KPMG’s Generative AI Play

Over the past one year, the consulting and finance sector has moved on from apprehension to enthusiasm on generative AI. One of The Big Four accounting firms, KPMG, has been using a ChatGPT-like framework to devise an in-house system that aids its staff by utilising proprietary data.

What’s more? KPMG also announced a commitment to spending $2 billion in an expanded AI alliance with Microsoft in July. The company had said back in December 2019 that it would allocate $5 billion for five years in advanced technologies like AI.

Meanwhile, PwC plans to allocate $1 billion towards advancing generative AI in its US activities in the next three years. Collaborating with Microsoft and OpenAI, the company aims to automate elements of its tax, audit, and consulting functions. Numerous teams are currently engaged in developing a multitude of AI and generative AI applications to enhance efficiency, reduce costs, save time, and uncover fresh perspectives.

Another Big Four, EY, is using generative AI for targeted business tasks like payroll queries. They've integrated tax laws into an AI system, allowing instant answers through a ChatGPT-like interface. This beta experiment has led to significant gains in efficiency and accuracy. As expected, Deloitte also launched a generative AI practice to equip its clients.

Speaking with AIM in an exclusive interaction, Sachin Arora, partner and head at Lighthouse (Data, AI, and Analytics), KPMG India, sheds light on the initial hesitation, the evolving mindset, and the innovative implementations that are shaping the future of these sectors.

Gen AI in Action

Last month, KPMG and Microsoft joined hands to modernise professional services with AI solutions, especially generative AI, aiming to streamline client engagement in auditing, taxation, and advisory sectors with Microsoft Cloud and Azure OpenAI service. KPMG plans to invest $2 billion in Microsoft Cloud and AI services over five years.

Earlier this year, Google Cloud and KPMG partnered to incorporate advanced generative AI into their processes. This venture will combine KPMG's expertise in cloud computing, data analysis, and ethical AI practices with Google Cloud's cutting-edge infrastructure and generative AI proficiencies.

“Collaborating with a GenAI service provider can be significant as it would impact the business. Aspects such as reputation and track record, customization and flexibility, data privacy and security, ethical considerations, scalability and performance, intellectual property considerations, future roadmap and last, but not the least, cost and pricing structures are key to the selection of the right GenAI service provider,” said Arora

At KPMG, the integration of generative AI involves leveraging open-source vector embeddings and databases. This approach facilitates the seamless incorporation of organisational data into widely-used language models, expediting responses and enhancing interactions. By utilising this custom framework, KPMG is at the forefront of embracing generative AI for enhanced customer experiences and operational efficiency.

“Today, generative AI is revolutionising how consulting and finance firms operate across various dimensions. The integration of generative AI is evident in diverse use cases,” he added. According to him, AI plays a multifaceted role: it boosts customer support through chatbots, improves data analysis and predictions for better decision-making, aids marketing with AI-generated content, and tailors financial services by offering personalised banking assistance and investment plans.

Overcoming Early Hurdles

“The initial reluctance stemmed from data security and privacy worries due to sensitive data involvement, ethical concerns regarding biassed or misleading AI-generated content, and the challenge of adhering to stringent regulatory frameworks,” said Arora.

Initially wary of venturing into generative AI, consulting and finance sectors faced huge challenges around data security, ethics, and regulations. Ethical concerns arose over misleading AI-generated content in financial advice and consulting services, raising regulatory and reputational risks. The stringent regulatory landscape further exacerbated hesitancy.

However, a transformative shift has occurred over time, exemplified by firms like KPMG. This change is driven by technological advancements, making AI more accessible and user-friendly. Pre-built AI platforms facilitated experimentation, leading to successful generative AI projects. Innovations in data management addressed data privacy apprehensions, with privacy-preserving AI techniques ensuring secure implementation. The establishment of ethical guidelines and standards enabled responsible AI usage and mitigated ethical dilemmas tied to AI-generated content.

Looking ahead, KPMG envisions significant developments in the realm of GenAI, machine learning, and analytics over the coming months. In the short term, the integration of GenAI with traditional AI and analytics is expected to substantially boost employee productivity. This amalgamation has the potential to expedite the rollout of new products and developments, disrupting conventional information brokering practices.