You’ve been hearing a lot about Artificial Intelligence, or AI recently and may have questions. What is AI, and specifically generative AI like ChatGPT and why is everyone talking about it? We’ll address the what and why in this AI primer.
Twenty-five years ago, IBM’s Deep Blue defeated chess grand champion Gary Kasparov and the world took notice of artificial intelligence or AI. Today, thanks to AI, computers have learned to write poetry, smartphones find the quickest route to the office, and driverless taxis transport passengers in several large cities.
Although AI is not a new concept, only recently have three key ingredients – big data, faster computers, and machine learning algorithms – converged to propel AI increasingly into new uses. Today, researchers are fine-tuning large language models that allow computers to recognize, predict, and write human language – and even poetry – using billions of parameters.
Artificial Intelligence and more specifically, large language models like ChatGPT have garnered much discussion over the past few months. We have seen excitement building around the development of generative AI and subsequent disruptions that may impact multiple industries over the longer term given its focus on productivity, efficiency, and cost reduction. Generative AI has the ability to create new content, moving beyond traditional AI’s data analysis and improved forecasting capabilities.
Generative AI’s two most visible potential impacts are on labor productivity and the job market. A recent McKinsey & Company study estimated that generative AI could boost the U.S. economy average annual productivity growth by 50% between now and 2040. The potential boost can be expected to come from AI’s ability to speed implementation of new ideas, and in the process accelerate innovation.
An aging workforce and slowing growth of labor supply is increasingly weighing on the economic growth potential for the U.S. and global economies, and AI’s potential for productivity gains is therefore coming at a critical time. Stronger productivity growth would help accommodate healthier, noninflationary wage gains and resulting improvements in household living standards.
The McKinsey study estimated that industries within the Healthcare, Financials, and Industrials sectors could see the greatest value add through AI implementation. For example, AI could deliver improvements for banks and other financial services firms in fraud detection and risk management, and customer interactions. Research, drug discovery and development, patient care, data management, and documentation are all likely to experience step-level improvements with the proper application of AI within the Health Care sector. AI’s largest potential benefit to companies in the Industrials sector will likely arise from supply-chain optimization, efficient warehousing, factory optimization and research & development.
As with any new technology, new risks develop. Risks and questions have already surfaced around the outcomes generated by hallucinating large language models. For example, issues have arisen around ChatGPT providing answers with conviction that turn out to be inaccurate. Since the large language models were trained on the structure of language, these models are more focused on the structure of which word or what concept comes next and less focused on whether the answer is accurate.
Despite all the excitement we think it is too early to tell how much traction companies will gain in terms broadly adopting generative AI going forward. Historically markets have often priced in technological advances well in advance of adoption. Regulation is likely to accelerate and may need time to balance economic growth and social concerns. We always favor a clear eyed evaluation of risk and reward in every investment decision and that remains true in the early stages of even transformative technology.
While the road to adoption may be longer than anticipated and regulatory risks prevail we believe with conviction that AI will help to boost U.S. productivity gains and advancements in the coming decades.
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