Change in the field of AI is happening at an exponential rate, particularly in industries like healthcare. In just a few years, the use of AI in healthcare has gone from being an emerging field to a key driver of innovation. As we enter 2022, it is clear that AI has the potential to revolutionize healthcare and other sectors.
Key Takeaway
AI-first companies have the potential for greater impact, financial returns, and long-term competitive advantage compared to AI-enabled companies.
The Rise of AI-First Companies
AI-first companies are those that prioritize the advancement of AI as a scientific discipline. In contrast, AI-enabled companies focus on implementing and distributing AI technologies. These two approaches establish moats at different levels of the industry. AI-first companies innovate at the core AI level, while AI-enabled companies create value by applying AI technologies to specific use cases.
However, it is important to note that this distinction is not binary. The most successful companies will likely combine elements of both approaches. Nonetheless, the future belongs to AI-first companies that have tight control over the technology stack, enabling them to optimize costs, explore product options, and establish a stronger competitive position.
Imperatives for Building AI-First Companies
For founders looking to build enduring AI-first companies in healthcare and other sectors, here are six key strategies to consider:
1. Create and sustain an undeniable data advantage
AI-first companies thrive on data and seek to acquire it creatively and sustainably. In addition to utilizing large and diverse datasets, these companies develop proprietary datasets that are specifically designed to excel at specific tasks. These unique datasets are machine-readable and scalable, enabling high-performance AI models.
For example, Subtle Medical, an AI-first healthcare company focused on imaging acceleration, generated millions of imperfect MRI images to train their deep learning models. By doing so, they were able to create a data advantage and develop a moat for their technology.
Furthermore, AI-first companies should leverage reinforcement learning with expert human feedback (RL(E)HF). This technique involves training AI systems by incorporating feedback from human experts in specific domains. By doing so, models can be fine-tuned to deliver high performance in those domains.
2. Recruit and empower AI scientists
Building an AI-first company requires a strong team of AI scientists. Founders should focus on attracting top talent with deep expertise in AI research and provide them with the necessary resources and autonomy to drive innovation. This includes fostering collaboration across disciplines and creating an environment that encourages continuous learning and experimentation.
3. Forge partnerships with aligned investors
AI-first companies often require more capital and longer-term support compared to AI-enabled companies. It is crucial to find investors who understand the unique challenges and opportunities of building AI-first companies and are willing to take a long view. Collaborating with aligned investors can provide the necessary financial resources and strategic guidance to navigate the complex landscape of AI research and development.
4. Develop a viable business model
A strong business model is essential for the success of AI-first companies. While unconventional approaches may be necessary, founders should focus on creating a sustainable and scalable model that aligns with the company’s long-term vision. This may involve a combination of proprietary technology, strategic partnerships, and innovative revenue streams.
5. Embrace interdisciplinary collaboration
AI-first companies thrive on interdisciplinary collaboration. By bringing together experts from different fields, such as healthcare and life sciences, these companies can leverage diverse perspectives and domain knowledge to drive innovation. This collaboration can lead to breakthroughs that have a real-world impact, particularly in vertical-specific platforms.
6. Stay ahead of ethical and regulatory considerations
As AI technologies continue to advance, ethical and regulatory considerations become increasingly important. AI-first companies should stay ahead of these issues by closely monitoring developments in the field and actively engaging with policymakers and regulators. By proactively addressing these concerns, companies can build trust with stakeholders and ensure the responsible deployment of AI technologies.
Conclusion
AI-first companies have the potential to revolutionize industries like healthcare and life sciences. By following these six imperatives and embracing AI as a scientific discipline, founders can build enduring companies that drive innovation and create lasting impact. The future belongs to those who prioritize AI research and development, and harness the power of revolutionary technologies like AI.
