Vertical AI and Why It Matters: What B2B Companies Need to Know

According to a 2024 Statista survey, roughly 52% of B2B marketers in the US used AI for content-related efforts, followed by coding and presentations at 39% and 35%, respectively. McKinsey & Co.’s 2024 B2B Pulse Survey, on the other hand, found that 21% of surveyed commercial leaders in the B2B seller market have fully enabled enterprise-wide adoption of gen AI in B2B buying and selling.

However, as more industries integrate AI, companies have discovered that off-the-shelf tools often fail to meet their needs. General-purpose models can struggle with the nuances of industry-specific data, requirements, and language, leading to outputs that are inaccurate or too broad to be useful.

Industry-specific AI solutions offer a solution to this problem. These tools are designed with the workflows and data of a specific industry in mind, making them better suited for B2B environments and operations. Even so, not every development team builds with that kind of context in mind. Without strong vertical AI expertise, the solutions are more likely to miss the mark, regardless of how advanced the technology may be.

Considering AI for your business? Learn about the benefits of AI for business growth. 

What is Vertical AI? 

Vertical AI, also known as domain-specific AI, is a type of AI designed for and tailored to companies within a particular industry or domain. Where generic, or horizontal, AI is widely applicable to businesses across various fields, solutions built with vertical AI expertise utilize industry-specific data, trends, and language to target the unique needs of a specific market.

For example, a vertical AI solution for the healthcare sector might analyze test results and patient records to help doctors with clinical decision-making and diagnostics. A legal-focused AI, on the other hand, might specialize in reviewing contracts, parsing case law, or flagging regulatory risk. Both of those solutions would be built with industry-specific compliance and privacy laws in mind.

How B2B Companies Benefit from Tailored AI Partnerships

AI solutions, while useful, are incredibly challenging to implement without assistance. Gartner reports that 85% of all AI projects fail due to poor data quality or a lack of relevant data.

For B2B companies, these challenges are often compounded by complex systems, siloed information, and use cases that require a thorough understanding of industry norms and operations. Even if a company has access to a wealth of internal data, leveraging it for AI training requires time, planning, and specialized vertical AI expertise.

That’s where the right development partner can make a difference. Industry-tailored AI partners are better equipped to work with the data you have, understand your operational context, and design solutions that fit the way your business runs. They can even build synthetic data for your use case, or run limited-scope proofs of concept to better understand what data you’re missing—and how to work around it.

By partnering with development teams with vertical AI expertise, companies get a number of benefits:

• Faster Alignment: Industry-specific AI partners are already familiar with your market’s terminology, challenges, and priorities. That familiarity shortens the learning curve, reduces the need to over-explain internal processes, and helps move projects from discovery to implementation efficiently.
• Greater Relevance: Vertical AI solutions are trained on industry-specific data, leading to smarter models, more precise outputs, and fewer irrelevant or misleading results. This makes the technology more useful from the outset and reduces the need for post-deployment adjustments.
• Smoother Integration: B2B companies often work within established systems or legacy infrastructure, with McKinsey reporting that 70% of the software powering Fortune 500 companies was developed 20 years ago. However, modernizing these systems with AI implementation for enterprises is complicated. Teams with vertical AI expertise are more likely to understand this and how to fit new AI solutions into these existing environments without creating disruption.
• Less Rework and Customization: An off-the-shelf AI solution might require significant modification to meet the needs of a particular use case. A partner with vertical AI expertise can help you avoid unnecessary retrofitting by designing the right solution from the start.‍

‍Interested in learning more about AI infrastructure and implementation? Learn how to choose your AI backbone. 

Real-World Use Cases of Vertical AI in Action

Vertical AI can mean different things depending on the industry, the problem being solved, and how you approach AI solution development. The best way to understand its impact is to look at how it performs in context, with real data, workflows, and goals in play.

Here are a few examples of how vertical AI expertise is being used in real-world settings.

Vertical AI for Logistics

For logistics companies, document processing involves a high volume of industry-standard forms, each with its own format and level of complexity. Systems also need to meet strict accuracy standards and scale reliably as demand grows—requirements that generic tools rarely address well.

