Why the tech sector can't build a sustainable ecosystem for Large Quantitative AI models alone

Artificial Intelligence (AI) technologies hold enormous potential for advancing humankind through breakthrough applications in healthcare, finance, telecommunications, manufacturing, cybersecurity, defense, technology and more.

While AI technologies have been in use in one form or another for decades, the mainstreaming of generative AI and Large Language Models (LLMs) has significantly boosted demand for AI applications and increased R&D.

Currently, model developers like OpenAI and Anthropic are aligning with and competing against major tech players like Amazon, Google and Meta to become the dominant players in AI.

Separately, government agencies are investing heavily to modernize their systems and implement AI strategies to protect their national security and interests, aiming to gain a competitive edge financially, economically, militarily, and culturally. Despite this progress, a lack of cohesion and information-sharing among public and private entities risks leading to significant missed opportunities to alter the course of economic, scientific and social progress.

For AI ecosystems to scale effectively, there must be a deliberate alignment of interests across governments, private enterprises and civil society. Scaling AI ecosystems means much more than developing a robust tech sector. Rather, it focuses on higher-value AI capabilities and functions that will benefit industry and individuals. For instance, while Gen AI and LLMs have made an indelible mark on business and society, their impact is mainly limited to the digital world.

The next evolution of AI, led by the proliferation of Large Quantitative Models (LQMs), will drive measurable impact on our physical world by creating more effective new drugs, better, safer products, more robust financial systems and a healthier planet. Undoubtedly, there is a critical interplay between the tech and public sectors. The tech sector needs hospitable laws and policies, a solid infrastructure and an educated workforce to thrive. The public sector relies on tech insights and innovations to identify critical technologies and modernization opportunities that form the basis of its long-term IT objectives.

But the AI ecosystem includes far more than just tech firms and the public sector — all have a role to play in delivering on the promise of quantitative AI:

Academia: Education and workforce development are critical to ensuring the growth and stability of the AI ecosystem. Without a steady stream of skilled data and computer scientists and postdocs across various disciplines, the world will be unable to fill the growing demand for AI applications. Academic institutions should prioritize and encourage STEM education and recruit seasoned tech execs to train the next generation of AI leaders and entrepreneurs to perpetuate the cycle.

Business and finance: Tech innovation springs from visionary leaders with inspiring ideas, but it lives or dies based on available capital. To that end, the banking and investment communities will play a pivotal role in ensuring the most promising technologies are cultivated and nurtured. Initial stages of R&D — particularly with advanced technologies like AI — can be capital-intensive before reaching full potential. This process will require forward-thinking focus and corresponding investments to sustain innovation from its outset.

Business and industry: Facilitating and encouraging dynamic thinking and innovation is essential to spurring innovation. Establishing foundational elements such as AI incubators and accelerators, as well as industry/academic partnerships for workforce development and commercialization opportunities is critical. Corporations must also invest in upskilling existing employees on these cutting-edge technologies, providing them with a clear path for career growth and strengthening retention.

In the public sector, governments must also make strategic investments in AI technologies not only through grants and tax credits but also through modernization efforts that create jobs and business opportunities for startups and established enterprises that improve the lives of their citizens.

To successfully scale the AI ecosystem, a collaborative framework must be developed to identify challenges and align efforts across the tech, business, financial, academic, scientific, and government sectors. Working together to establish long-term, strategic AI objectives is essential to ensuring that all parties—including the general public—benefit from these transformative technologies and that businesses, schools, and government agencies take the lead in building a healthier and more sustainable future.