Gaurav Tewari, founder and Managing Partner of Omega Venture Partners.
ChatGPT reached 1 million users a mere five days after its launch in November 2022. By January 2023, it had accumulated 100 million active users, making it the fastest-growing application in history.
The large language model (LLM) released by OpenAI is the first program to make generative artificial intelligence (AI) easily accessible to the public. Now, the generative AI market is expected to grow from $40 billion in 2022 to $1.3 trillion over the next 10 years. In this article, I aim to demystify how generative AI constitutes a distinct revolution and explore the prospective economic impacts of deploying this technology across diverse sectors.
How Generative AI Is A Gamechanger
AI has been driving value for businesses since the early 2000s; however, the majority of AI models have been discriminative, not generative. Discriminative models excel at making predictions from existing data and identifying anomalies. These models power everything from social media content recommendation engines to financial fraud detection platforms. However, these models output only discrete results—for example, “This transaction is likely fraudulent.” Generative AI systems like ChatGPT have shifted the paradigm from classifying information to creating an array of novel outputs, thus greatly expanding the set of tasks AI can perform.
Generative AI can be distinguished from discriminative, narrow AI in at least three key ways.
1. Generating Output Rather Than Analyzing Information
The goal of discriminative models is to make accurate predictions based on training data. Generative models instead create output indistinguishable from the training data. For example, a model trained on billions of lines of text can generate new lines of text instead of simply classifying whether new text is “happy” or “sad.”
2. Democratized Usability Via Natural Language Interfaces
Interacting with most discriminative AI models requires the use of specific syntax or knowledge of a programming language. This takes time to adapt to and greatly limits the range of people capable of using the model. However, generative models use Natural Language Interfaces (NLIs) to interpret text as opposed to code. NLIs reduce the technical learning curve and widen the potential user base, empowering a much larger number of people to utilize the model effectively.
3. Generalized Vs. Specialized Use Cases
Traditional models have been trained on smaller, specialized datasets to serve a specific purpose (e.g., analyze previous machine maintenance patterns to predict when servicing is necessary). Generative AI models are trained on large databases, such as the entire publicly available internet, and so can serve a much wider range and versatility of use cases.
When you combine the broader capabilities of generative models with the democratization of access provided by NLIs, the explosive rise of ChatGPT and massive generative AI market predictions become more understandable.
The Future Of Work: Augmentation Vs. Automation
Goldman Sachs estimates that generative AI could automate tasks that take up to one-fourth of employees’ time today. McKinsey estimates 60% to 70%. These assessments have sparked concerns about job displacement and an uncertain future of work.
However, most jobs are only partially exposed to automation. Instead, AI will likely serve as a complement to existing workflows rather than a substitute for an entire occupation. According to the same research by Goldman Sachs, only 7% of U.S. jobs risk automation, while 63% will leverage AI-enabled augmentation, and roughly 30% will remain unaffected.
While AI will automate some portion of jobs, it will also create entirely new occupations and sectors. Today, approximately 60% of the workforce holds positions that did not exist in 1940. Nearly 85% of employment growth since that time is due to new occupations created through technological advances. We are already seeing the beginnings of this with the advent of new roles like “Prompt Engineer.” Upskilling workers to be ready for these new roles and to be ready to make use of AI advances, in general, is one way to help maximize the positive impact AI can have on the labor market.
Major Changes: Economic Growth Predictions
Properly managing the workforce changes posed by generative AI could raise the global GDP by 7% in just 10 years. AI-enabled automation of tasks can empower employees to focus more on highly cognitive tasks, boosting overall output. Simultaneously, many of the new jobs created by the rise of AI are likely to contain higher-level work worthy of higher compensation, further boosting GDP.
While the timeline of when this labor productivity boom would occur is relatively uncertain, there is no question that the economic impacts will be significant. If generative AI lives up to its foreseen capabilities in the coming decades, we could see a technological revolution as impactful as the automobile and the personal computer.
Industries Capitalizing On The Generative AI Revolution
While generative AI will impact a wide variety of industries, 75% of its potential value spans just four sectors.
1. Customer Service: After implementing conversational AI into their customer operations, 80% of executives reported demonstrable improvements in the delivery of service and contact center performance.
2. Sales And Marketing: Investing in generative AI-powered sales identification, market optimization and personalized outreach efforts is predicted to increase revenue from 3% to 15%.
3. Software Engineering: Generative AI tools are helping programmers develop applications twice as fast by automating tedious tasks such as refactoring and documenting sections of code.
4. Research And Development: By reducing research time and optimizing testing capabilities, generative AI tools could cut costs for R&D methods by 10% to 15%.
Generative AI possesses the power to create human-like content instantaneously, unlocking new levels of productivity across various sectors of our economy. As this technology develops, I believe it will continue to empower the transcendence of previous capabilities.
Final Thoughts
Of CEOs surveyed by IBM, 75% believe businesses leveraging the most advanced generative AI will garner a distinct competitive advantage. The technology’s ability to widen the range of tasks AI can automate has already led to a reduction in time-consuming work and a subsequent surge in productivity. I believe the time is now for businesses to think about how to capitalize on generative AI to augment workflows, gain a competitive advantage and create their ideal future.
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