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Integration will be the next wave of AI market expansion, predicts generative AI firm Native AI

Large businesses especially have found it challenging to navigate the increasingly-complex landscape of AI applications

Photo courtesy of Native AI
Photo courtesy of Native AI

Opinions expressed by Digital Journal contributors are their own.

Throughout modern history, technological innovations have always followed the same cycle: early hype, fragmented expansion, and finally integration and consolidation. Generative AI is following this same trajectory, only more accelerated than anyone could have predicted. Barely more than a year after OpenAI launched ChatGPT, the market has already become flooded with industry-specific applications. This no-code software alleviates the need for end-user sophistication, which has lowered the adoption barrier.

Large businesses especially have found it challenging to navigate the increasingly-complex landscape of AI applications. With multiple teams requiring slightly different solutions, it can quickly become an IT nightmare. There is growing demand for all-in-one platforms that can solve for the complexity of enterprise use cases. AI startups that take a partnership-driven approach will have an advantage.

Native AI says this has become a major scaling opportunity over the past year. Previously focused exclusively on working with brands, Native AI says they are seeing a huge uptick in interest from platform and service providers to white-label or integrate their solution.

“Nobody wants to be left in the dust,” says Native AI CEO Frank Pica. “We work with individual brands, but many would rather access Generative AI solutions directly within their existing commerce and insights platforms. And software buyers have come to expect AI capabilities.” 

The race to integrate proven solutions that solve for real use cases is in full swing. Within the next two years, Pica predicts, the vast majority of platform providers will have already white-labeled or acquired Generative AI solutions.

This has been a win-win for AI applications like Native AI and the all-in-one platforms. Market research firms are enhancing human survey responses with predictive synthetic responses at a very low cost. Ecommerce platforms use generative AI to allow businesses to explore consumer purchase motivations. Marketing technology companies are using generative AI to build consumer personas for cookieless targeting and brand lift measurement. And these are just a few of the common applications within the field of consumer insights, says Pica. This integration is happening across nearly every industry.

Will AI industry consolidation amplify data safety concerns?

While consolidation can certainly lead to greater efficiency, business executives have raised concerns about data safety. Consumer data often contains personal information, and that can cause serious harm if the data is used for model training. “We obviously take data privacy and security very seriously, and It’s important for people to realize that there is a difference between model training and data inference,” says Native AI CTO Mike Jackson. “AI applications like ours are built on top of the latest, most accurate, foundational models. For example, we use three separate models to produce the best results for one of our question and answer solutions: Claude 3 for conversational AI, Open AI’s GPT 4 for text embeddings, and Mistral-7B for question generation and short question answering. It’s important to understand customer data is not contributing to training of these models.”

Jackson is describing Retrieval-Augmented Generation, or RAG. This process allows applications like Native AI to reference first party data by ingesting it into a Large Language Model without model training or fine-tuning. “We are at an inflection point with regards to the AI learning curve,” says Jackson. “The early days of AI have given leaders a healthy level of skepticism,” he says, “but we’re doing our part to make sure everyone knows exactly how we’re keeping their sensitive data safe within our platform.”

Ultimately, the market will decide whether industry-specific AI applications will remain independent or merge with all-in-one platforms to create competitive differentiation. But one thing is for certain: the demand for predictive AI functionality is not going away anytime soon. To learn more about how Native AI can enhance your own platform offering, visit gonative.ai.

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Jon Stojan is a professional writer based in Wisconsin. He guides editorial teams consisting of writers across the US to help them become more skilled and diverse writers. In his free time he enjoys spending time with his wife and children.

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