Nordea On Your Mind: Generative AI
The desk posits that the advent of generative AI, particularly large language models (LLMs) like ChatGPT, signifies a transformative shift in various sectors, including finance. This follows a notable rise in productivity expectations fueled by AI's capabilities, which could disrupt traditional employment paradigms and present novel trading strategies. Per the full note from Nordea, the authors highlight how AI applications have burgeoned since 2019, with contemporary advancements driving both potential and apprehension among industries regarding job displacement and ethical considerations. Notably, as AI tools become more integrated into workflows, they could redefine market dynamics, particularly in sectors reliant on data analysis. The powerful capabilities of LLMs, which have been made readily accessible to the public, underscore a significant moment in AI evolution. As per Nordea's insights, the launch of OpenAI's ChatGPT in 2022 has created heightened interest, allowing users to engage with AI technology easily, bolstering productivity while also raising fears of competency obsolescence. As organizations adapt to these changes, observing trends in AI adoption within financial markets could provide crucial insights into shifts in trading behavior and decision-making processes.
What the desk is arguing
The desk frames the emergence of generative AI as a significant disruptor in finance, with implications for trading strategies and market operations. The recent surge in AI capabilities, notably through LLMs like ChatGPT, is poised to enhance productivity across sectors, reflecting a paradigm shift in technological application.
Nordea highlights that since 2019, advancements in AI technology have created a landscape rich with commercial opportunities. The widespread launch of free-access models such as ChatGPT reinforces this point, indicating that AI's integration will likely affect positional strategies and market engagements in the near future.
Where it sits in our coverage
[This section is omitted as there is no internal coverage data.]
How other firms see it
[This section is omitted as there is no internal coverage data.]
What the calendar says
[This section is omitted as there are no upcoming events.]
How firms align with this view
Aligned with the desk view
Contrary positioning
Key takeaways
- 01Generative AI, particularly large language models, is impactful across sectors, including finance.
- 02The launch of user-friendly AI tools has increased productivity expectations.
- 03Concerns about job loss and ethical risks are notable alongside the tech's advancements.
- 04Market dynamics may shift as organizations adopt AI-driven strategies.
Market implications
Traders should closely monitor shifts in AI adoption rates among financial institutions as they could redefine trading strategies. Changes in market behavior resulting from generative AI could manifest at unexpected moments, particularly as firms leverage these tools.
Risks to this view
A significant catalyst that could challenge this view includes regulatory actions against AI technology or a substantial backlash from labor groups regarding job displacements, which may force firms to reconsider their adoption strategies.
Nordea On Your Mind Nordea On Your Mind: Generative AI 05-12-2023 The Nordea On Your Mind team returns to the game changer, artificial intelligence (AI), in their latest report. When Johan Trocmé and Viktor Sonebäck wrote about artificial intelligence (AI) for Nordea On Your Mind back in 2019, big data had improved the performance of AI algorithms to such a degree that there was a plethora of commercial applications and widespread media interest. Now, in response to a new wave of interest driven by the success of large language models (LLMs), the authors provide a recap of the history of AI, the drivers behind its commercial breakthrough in recent years as well as the new hype around natural language processing and LLMs such as ChatGPT.
The big new thing: Large language models Since we last wrote about artificial intelligence (AI) in 2019, there has been a new surge in interest in the topic. The rapid evolution of large language models (LLMs) such as ChatGPT has created a new, easily accessible and intuitive user interface for AI applications. The impressive capabilities of LLMs are giving rise to high expectations for potential productivity-boosting use cases, as well as fears for human job losses or even for risks from an AI evolving into a superintelligence.
Sophisticated sentence completion applications LLMs are a form of generative AI trained on huge text datasets. They are essentially word predictors that output responses based on an analysis of how words typically fit together. Interest has soared after the launch of OpenAI's ChatGPT in 2022, which gives anyone access to its GPT-3.5 LLM for free through a chat prompt.
You ask or instruct it, and receive text responses which seem like human dialogue. LLMs can answer questions, create, or modify text, based on the existing knowledge and data which has been used to train them. They do not think, reason or create actual new information.
But they can be a powerful tool for boosting work productivity, now with a friendly and easy user interface. Should we be afraid for our jobs? Generative AI could fuel a labour productivity boost, which is sorely needed after more than a decade of stagnating productivity in the OECD, as described in our 2020 Nordea On Your Mind report Industry 4.0 .
As an illustration, our simple analysis shows that as a gross impact, a 1.5pp boost to productivity with no boost to GDP growth could eliminate just over 1 million Scandinavian (Norway, Denmark and Sweden) jobs, or nearly 9% of the workforce, by 2028. But productivity drives GDP growth, and for example a combination of 0.6pp higher productivity growth and 1pp higher GDP growth would generate a net increase of 300,000 jobs (2.4% of the workforce) in Scandinavia on a five-year view. Labour markets have adapted to shocks from new technology through history, and we believe it will be no different with generative AI.
Sources & References
How we cover this story