The interest in generative AI as a tool to improve productivity and ROI has skyrocketed since ChatGPT’s explosive arrival in 2022. In fact, according to McKinsey research from 2025 [https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai], 62% of corporate survey participants say their businesses are actively experimenting with AI adoption.
However, generative AI models (like ChatGPT) are no longer the only AI options for forward-leaning organizations. Indeed, vertical AI is trending as a more focused solution to allow companies to squeeze more profitability from AI.
Going Deeper Instead of Wider
Vertical AI uses the same basic premise of generative AI by leveraging deep learning to create unique outputs based on historic and incoming pools of data. But vertical AI isn’t generalized like generative AI. Rather than being a one-size-fits-all AI solution, vertical AI is fine-tuned to fit the niche needs of a company’s or industry’s operations.
This isn’t to suggest that generative (horizontal) AI products like generic chatbots can’t be useful. They can, and are making it possible for lean startups and smaller businesses to compete in new, cost-effective ways. That said, vertical AI goes farther because it can automate and continuously improve complex, multi-step processes. As a result, companies that embrace vertical AI can reap significant benefits, starting with the ability to meet the demands of modern customers.
Today, customers want always-on experiences that feel intuitive and personalized. Vertical AI can deliver those experiences in a way that horizontal AI can’t. Why? Vertical AI engagement tools are designed to be industry-specific, meaning they make better sense within the context of the customer interaction.
Another benefit of vertical AI is its ability to overcome common talent shortage issues. For example, a vertical AI product can be created to streamline precise, organization-specific workflows. It won’t vary from its set parameters, making it a safe way to automate essential processes when labor isn’t available.
Finally, vertical AI can speed up the knowledge and effectiveness of human workers. A recent McKinsey piece [https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/the-economic-potential-of-generative-AI-the-next-productivity-frontier#business-value] noted that a high-volume, 5,000-representative call center successfully used an AI product to improve the capabilities of its novice representatives. The AI product was trained to learn the “secrets” of the more seasoned representatives. The AI then used those insider techniques to help novice representatives sound and act like their more seasoned colleagues.
Transforming business across multiple industries
Nearly any industry can be transformed by adopting vertical AI, and three industries have already embraced vertical AI in winning ways.
1. Automotive retail sector
Buying, leasing, and servicing vehicles involves meeting the needs of huge numbers of customers who are all at different stages. One customer might be interested in taking a test drive, for the third time. Another might be nearing the end of a lease or scheduling services for more than one car. Though human employees have historically taken care of these tasks, their responsibilities become more difficult as their volume of customers grows.
Vertical AI platforms and applications such as agentic AI solutions can close any friction points, gaps, or inefficiencies for dealers. And best-in-class vertical AI products are already trained on data from the automotive retail sector, making them a perfect fit right out of the box.
Case in point, one Ford dealership invested in the Impel vertical AI platform [https://impel.ai/platform-overview/] to handle a growing number of incoming leads that its personnel couldn’t realistically manage. Using the Impel AI Chat product, the dealership booked 1,500 showroom appointments over three months without the need for human involvement until staff were truly needed. This meant fewer lost leads and many more sales opportunities without incurring additional labor costs.
2. Medical and healthcare field
As in the automotive retail sector, healthcare organizations are constantly handling the needs of customers at different stages. At the same time, the expectations, regulatory demands, and labor challenges of healthcare are making it harder for providers to operate efficiently.
In this environment, vertical AI products can take over administrative tasks, such as patient intake and scheduling duties. Additionally, vertical AI can interpret data to trigger patient reminders or alert medical staff to potential issues.
According to leading professional healthcare products corporation Phillips [https://www.philips.com/a-w/about/news/archive/features/2025/ai-in-radiology-three-keys-to-real-world-impact.html], vertical AI is also shaking up radiology in an impactful and positive way. A full 85% of radiologists told Phillips they believe AI can bring more efficiency and consistency to their work. For instance, one radiologist shared that he leaned on vertical AI to assist him in analyzing images so he could spend more time working with people.
3. Manufacturing and industrial spheres
In manufacturing, speed can be both an asset and a liability. However, vertical AI applications can provide speed without incurring risks like inconsistencies, human errors, compliance problems, and accidents.
Wherever a manufacturer experiences a pain point, vertical AI may be able to fill in gaps and eliminate future concerns. That’s good for any manufacturing company that’s trying to meet all regulations while still remaining ahead of the competition.
An illustrative example of vertical AI’s use in manufacturing is streamlining complicated supply chain processes. As an IBM article [https://www.ibm.com/think/topics/vertical-ai-agents] explains, an industry-centered vertical AI solution can spot anomalies in production data that might indicate short-term equipment problems. Having this knowledge before an incident could save money and avoid supply chain interruptions.
Horizontal AI will always have a use in society, but vertical AI is beginning to take over the business landscape. Thanks to its versatility, it’s becoming a must-consider product for organizations from a growing network of industries.
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