FullStack Labs collaborated with a leading logistics technology provider to develop an AI-powered system specifically designed to meet those exact needs. The solution utilized document classification and extraction workflows to accommodate the types of paperwork that logistics teams handle on a daily basis.

Within 90 days, FullStack delivered a proof of concept that reduced processing times by four times and led to projected cost savings of up to 50%. The system was built to handle the variability and volume that define logistics operations, without relying on one-size-fits-all assumptions, thanks to our vertical AI expertise. 

Want to deploy AI in your development process? Discover how to implement AI-enabled development in any industry. 

Vertical AI for Finance

Companies in the financial and banking industries regularly manage complex, detail-heavy records, such as tax documents, transaction histories, and customer profiles. Human teams can spend hours analyzing and processing this data, which slows down reporting cycles and leaves room for costly errors. 

Many companies are already turning to AI to streamline this process. According to KPMG, one major financial firm claims that AI has made their KYC processes 90% faster, while another major bank says that AI has reduced their number of false positives by 60%. Additionally, a report by the Boston Consulting Group found that implementing vertical AI for risk and compliance checks has led to a greater than 50% cost benefit, making a promising case for industry-specialized AI solutions. 

Vertical AI for Legal

AI has the potential to revolutionize the B2B legal industry and the average lawyer’s workload. According to Thomson Reuters’ 2024 Future of Professionals Report, AI could save lawyers 4 hours per week while generating $100,000 in new billable time per lawyer annually. As 42% of legal professionals surveyed in the report also want to spend more of their time on expertise-driven legal work, it’s clear that there’s a demand for this extra time. 

However, while 63% of lawyers surveyed by Thomson Reuters have used AI for work, general AI tools can backfire. For example, during a case against Avianca Airlines, lawyer Steven Schwartz turned to ChatGPT to conduct his legal research. Instead of citing real cases, the AI hallucinated several fictitious ones and assured him they were real. Schwartz then referenced these cases when filing a response, which ultimately led to sanctions against him, his fellow lawyer, and his law firm.

Fortunately, while ChatGPT may not be suitable for legal work, other companies have stepped up to create solutions specifically for the industry. Harvey AI is one such example. While it uses OpenAI as a skeleton, Harvey references all of US case law and uses vertical AI expertise to generate relevant, highly accurate results.

“97% of the time, the lawyers preferred the output from the case law model,” said Winston Weinberg, founder of Harvey AI. “Usually, it was because it was a longer, more complete answer. It went into the nuance of what the question was asking and covered more relevant case law.”

Choosing the Right Vertical AI Partner: What to Look For

While many development firms might claim to have experience in your industry, not all of them have proper vertical AI expertise. Knowing how to tell the difference can save you time, money, and unnecessary rework. Here are a few ways to find proper industry-specific AI partners.

1. Strong Industry Experience: When assessing companies with vertical AI expertise, their past engagements are the strongest indicator of suitability. A qualified partner will have a proven track record of delivering successful solutions in your industry, accompanied by relevant case studies and positive testimonials from past clients.
   
   For example, at Fullstack Labs, we’ve worked with clients in logistics, marketing, and finance to build AI tools suited to their unique needs. You can explore a few of those projects on our Case Studies page here. 

2. Informed Questions: Industry-specific AI partners will ask questions that show a working understanding of your industry instead of surface-level prompts. They’ll be curious about how your workflows are structured, where your data lives, and what operational challenges you're trying to solve.
   
   
3. Familiarity with Industry Tools: Different industries often rely on different systems, formats, and processes. A partner with vertical AI expertise should be comfortable working with the platforms you already use and know how to design around the limitations or quirks that come with them.
   
   
4. Realistic Scope and Planning: While it can be tempting to work with a company that completely agrees with you, a knowledgeable team will understand when to push back. Partners with experience in your space will be better equipped to set practical expectations, identify common roadblocks, and help shape a project that’s both ambitious and achievable.

If you’re interested in working with a development company with vertical AI expertise, FullStack Labs can help. We’ve built AI solutions for B2B companies across logistics, marketing, finance, and more, each tailored to the workflows and systems our clients use every day.

‍Ready to get started? Book a free strategy session with our AI experts today.