Use of Large Language Models (LLMs) can boost AI-driven innovation in startups, reveals AURAK research
New applied research by the American University of Ras Al Khaimah (AURAK) has revealed that the use of Large Language Models (LLMs) can dramatically accelerate growth and productivity of startups – offering multiple benefits, such as automation of tasks, improved decision-making, and enhanced customer experience through AI-driven marketing, CRM, and financial forecasting tools.
The research entitled ‘Integrating Large Language Models into Entrepreneurial Ventures’ was conducted by Dr. Tahseen Anwer Arshi, Associate Provost for Research and Sustainability, and Director of the Center for Innovation and Entrepreneurship, AURAK.
The study provides actionable insights into the benefits of integrating LLMs into entrepreneurial activities, demonstrating the potential to empower and grow startups in areas like ideation, creativity, new product development, innovation, customer engagement, and service personalization.
Prof. Stephen Wilhite, Senior Vice President of Academic Affairs and Student Success and Provost at AURAK, says: “LLMs are critical to accelerating growth and speeding up processes in enterprises large and small. They push entrepreneurs toward peak performance due to the increased productivity resulting from automating of tasks. Our research delves into how LLMs empower entrepreneurs to harness automation smartly, leaving them to devote themselves to more complex tasks that can only be performed by humans.”
Dr. Tahseen Anwer Arshi explains: “The use of LLMs in entrepreneurship is still developing, with few case studies available. However, promising examples include AI-based content generation start-ups using GPT-4 for marketing and software companies using LLMs for real-time coding. Our study demonstrates that LLMs enhance product innovation by automating tasks and facilitating rapid prototyping. They allow innovation teams to quickly create user interface descriptions, technical documentation, and wireframes, leading to faster stakeholder feedback and supporting agility in start-ups.”
Recent advancements have improved LLM technology further, moving beyond traditional transformer architectures to include innovations such as mixture-of-experts architectures and advanced quantization techniques (4-bit, 8-bit) that reduce memory usage while maintaining performance. Additionally, start-ups are employing hybrid deployment strategies combining edge computing with cloud-based model sharding for better resource efficiency.
The study recommends enhanced AI literacy among entrepreneurs through wider exposure to chatbots, recommendation algorithms and AI-powered analytics. Entrepreneurs should also be provided with hands-on opportunities with no-code AI tools like ChatGPT, Google AutoML, and Zapier AI. Such learning can be facilitated through AI hackathons, mentorship programs, and start-up accelerators. AI peer networks can be created through entrepreneur communities, LinkedIn groups, and local meetups.
The research paper was first presented at the International Conference on Business Management, Entrepreneurship & Circular Economy in November 2024. It is currently in the process of being released in Advances in Science, Technology and Engineering, published by Springer Nature.
The research carries great significance for businesses, since LLMs are widely hailed as key business drivers worldwide. Researchers at the International Institute for Management Development have termed LLMs a “technological tsunami” about to “reshape the global economic landscape”; while researchers at McKinsey estimate generative AI could add the equivalent of $2.6 to $4.4 trillion of value to the world economy annually.
Last Updated on 3 hours by News Desk 1
