How Generative AI is Revolutionizing Business

Overview

The rapid evolution of generative AI is paving the way for unprecedented integration across diverse technologies, enabling tasks to be performed more seamlessly than ever before. As the costs of emerging technologies decrease, accessibility increases, creating fertile ground for innovation and growth. While numerous organizations are vying for a leading position in generative AI, most are converging toward similar development and implementation goals. Companies like Google and Microsoft are uniquely positioned to capitalize on these advancements due to their extensive distribution networks and pre-existing product and service ecosystems. They have the potential to integrate generative AI more effectively, unlike independent service providers such as OpenAI's ChatGPT .

Intro

Generative AI has arrived, revolutionizing industries across the globe. While it hasn't yet achieved the level of Artificial General Intelligence (AGI), its impact is both profound and enduring. Organizations must seize this opportunity to experiment, educate, and strategically leverage generative AI to stay ahead in an increasingly competitive landscape. By doing so, we can unlock unprecedented potential and drive meaningful innovation within our organizations (both big and small).

Big Companies

Large corporations are increasingly embracing generative AI, solidifying their market dominance through advanced technological integration. The execution of large-scale operations and complex tasks often requires substantial computational power, typically facilitated by cloud and edge computing. Today, the improved accessibility of generative AI allows more organizations to harness its capabilities. However, this accessibility is not without limitations. The entities that control these powerful technologies ultimately hold the "off-switch," raising concerns about centralized control and potential dependency. Despite these challenges, the widespread adoption of generative AI by big businesses highlights its transformative potential and underscores the need for thoughtful, strategic implementation.

Small Companies

Small businesses are also harnessing the power of generative AI, particularly through the use of small language models (SLMs). These models require significantly less computational power, making it possible to run them on local machines. This increased accessibility allows smaller organizations to remain competitive and relevant in the ever-evolving market landscape. The advent of low-code and no-code platforms further democratizes AI technology, enabling businesses without extensive technical expertise to leverage these advancements effectively. To maximize the benefits, it is essential to invest in comprehensive training programs from the ground up. This approach ensures stakeholder engagement and promotes the long-term application and adoption of AI technologies, empowering small businesses to innovate and thrive in the digital age.

Big & Small

The convergence of generative AI adoption by both large and small businesses is paving the way for a more inclusive and prosperous future. Despite the promising advancements and bold claims from corporations and academics, we still have a considerable journey ahead before realizing the full potential of these technologies. Generative AI represents a suite of general-purpose tools designed to assist with a wide array of existing tasks and challenges. By granting smaller businesses access to these cutting-edge technologies, large enterprises are fostering a collaborative ecosystem. This shared access not only democratizes technological innovation but also promotes a unified approach to leveraging AI for collective growth and development. This convergence ultimately aims to create a balanced technological landscape where businesses of all sizes can thrive and contribute to a more equitable economic future.

In Closing

A good understanding of what is happening with gen AI conceptually will help protect you and your organization from misinformation and possible deception. This technology has far reaching implications far beyond large language models (LLM’s) and is ripe for other business use cases. One of the greatest challenges is figuring out what to build vs. building the technology itself. We need conceptual understanding of the technology as well as business operation understanding. It is the combinatorial effect that will produce the greatest impact and outcomes for organizations, the global economy and humanity.

References

eCornell. (2024, May 6). Watch Keynote: AI Today | eCornell. eCornell - Online Education Programs. https://ecornell.cornell.edu/keynotes/view/K052224/