AI investment is moving into a more practical phase. While major funding continues to flow toward foundation models, computing, and infrastructure, investors are also backing companies applying AI to specific problems that businesses already understand.
The shift reflects a simple question: can AI create measurable commercial value? Across ecommerce, hospitality, and automotive retail, a growing group of companies is using the technology to improve customer experiences, streamline operations, and recover revenue that might otherwise be missed.
Bringing AI Closer to Ecommerce Revenue
Rather than treating AI as another isolated software feature, the company is developing an AI platform built for Shopify merchants, covering the customer journey from product discovery and sales to pos t-purchase support.
In May 2026, Rep AI raised $6.2 million in strategic follow-on funding, bringing its total funding to $14.4 million. The round was led by Silicon Road Ventures, with participation from Osage Venture Partners, Flashpoint Venture Capital, and strategic investor Zendesk, marking Zendesk’s first investment in an Israeli company.
The company’s approach reflects how ecommerce businesses are increasingly thinking about AI. Shoppers interact with brands through multiple touchpoints, but businesses ultimately need those interactions to contribute to stronger customer relationships and revenue. Rep AI CEO Yoav Oz captures that shift by saying, “Brands don’t need another chatbot bolted onto their store – they need an AI system that actually drives revenue, end to end. That’s what we built with Rep AI. Our goal is to help brands turn more conversations into customers at scale.”
The round reflects growing interest in AI applications that sit close to the commercial side of a business.
Turning Hospitality Data Into Better Decisions
The opportunity looks different in hospitality, where operational efficiency can have a direct effect on margins. Restaurants and quick-service chains constantly make decisions around inventory, ordering, forecasting, preparation, and store performance.
Edify, founded by hospitality operator Ed Barry, is applying AI to that challenge. The company has developed an AI-powered operations platform that connects inventory management, demand forecasting, and back-office functions, helping hospitality companies make better use of their operational data.
In June 2026, Edify raised £3 million in funding, including a £2.5 million investment from Calculus Capital. The funding supports the company’s expansion as hospitality operators look for ways to improve efficiency while managing costs and staffing pressures.
For Ed Barry, CEO of Edify, the value of AI comes from making hospitality operations work better without adding unnecessary complexity. “We’re not bolting AI onto old software. We’re building a live intelligence system around the way hospitality actually works, connecting the floor and HQ so GMs can lead better, stores can perform stronger, and businesses can grow smarter,” he says.
The value here is not simply adding another AI tool. It is about making existing information more useful and reducing the manual work involved in everyday operational decisions.
Using AI to Recover Missed Automotive Revenue
Automotive retail presents another version of the same challenge. Dealerships generate a steady stream of sales and service opportunities, but busy teams may not always have the time to follow up consistently with every customer.
Lokam.ai has developed a voice-first AI platform for dealerships that automates customer communication across sales and service.
The company raised $350,000 in pre-seed funding, led by customer World Auto Group after seeing the platform’s results firsthand. The funding is supporting the company’s expansion as it works to help dealerships improve sales conversion and retain service revenue.
The problem behind the technology is straightforward. Lokam CEO Muhammed Saleeq points to the gap between generating demand and having the resources to follow through, noting that “This platform was built to solve a simple but costly gap: dealerships generate demand but often don’t have the bandwidth to consistently convert and retain it.”
The approach highlights another practical use of AI: making better use of demand a business already has rather than relying entirely on new customer acquisition.
Where AI Investment Is Heading
The industries are different, but the funding behind these companies reflects a common investor interest. AI is increasingly being applied to specific commercial problems where its impact can be connected to revenue, efficiency, customer retention, or operational performance.
This does not mean investment in foundational AI is disappearing. Instead, application-focused companies are creating another layer of opportunity by taking increasingly capable technology into industries with clear, measurable needs.
As AI becomes more accessible, simply using the technology may no longer be enough to create an advantage. The stronger opportunity may belong to companies that understand where businesses lose time, money, or customers and build AI specifically around those gaps.
Recent funding activity points in that direction. The next wave of AI-driven business innovation may be defined not by how impressive the technology sounds, but by how effectively it solves problems that businesses can measure.
