For the past few years, the enterprise AI race has focused heavily on one question: Which company has the best AI model?
Companies have competed to build models that are smarter, faster and more capable. But as AI becomes more common in the workplace, another question is becoming just as important: How do companies actually put AI to work?
That is where partnerships come in.
For businesses, choosing an AI model is only the first step. The bigger challenge is connecting that technology to the systems, software and processes they already use.
A company might have access to a powerful AI model, but that does not automatically mean it knows how to use it effectively. Businesses still need to figure out where AI can make a difference, how it should connect with their existing technology, how employees will use it and how to keep the technology secure.
This is creating a growing role for partnerships between AI companies, enterprise software companies and technology providers.
The relationship between Anthropic and ServiceNow is one example. ServiceNow has partnered with Anthropic to bring Claude into its enterprise platform, including tools designed to help companies build AI-powered applications and automate work.
The partnership shows how AI companies can reach businesses through technology platforms that are already part of their daily operations.
This could become one of the most important ways AI spreads through the business world.
Think about it this way. An AI model can be extremely powerful, but most businesses do not want to start from scratch. They want AI to work with the tools they already use.
A bank may want AI to help employees handle customer requests. A software company may want AI to help developers write and test code. A large company may want AI agents to handle routine IT or human resources tasks.
In each case, the AI model is only one part of the solution.
The technology also needs to connect to company data and existing software. Employees need to know how to use it. Leaders need to understand whether it is actually saving time or money. Companies also need rules around security, privacy and how AI makes decisions.
That is why partnerships could become so important to the next stage of enterprise AI.
Jason Rosenfeld, Chief Growth & Alliances Officer at NewRocket, puts the idea simply: “Partnerships don’t produce revenue on their own. What you build behind them does.”
That distinction is important. A partnership announcement may generate attention, but the real value comes from what happens after the announcement.
Companies need to build products, services, integrations and processes around those relationships. They need to make it easier for customers to adopt new technology and turn it into something that solves an actual business problem.
In other words, the partnership is the starting point, not the finish line.
We have seen something similar happen with cloud computing. Cloud technology became much more useful to businesses as an entire ecosystem of software companies, consultants and technology partners developed around it.
AI could follow a similar path.
The companies building AI models provide the underlying technology. Enterprise software companies provide the systems businesses already rely on. Cloud companies provide the infrastructure. Partners help businesses connect everything together and turn the technology into something employees can actually use.
This also creates a growing opportunity for companies that specialize in AI transformation.
These companies can help businesses move beyond experimenting with AI and start using it in real business processes.
That distinction is becoming increasingly important.
Many businesses have already tried generative AI. Employees have used chatbots, companies have tested AI assistants and executives have launched pilot programs.
The harder part is turning those experiments into systems that work reliably across an entire organization.
A company might successfully test an AI tool with 20 employees. Getting that same technology to work across thousands of employees is a much bigger challenge.
There may be concerns about company data, security, employee training and how the AI connects with existing systems. There may also be questions about who is responsible when something goes wrong.
This is where an experienced technology partner can become valuable.
Instead of simply giving a company access to an AI model, a partner can help identify where AI should be used and how it can fit into the company’s existing operations.
That may be where the next wave of enterprise AI growth comes from.
Businesses will increasingly want to see results, not just demonstrations.
Can AI save employees time? Can it reduce costs? Can it improve customer service? Can it help employees make better decisions? Can it automate repetitive work?
Those questions are ultimately more important to a business than how impressive an AI model looks on a benchmark.
There is also a reason companies may want access to more than one AI model.
Different models may be better suited to different tasks. Businesses may not want to depend completely on one provider. They may want the flexibility to use different AI technologies while keeping their data, security and business processes under control.
That makes partnerships and integration even more important.
The companies that can connect different AI models to the systems businesses already use could become just as important as the companies building the models themselves.
There is another important factor: trust.
Businesses are more cautious about AI than individual consumers. A company cannot simply introduce a new technology and hope employees use it correctly. It needs to understand how the technology works, what information it can access and what safeguards are in place.
Partnerships can help businesses manage that risk.
When an AI company works with an established enterprise technology company and experienced implementation partners, businesses may have more confidence that the technology can be introduced in a controlled way.
This could become especially important as AI moves from simple chatbots toward AI agents that can take actions on behalf of employees.
The more responsibility AI systems have, the more important integration, security and oversight become.
The future of enterprise AI may therefore be less about one company winning the race to build the best model and more about which companies can build the best ecosystem around AI.
The strongest AI technology still matters. But technology alone does not transform a business.
Businesses need people who understand their industry, their technology and their workflows. They need partners who can help connect AI to the systems they already have and turn new technology into something useful.
That could change how we think about competition in AI.
The biggest question for businesses may no longer be, “Which AI model is the best?”
Instead, it may be, “Who can help us make AI actually work for our business?”
The answer to that question could determine where the next stage of enterprise AI growth comes from.
As AI becomes more powerful and more widely available, the technology itself may become easier to access. The real advantage could come from knowing what to do with it.
And as Rosenfeld’s observation suggests, the partnerships themselves may matter less than what companies build behind them.