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Artificial intelligence is moving from experimentation into everyday business operations. Enterprises are investing heavily in AI, but many are now facing a more practical question: how can they turn these technologies into measurable business results?
NewRocket’s work with Anthropic’s Claude is focused on that challenge. The company is helping enterprises identify where Claude can support real business needs, including customer service, sales, finance, human resources, operations and back-office processes.
Jason Rosenfeld, Chief Growth & Alliances Officer at NewRocket, is helping drive the company’s growth and partnership strategy as demand for enterprise AI continues to expand. His role highlights an important part of the market’s evolution: connecting AI technology with the business problems organizations need to solve.
NewRocket says it works with companies across financial services, telecommunications, technology, manufacturing and retail. These industries have different operating models, but many share similar challenges. Employees manage large amounts of information, complex workflows and repetitive tasks while businesses face growing pressure to improve efficiency and customer service.
The opportunity for AI goes beyond giving employees another productivity tool. Companies are increasingly looking at how AI can change the way work gets done.
Customer service teams, for example, could use AI to find information more quickly and respond to customers more efficiently. Finance teams could use it to assist with repetitive processes and information analysis. Sales organizations could use AI to support research and administrative work, while HR and operations teams could apply it to internal processes and knowledge management.
The potential benefits include saving employee time, reducing operational costs, improving service and allowing people to spend more time on higher-value work.
Turning those possibilities into results, however, requires more than access to an AI model. Enterprises also need to consider security, governance, employee adoption and how AI fits into existing processes.
NewRocket’s consultants and forward-deployed engineers are intended to help address those challenges. The company says its teams work directly with enterprise organizations to identify specific business problems and develop AI-enabled solutions. NewRocket says its approach can help companies move from identifying an opportunity to deploying a working solution in weeks.
Speed could become an important factor in the enterprise AI market. Businesses are under pressure to demonstrate returns from technology investments, while AI capabilities are developing rapidly. Companies that can move quickly from testing to practical applications may have an advantage over organizations that remain stuck in lengthy pilot programs.
The key measure, however, will be business impact.
An AI deployment is valuable only if it improves a process in a meaningful way. That could mean reducing the amount of time employees spend on repetitive work, improving customer response times, lowering costs or helping teams complete work more efficiently.
NewRocket’s focus on training and enablement also creates an opportunity for longer-term growth. The company says it helps employees become more familiar with Claude Code and Claude Cowork, giving organizations the skills to continue developing AI applications internally.
That approach could allow companies to expand beyond individual projects. An organization might begin by applying Claude to customer service and later identify opportunities in finance, sales, HR or operations. A successful project can provide both measurable results and a model for identifying additional applications.
NewRocket’s Claude squads are designed to support this expansion by bringing technical expertise together with knowledge of specific business functions and industries. This type of specialization could become increasingly important because AI adoption will not look the same across every organization.
A financial institution may focus on customer service, document processing and compliance-related workflows. A manufacturer may prioritize operations and supply chain processes. A retailer could focus on customer engagement and administrative work.
The technology may be similar, but the business challenges are different.
That creates a potential growth opportunity for NewRocket. Successful implementations can lead to additional projects within the same organization, while experience across industries can help identify new opportunities with other enterprises.
The broader enterprise AI market is also moving toward a more outcomes-focused approach. Early generative AI efforts were largely about experimentation and understanding what the technology could do. Businesses are now asking harder questions about return on investment, scalability and measurable results.
NewRocket’s partnership around Claude is positioned within that transition. The opportunity is not simply to introduce companies to AI, but to help them identify where it can make a practical difference and develop the capabilities to use it more broadly.
For Rosenfeld and NewRocket, growth will depend on demonstrating that this approach can produce results that enterprises can measure and build upon. For businesses, the opportunity is to move beyond isolated AI experiments and make the technology part of the everyday processes that matter most.
The next phase of enterprise AI may ultimately be less about the technology itself and more about how effectively organizations can put it to work. Companies that can connect AI capabilities to real business needs will be better positioned to turn investment in the technology into lasting operational value.
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