Kamal Ahluwalia, Ikigai Labs: How to elevate your business to the next tier with generative AI.

AI News recently had the opportunity to speak with Kamal Ahluwalia, president of Ikigai Labs, about the growing role of generative AI in business, including key adoption strategies and the critical importance of embedding ethics into AI design.

Ikigai Labs is at the forefront of transforming enterprise data into predictive and actionable insights through its generative AI platform, which is uniquely tailored for structured, tabular data. This data type, which predominates in systems like SAP and Salesforce, is crucial for business planning and forecasting. Unlike the widely discussed Large Language Models (LLMs) that excel with unstructured data, Ikigai has developed patented Large Graphical Models (LGMs) from MIT to tackle structured data challenges, particularly in time-series datasets crucial for business operations.

Discussing the generative AI landscape, Ahluwalia noted that while LLMs like those from OpenAI and Anthropic have dominated public attention due to their training on massive internet-scale datasets, these models are not always suitable for enterprise use where accuracy, privacy, and cost are paramount. The high costs and potential risks of exposing sensitive data make these models less feasible for enterprise applications, driving the need for tailored solutions that maintain data confidentiality and lower ownership costs.

Ahluwalia advises companies wishing to leverage generative AI to focus on specific, high-value business areas rather than generic applications. He suggests identifying unique challenges within an organization where AI can provide distinct advantages, such as logistical planning in manufacturing or developing more sustainable materials and practices.

The deployment of generative AI poses its challenges, mainly around data quality, integration, cost, and security. However, Ahluwalia points out that Ikigai's approach using Large Graphical Models can operate efficiently on limited data and standard CPU infrastructure, significantly reducing costs and complexity while ensuring data privacy and regulatory compliance.

When asked about the cultural shifts necessary for successful AI integration, Ahluwalia emphasized the need for strong executive commitment and ongoing education to overcome resistance and fear associated with AI deployment. He underscored the importance of adapting business processes to leverage AI effectively, including integrating human oversight where necessary, especially in regulated industries.

Highlighting Ikigai Labs' commitment to responsible AI, Ahluwalia shared insights into their AI Ethics Council, which includes prominent experts like Dr. Munther Dahleh from MIT and Dr. Michael I. Jordan from UC Berkeley. The council focuses on addressing ethical and security challenges in AI development and usage, reinforcing Ikigai's dedication to ethical practices.

Finally, Ahluwalia discussed the impact of recent funding, which will enhance Ikigai's solutions and expand its customer and partner engagements. The focus remains on solving key business challenges through advanced time-series applications, driving significant value for clients in areas like sales and consumption forecasting.

In sum, Ikigai Labs, under Ahluwalia's leadership, is shaping a future where generative AI is not only transformative for businesses but also developed and applied ethically and responsibly.