The commercialization of artificial intelligence (AI) has given rise to a new generation: AI-native humans. These individuals have grown up with voice-activated virtual assistants, personalized digital experiences, and automated content-creation tools at their fingertips, making living with AI a seamless and natural experience. In contrast, their parents and mature enterprise organizations are experiencing a learning curve as they try to adapt to this new technology.
The Challenge for Mature Organizations
Thousands of startups are emerging with AI built into the core of their products and processes, working faster and more efficiently. Meanwhile, large enterprises are struggling to retroactively fit AI into their existing processes, which proves to be a near-impossible task. Rather than treating AI as a patch to repair pre-existing problems, enterprises should strategize around incorporating AI into their workflows, ensuring they have the necessary data and infrastructure to drive informed decision-making and productivity.
Defining an AI-Native Organization
An AI-native organization is one that embeds AI into the core of its operations, using it to drive strategic decision-making, optimize critical processes, and fuel growth from the ground up. AI is not seen as a tool but as a fundamental shift in the business identity, leveraging human-like intelligence delivered by technology. As AI adoption becomes widespread, “ambient AI” will become the new normal, enabling a fully symbiotic and synchronized co-piloting between humans and AI.
Four Steps to Become an AI-Native Company
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Start with the Problem, Not the Solution
- Recognize that AI is not a one-size-fits-all technology.
- Different use cases demand different data, models, and architectures.
- The closer AI is to your company’s core revenue activities, the more rigorous your adoption standards should be.
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Evaluate Your Data
- Assess the quality, structure, and volume of your data.
- Ensure you have enough data to train reliable models.
- Verify that your data is organized, clean, and regularly generated.
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Consider Your Resources
- AI adoption requires high-quality data and more computing capabilities than typical SaaS products.
- Assess your existing infrastructure to support AI workloads.
- Define your team’s roles and responsibilities, including technical implementation and human enablement.
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Refine and Iterate
- Determine benchmarks to measure AI’s impact, such as cost savings, response rates, and time savings.
- Use these metrics to ensure AI provides the expected ROI.
- Refine and iterate based on the results.
Embracing the AI-Native Future
Transitioning to an AI-native organization represents a fundamental shift in everyday processes. While the change may feel unnatural at first, with challenges along the way, staying focused and determined will make the result worthwhile. By following these steps, enterprise organizations can future-proof their businesses and position themselves to excel in the era of ambient AI.
