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The AI-native generation is here. Don’t get left behind

The commercialization of artificial intelligence (AI) has given rise to a new generation: AI-native humans. These humans grow up with voice-activated virtual assistants, personalized digital experiences and countless automated content-creation tools at their fingertips. To this young generation, living with AI is seamless and natural. To their parents, it is a different story. 

Similar to how the parents of prior generations had to learn how to use the television and the internet while their children adopted the technology with ease, today’s adults are experiencing a learning curve with AI. This same phenomenon is occurring with mature enterprise organizations.  

Thousands of fast-moving startups emerge with AI built into the core of their products and processes, working faster and more efficiently. At the same time, large enterprise organizations are trying to retroactively fit AI into the processes they have been following for years — a near-impossible task. Rather than treating AI like a patch to repair pre-existing problems, enterprises should strategize around incorporating AI into their workflows, ensuring the data and infrastructure are in place to drive informed decision-making and productivity. While this transition can be confusing, clunky and complicated, the adoption is necessary if organizations want to remain relevant and thrive in this new era of business and technology. 

What does the process look like for an organization to transform into an AI-native company? First, one must define what it means to be AI-native. 

What does it mean to be AI-native?

An AI-native organization is one that embeds AI into the core of its operations. In other words, AI drives strategic decision-making, optimizes critical processes and fuels growth from the ground up. An AI-native company does not think of AI as a shiny new tool but as a fundamental shift to its business identity, leveraging human-like intelligence delivered by technology. 

Eventually, as AI adoption spreads, “ambient AI” will become the new normal, inducing a fully symbiotic and synchronized co-piloting between humans and AI. AI will augment human and business performance by driving real-time insights and actionable decisions. In this new normal, employees will no longer need to “make the case” for AI because the value will be clear and indispensable. 

It is important to note that becoming an AI-native company does not mean replacing human intelligence. Rather, an AI-native company blends and augments human teams’ creativity and innovation with AI’s analytical power to improve collaboration, productivity and strategization. 

4 steps to transform your enterprise organization into an AI-native company 

Becoming an AI-native company does not happen simply by purchasing any AI product. It happens by exploring the inefficiencies plaguing your business operations, figuring out how AI can help alleviate those inefficiencies, following a framework to recognize what criteria AI products must meet to solve your use case and having the right resources in place to effectively implement AI. 

Here are four steps to help you get started: 

1. Start with the problem, not the solution

AI is not a one-size-fits-all technology. Different use cases demand different data, models and architectures. Recognizing these nuances from the beginning of your AI exploration will help you build or purchase the right AI for your use case. Generally speaking, the closer the AI is to your company’s core revenue activities — such as manufacturing a product or forecasting sales — the more rigorous your standards for adoption should be, since the business impact of an incorrect output is greater.  

2. Look at your data

The success of any AI model largely depends on its ability to understand the language patterns, context and nuances of your business data. As soon as you think you are ready to adopt AI technology, pause and evaluate your data’s quality, structure and volume. Ask your team questions like: Do you have enough data to train reliable models? Is it organized and clean? Is it regularly generated? AI algorithms improve by continuously learning new data, so making sure you are constantly feeding your models the most up-to-date information is essential. 

3. Consider your resources

Not only does an AI model’s robust training require high-quality data, but it also requires more computing capabilities than those of a typical SaaS product. Take a critical look at your existing infrastructure to see if it can support the scale of your potential AI workloads. You will likely need to increase your cloud spend to support the data and hardware required to successfully operate AI. Use this knowledge to ensure you invest in the AI solutions that will bring you the strongest return on investment. 

Beyond the technical component, remember that when you transition into an AI-native company, you are not stacking AI on top of your existing tech stack but weaving it into your entire technical architecture. Doing so requires human influence. Therefore, before you initiate AI adoption at your organization, clearly define your team’s roles and responsibilities. Make sure you assign someone to lead the technical implementation efforts, as well as someone to lead the human enablement of adopting the new workflow. 

4. Refine and iterate

While artificial intelligence automates many tasks, and the future of the technology is one where AI works alongside humans to drive productivity, you cannot treat AI as a set-it-and-forget-it solution. Before you “turn on” AI for your business, determine a set of benchmarks you will use to measure its impact. These metrics could include cost savings, response rates for customer inquiries and/or time savings. Use these metrics to ensure the AI is providing the ROI you expected. Then, refine and iterate based on the results. 

Embrace the AI-native future 

Transitioning to an AI-native organization represents a fundamental shift in your everyday processes. As with the adoption of any new technology, the change will feel unnatural at first, and there will be challenges along the way, but if you stay focused and determined, the result will be well worth the effort. 

Startups are already building with AI at the forefront of their businesses. To keep up with the pace of innovation, enterprise organizations must embrace the new normal and work towards ambient AI. The future belongs to those who act today. By following the steps outlined above, you are not just future-proofing your business — you are positioning it to excel.

This article is published as part of the Foundry Expert Contributor Network.
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Category: NewsMay 21, 2025
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    Tiatra LLC.

    Tiatra, LLC, based in the Washington, DC metropolitan area, proudly serves federal government agencies, organizations that work with the government and other commercial businesses and organizations. Tiatra specializes in a broad range of information technology (IT) development and management services incorporating solid engineering, attention to client needs, and meeting or exceeding any security parameters required. Our small yet innovative company is structured with a full complement of the necessary technical experts, working with hands-on management, to provide a high level of service and competitive pricing for your systems and engineering requirements.

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