Generative AI is here – is your company a resilient leader or a follower?
This article is the first part of a two-part series that sheds light on two categories of resilience: technological and ESG, stemming from dialogues across the Danish and American ecosystems. For each category, the focus is on companies in the USA that present a strategy and approach to navigating challenges and building robustness within their field.
This article was published by Ingeniøren on May 28, 2024 [in Danish]
We are in a polycrisis.
The COVID-19 pandemic, climate change, and geopolitical conflicts and uncertainties have highlighted the necessity for leaders to embrace a new, future-driven mindset to navigate successfully and strengthen their competitiveness.
But how can companies prepare, respond, and even emerge stronger in a world where the future is uncertain, and changes occur rapidly?
facts what is technological resilience?
Technological resilience is broadly defined as an organization's ability to overcome challenges when new disruptive technologies emerge, and its capacity to adapt quickly under such circumstances.
American perspectives can provide Danish leaders with new inspiration
One of the most debated and significant technological breakthroughs in recent times is generative AI (GenAI) and its potential to fundamentally transform businesses, organizations, and even entire societies.Since the introduction of OpenAI's ChatGPT in November 2022, society has been trying to harness GenAI to accelerate innovation and creativity, as well as automate routine tasks to save valuable time and resources.
But how is technological resilience built?
Bloomberg, Morgan Stanley, and Databricks each have their own perspectives on this.
They shed light on the challenge that companies across sectors face: Should one buy new technology, develop in-house, or partner with tech giants or other technology providers? Regardless of the approach, Danish leaders can find valuable inspiration by looking at how some of the U.S. giants navigate the GenAI landscape.
facts build, buy, or partner?
The following strategies are among the most common and accessible when it comes to building capabilities within GenAI.
Build Strategy: This involves developing GenAI solutions in-house by leveraging the organization's internal resources. Companies may choose this strategy when they have the expertise and resources to create a customized solution tailored to their specific needs.
Buy Strategy: This involves acquiring companies that possess established technologies, products, or services. Companies may opt for this approach when they lack internal expertise and seek specific skills or tools that a particular company possesses.
Partner Strategy: This involves collaborating with external companies, such as AI firms or technology providers, to develop or access the necessary technology or competencies. Companies may pursue partnerships to leverage complementary strengths, share resources, or access specific expertise without having to develop or purchase a solution independently.
A partnership with benefits and risks
The leading global investment bank and wealth management firm, Morgan Stanley, aims to stay at the forefront with a strategy where technology and innovation are crucial components for long-term success and survival:
Morgan Stanley aims to leverage OpenAI's breakthrough technology for a competitive edge in how their financial advisors can utilize Morgan Stanley's collective knowledge and insights in ways previously deemed impossible, explains Andy Saperstein, Head of Wealth Management and Co-President at Morgan Stanley.
In partnership with OpenAI, they are navigating the rapidly evolving era of GenAI and have developed a chatbot that generates unique responses based on their proprietary data, including investment strategies, market research, commentary, and insights from analysts.
The chatbot scans thousands of internal documents and provides answers to financial advisors within seconds, a task that would otherwise require significant time for the advisor to perform.
Through this partnership, Morgan Stanley gains access to OpenAI’s latest AI solutions—which in itself can provide a competitive advantage—as well as tailored support from software engineers and scientists.
However, the partnership strategy is not without risks. Morgan Stanley depends on OpenAI for the construction of their GPT, creating potential vulnerabilities that could arise from changes in OpenAI’s priorities, capabilities, or business strategy. This was illustrated by the turmoil at OpenAI in November 2023 when the board fired CEO and co-founder Sam Altman, casting doubt on the company's future direction and existence. After protests from employees and Microsoft, which owns 49 percent of OpenAI, he was ultimately reinstated.
Additionally, Morgan Stanley must ensure that proprietary data remains protected and fully owned. Technological advancements require vigilance to stay ahead and avoid being surpassed by more agile and technologically savvy competitors.
It's time to move out of the slow lane and into the resilient fast lane
Morgan Stanley’s partnership with OpenAI is just one example of how companies can join the GenAI race. Among the build and buy strategies, we find Bloomberg and Databricks.
Bloomberg built its own large language model (LLM), BloombergGPT, with the vision of becoming the first and leading LLM in the financial sector. They created an enormous dataset - their 'crown jewel' - with over 700 billion tokens to train the model. Developing their own LLM requires significant investments in both time and resources, as well as the ability to maintain and attract top talent in AI and data engineering.
Conversely, Databricks acquired expertise and new technology through the purchase of the GenAI startup MosaicML for approximately USD 1.3 billion—the largest GenAI acquisition to date. The MosaicML platform provides companies with easy access to train and run LLMs on their own proprietary data while maintaining complete ownership over the data and GenAI models. This acquisition has strengthened Databricks' position within open-source GenAI.
From a Silicon Valley perspective, there is no single right strategy. Ultimately, it’s about how GenAI aligns with the company’s strategic or tactical goals. If the implementation of GenAI is deemed to create a competitive advantage or transformative effect, it signals strategic significance.
This places higher demands on the company's own competencies, data security, and ownership, but the reward is enhanced resilience. Therefore, now is the time for Danish companies to act and prepare for the future.