By Jonathan Chin
We are in the midst of a technological revolution, propelled by the advent of generative AI. This is not just another incremental advancement in the world of technology. It is a radical, transformative shift akin to the major technology revolutions that have reshaped our world in the past. What sets generative AI apart is its potential to impact not just the technological sphere, but also industries that seem far removed, such as the creative arts, photography, graphic design, news, and content production. Rarely does innovation have the power to shake up multiple industries simultaneously, creating opportunities, disrupting norms, and redefining boundaries.
In essence, generative AI is rewriting the rules across diverse industries. As we continue to uncover its potential, we can expect even more disruption and innovation. The only question is, how quickly can we adapt and what new boundaries can we redefine with generative AI at our disposal?
The data explosion: a prelude to transformation
As we delve into this topic, it’s essential to understand the backdrop against which this AI revolution is unfolding – the explosion of data. The digital age has engendered a proliferation of data, with more information generated in the past two years than in the preceding decade. This has spurred the evolution of big data tools in the 2010s, making it economically viable and straightforward to store and query vast data sets.
The notion of being a data-driven enterprise is no longer a niche or novel idea. It has emerged as a core strategy for businesses, seeping into every roadmap, agenda, and strategic planning session. Yet, even with this surplus of data and seemingly limitless computing and storage capabilities, extracting actionable insights remains a complex and technical discipline. Business users often rely on an army of data engineers, scientists, analysts, and visualization tools to decipher the data and answer their questions.
The convergence of large language models: A game-changing future for data
In the world of AI, fierce competition is underway between the big players such as OpenAI, Google, and Amazon, each striving to develop and perfect their own Large Language Models (LLMs). These behemoths of machine learning are rapidly evolving, expanding, and improving, transforming the landscape of AI as they progress.
As we move into this new era, the ability for these models to learn from and interact with specific data sets could become the game-changing differentiating factor.
Imagine a future where not only are these models capable of generating human-like text, but they’re also able to understand and interact with the vast oceans of data that companies and individuals have at their disposal. Picture an AI that can sift through terabytes of data to provide accurate and meaningful answers to complex questions at the speed of thought.
This is the realm where generative AI combined with data analytics can truly shine. No longer will data analysis be a time-consuming process requiring a deep technical skillset. Instead, anyone with a question about their data could receive answers almost instantaneously, and the implications of this shift are immense.
The ability to combine the conversational fluency of a generative AI with the data-processing capabilities of big data analytics represents a compelling proposition. For businesses, it could democratize access to data insights, making every employee a potential analyst and empowering decision-making at all levels. For individuals, it could mean a level of personal data understanding previously unattainable.
So, while the converging capabilities of LLMs from different developers may make it harder for users to distinguish between them, the true differentiation may lie in their ability to interface with and learn from data. This fusion of generative AI and big data promises a transformative impact that could revolutionize industries, redefine roles, and democratize data literacy like never before. As we brace for this future, the question isn’t which model will lead the way, but how swiftly we can adapt and evolve in this new data-driven landscape.
Generative AI: The democratization of data and the emergence of a new skillset
This is the juncture where generative AI shows its true potential as a transformative force. Capable of transforming extensive data sets into interactive Q&A interfaces, generative AI demystifies data analytics, making it accessible to all business users, regardless of their technical proficiency. We are looking at a phenomenon that could completely overturn the traditional model of business intelligence and data analytics.
Traditionally, the requirement for reports or dashboards is set at the business level before being funneled into a technical workflow for execution. This method is not only time-consuming and expensive, but it also creates an unwieldy divide between business users and data insights. Generative AI promises to disrupt this status quo. In the future, a business user will need to do nothing more than pose a question to retrieve the required information. Suddenly, analytics and insights become as fluid as conversation, breaking free from the constraints of project timelines and process workflows.
In this context, data analytics as a standalone job, function, or discipline could become obsolete. Instead, it will evolve into a skillset, something akin to data literacy, that everyone will need to adopt as data access becomes democratized. The technical barriers traditionally associated with data will fall away, and data literacy will emerge as a required skill for all, not just a select few.
While forecasting the future with absolute certainty is impossible, the trajectory seems clear: enterprises that harness this form of data empowerment will leapfrog over those that don’t. Generative AI will not only streamline processes, but will also democratize data, fostering a data-driven culture that is far more inclusive and empowering.
In conclusion, the emergence of generative AI signals a significant turning point, a transformative leap in technology set to reshape entire industries. By marrying AI with big data, we stand on the threshold of a new era, one that will see dramatic changes in how businesses function and industries evolve.
About the author
Jonathan Chin is the Co-Founder and Head of Data and Growth at alternative data company Facteus. Â