Business leaders have high hopes that artificial intelligence (AI) investments can drive market-changing innovations to transform everything from customer satisfaction to product innovation. However, a poor data foundation is holding 78% of organisations back from achieving these goals.

A new report from MIT Technology Review Insights, in partnership with Snowflake, the AI Data Cloud company, titled ‘Data Strategies for AI Leaders’ found that while businesses have big ambitions for generative AI — with 72% looking to increase efficiency or productivity, 55% betting on increased market competitiveness, and 47% aiming to see more innovation in products and services — the foundational data strategy needs to be improved to maximise AI’s potential.

Businesses need strong data foundations, powered by modern cloud data platforms, to enable them to harness their own stores of data, and also vast volumes of previously inaccessible data, largely from unstructured data such as videos and images. According to the report, just 22% of business leaders say they are ‘very ready’ to engage with AI, while 53% are ‘somewhat ready’. Higher readiness correlates with fewer challenges related to accessing scalable computing power, data silos and integration issues, and data governance. Despite many business leaders’ confidence in the results AI can deliver, they are realising that data is key to how quickly and effectively they can unlock AI’s value.

Another challenge facing organisations is deploying AI at scale. 95% of those surveyed reported facing hurdles when implementing AI. 59% of respondents cited data governance, security, or privacy as their most prevalent challenge, followed by data quality and timeliness (53%), and costs of resources or investment (48%). Spending and resourcing decisions, including those needed to improve data foundations, are a challenge when it comes to any technology investment. But the cost of generative AI itself is decreasing, with enterprises having begun to build smaller large language models (LLMs) that remain equally capable, and less expensive.

“Many of today’s organisations have big ambitions for generative AI: they are looking to reshape how they operate and what they sell,” says Baris Gultekin, Head of AI, Snowflake. “Our joint research shows that as organisations feel increasing urgency to deploy AI applications, they are realising that their data can help them deliver insights from previously untapped sources of information. A strong data foundation is at the core of generative AI capabilities, and business leaders need to move quickly to deal with concerns such as data security and cost, and establish the foundation they need to deliver on the promise of AI.”

Generative AI’s benefits are becoming visible to those companies farther along their data journey, because they invested heavily in data foundations and are now being rewarded by bringing AI onto that data. For any business looking to capitalise on AI, they must first establish a robust data foundation, which covers a broad collection of processes and assets involved in the gathering, aggregation, storage, and accessibility of organisational data. Investment in data foundations across an organisation will enable much more powerful generative AI users, while also reducing governance and security concerns.

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Snowflake announced the appointment of Vijayant Rai as the new Managing Director, responsible for driving the business growth and Go-To-Market strategy for Snowflake in India. Vijayant will be succeeding Vimal Venkatram, who has moved to a regional role for Snowflake, based in Singapore. 

Vijayant comes with over 27 years of extensive experience in senior sales positions across leading companies. Previously, he served as the Executive Director for Microsoft India, and was the Country Leader for the BFSI industry segment in the company. Prior to this, he also held leadership roles in Salesforce, SAP, and CA Technologies. 

He will spearhead Snowflake’s business expansion across India, overseeing strategy, sales and execution, fostering strategic partnership engagements across the country, and driving the adoption of Snowflake’s Data Cloud across various industries, such as retail and CPG, manufacturing, public sector, startups, healthcare, pharmaceuticals, and BFSI.

“India is a dynamic growth market that is rapidly transitioning to a data-driven economy,” said Vijayant. “As Managing Director, my primary focus will be to help our customers fully mobilize their data into successful business outcomes. I am excited to join Snowflake at this pivotal point. Snowflake recently announced a slew of new features, including Snowflake Cortex currently in private preview, that facilitates businesses with swift development of AI applications, further bolstering their commitment to driving innovation in the Indian market. I look forward to working with the talented team at Snowflake India to support our customers in their quest for growth,” he added. 

Speaking on Vijayant’s appointment and Snowflake’s commitment to India, Sanjay Deshmukh, Senior Vice President of ASEAN and India, added, “Vijayant’s extensive experience in India of doing leadership roles with leading global technology organizations and helping customers in accelerating their transformation journey makes him the perfect fit for leading Snowflake in India. We believe that our business in India is at an inflection point of wider adoption across all industries, and with Vijayant’s successful track record in building and scaling businesses, we are confident that he will spearhead our expansion in the local market and drive strong growth across all of our portfolios.” 

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The Snowflake Summit 2023, the company’s annual user conference, witnessed a number of LLM-based announcements and a host of enhancements to the company’s Data Cloud platform. The most notable one, perhaps, is its Document AI which stems from Snowflake’s acquisition of Applica (Sept. 2022) and leverages its purpose-built, multimodal LLM.  Document AI, which is currently in private preview, will enable businesses to extract and leverage unstructured data from documents. 

Over the next five years, over 90 percent of the world’s data will be unstructured in the form of documents, images, video, audio, and more according to IDC2. This massive volume of unstructured data is routinely stored by organizations, however gaining valuable insight from it has historically required manual, error-prone processes and limited expert skillsets. Snowflake’s built-in Document AI will make it easier for organizations to understand and derive value from unstructured data and documents using natural language processing, said Murad Wagh, Director of Sales Engineering at Snowflake, while addressing the Indian media.

Some of the use case examples include the ability to easily extract content like invoice amounts or contractual terms from documents and fine-tune results using a visual interface and natural language. Snowflake is starting with Document AI and plans to expand these capabilities to more types of unstructured data.

Additionally, the company also announced updates for Iceberg Tables, which will enable organizations to work with data in their own storage in the Apache Iceberg format, whether that data is managed by Snowflake or managed externally. Snowflake also announced that its platform will support a broader set of advanced analytics capabilities including pre-built machine learning functions for SQL users (public preview), and is expanding its unified governance and privacy with new data quality metrics and classification features (both in private preview). 

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Snowflake and NVIDIA announced that they are partnering to provide businesses with a platform to create customized generative AI applications using their own proprietary data in the Snowflake Data Cloud. The announcement came today at Snowflake Summit 2023.

With NVIDIA NeMo platform for developing large language models (LLMs) and NVIDIA GPU-accelerated computing, Snowflake customers can use data in their Snowflake accounts to make custom LLMs for advanced generative AI services, including chatbots, search and summarization. Snowflake plans to host and run NeMo in the Data Cloud. 

“Snowflake’s partnership with NVIDIA will bring high performance machine learning and artificial intelligence to our vast volumes of proprietary and structured enterprise data, a new frontier to bringing unprecedented insights, predictions and prescriptions to the global world of business,” said Frank Slootman, chairman and CEO, Snowflake.

“Data is essential to creating generative AI applications that understand the complex operations and unique voice of every company,” said Jensen Huang, Founder and CEO, NVIDIA. “Together, NVIDIA and Snowflake will create an AI factory that helps enterprises turn their own valuable data into custom generative AI models to power groundbreaking new applications — right from the cloud platform that they use to run their businesses.”

The partnership will enable customers to use their proprietary data — which can range from hundreds of terabytes to petabytes of raw and curated business information — to create and fine-tune custom LLMs that power business-specific applications and services. 

The companies maintain that the integration of AI technology from Snowflake and NVIDIA will enable users to quickly build generative AI apps for a number of business use cases. For example, a healthcare insurance model could answer complex questions about what procedures are covered under various plans. A financial services model could share details about specific lending opportunities available to retail and business customers based on a variety of circumstances. 

Another advantage, according to Snowflake, is the ability to create these apps where the governed data already resides – a benefit that reduces cost and latency while maintaining the security of the data. 

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