Latin America 10 Year Outlook

A new era of generative AI for everyone, The technology underpinning ChatGPT will transform work and reinvent business

The United States has strived to address digital inequities in the Internet economy through programs that combat the “digital divide.” But in the data economy, a number of social and economic inequities arise from a lack of data collection or use of data. These inequities—the “data divide”—require new policy solutions to ensure that all Americans are represented in data and can put it to use. To tackle this new challenge, policymakers face two starkly different options: Option A) hold back data collection and data-driven technologies until they are equitable for everyone; or option B) allow the data-driven technologies to prosper while working to increase access for everyone. To close the digital divide, U.S. policymakers have chosen option B. But for the data divide, many are flirting with option A, when they should be choosing option B.

The State of AI Global 2022 recap provides comprehensive data and analysis on dealmaking, funding, and exits by private market AI companies. Some key findings include that global AI funding reached a new high in 2021, with $83.4B invested across 5,064 deals. Additionally, the report highlights the top AI investors and the most active AI acquirers. For more information on the report's findings, please refer to the relevant pages in this PDF file.

The McKinsey Global Institute's research on Artificial Intelligence highlights the promise and potential of AI to boost profits and transform industries. The report also notes that while AI technologies have advanced significantly in recent years, adoption remains in its infancy. The paper provides case studies of digital natives and responses from their survey, which show early evidence that AI implemented at scale delivers attractive returns. Additionally, the report discusses the challenges associated with the widespread adoption of AI, including making the business case for investment and ensuring algorithmic transparency and accountability.

Artificial intelligence (AI) researchers have been developing and refining large language models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks, challenging our understanding of learning and cognition.