations. Teaming up with Microsoft and OpenAI, their ambitious objective involves automating segments of tax, audit, and consulting functions. Numerous teams within PwC are diligently working on diverse AI and generative AI applications, aiming to enhance efficiency, streamline costs, save time, and unveil novel perspectives.
EY, another member of The Big Four, has understood the capabilities of generative AI for specific business tasks, such as handling payroll inquiries. By integrating tax regulations into an AI system, they’ve created a ChatGPT-like interface that delivers instantaneous answers. This beta experiment has proven highly advantageous, resulting in substantial gains in both efficiency and accuracy. Predictably, Deloitte has also embraced the potential of generative AI by launching a dedicated practice to equip its clients with these transformative technologies.
In an exclusive discussion with AIM, Sachin Arora, Partner and Head at Lighthouse (Data, AI, and Analytics) for KPMG India, provides invaluable insights into the initial skepticism that once prevailed, the evolving mindset that’s now taking shape, and the amazing implementations that are actively shaping the future trajectory of these dynamic sectors.
Gen AI in Action
In the recent past, KPMG and Microsoft have forged a collaborative effort to modernize the landscape of professional services by adopting the power of AI solutions, specifically focusing on generative AI. Their collective objective revolves around streamlining client interactions within the realms of auditing, taxation, and advisory sectors. This transformative endeavor involves the strategic integration of Microsoft Cloud and Azure OpenAI services. A substantial financial commitment of $2 billion from KPMG is earmarked for investments in Microsoft Cloud and AI services over a span of five years.
Notably, KPMG’s pursuit of innovation extends beyond its alliance with Microsoft. Earlier this year, a partnership was forged between KPMG and Google Cloud to infuse advanced generative AI capabilities into their operational frameworks. This strategic collaboration capitalizes on KPMG’s proficiency in cloud computing, data analysis, and ethical AI practices, coupled with Google Cloud’s cutting-edge infrastructure and deep-seated expertise in generative AI technologies.
According to Sachin Arora, the Partner and Head of Lighthouse (Data, AI, and Analytics) at KPMG India, the choice of a generative AI service provider is a consequential decision with a multitude of factors at play. Elements such as reputation, customization flexibility, data privacy and security, ethical considerations, scalability, performance, intellectual property concerns, future roadmaps, and cost structures are pivotal in selecting the right provider for generative AI services.
Within the framework of KPMG’s operations, the integration of generative AI revolves around adopting open-source vector embeddings and databases. This strategic approach facilitates the seamless infusion of organizational data into widely adopted language models, expediting responses and enriching interactions. Through this tailored framework, KPMG stands at the forefront of adopting generative AI to enhance customer experiences and operational efficiencies.
Sachin Arora emphasizes that generative AI is precipitating a revolutionary transformation in how consulting and finance enterprises operate across various dimensions. Its impact is discernible through diverse use cases: bolstering customer support through chatbots, enhancing data analysis and predictive capabilities for informed decision-making, leveraging AI-generated content for marketing, and personalizing financial services through custom banking assistance and tailored investment plans. This reflects the multifaceted role that AI is playing in reshaping the landscape of these sectors.
Overcoming Early Hurdles
“The initial reluctance stemmed from data security and privacy worries due to sensitive data involvement, ethical concerns regarding biased or misleading AI-generated content, and the challenge of adhering to stringent regulatory frameworks,” said Arora.
The initial caution displayed by the consulting and finance sectors towards entering the realm of generative AI was underpinned by significant challenges surrounding data security, ethical considerations, and regulatory compliance. The emergence of ethical concerns, particularly pertaining to potentially misleading AI-generated content within financial advice and consulting services, created a backdrop of apprehension due to potential regulatory infringements and reputational hazards. The already intricate regulatory environment further compounded the hesitancy.
However, a remarkable transformation has gradually unfolded, epitomized by trailblazing firms like KPMG. This shift has been catalyzed by the advancement of technology, rendering AI more accessible and user-friendly. The introduction of pre-built AI platforms has facilitated a culture of experimentation, leading to successful execution of generative AI projects. Noteworthy innovations in data management have effectively assuaged concerns regarding data privacy, bolstered by the integration of privacy-preserving AI techniques that ensure secure implementation. The establishment of ethical guidelines and industry standards has played an instrumental role in promoting responsible AI adoption and mitigating ethical quandaries associated with AI-generated content.
Looking to the horizon, KPMG envisions substantial advancements in the domains of generative AI, machine learning, and analytics in the impending months. In the near term, the fusion of generative AI with traditional AI and analytics is poised to notably amplify employee productivity. This integration holds the potential to expedite the introduction of novel products and innovations, consequently disrupting conventional practices in information exchange and dissemination.