It’s 2026 and AI chatter is everywhere. The technology’s potential to change the way we work and the world we live is a topic of celebration, debate, and even ire. AI conversations are sometimes sensationalist, often idealist, and regularly energizing – especially to people working in companies where efficiency is easy to strive for but difficult to achieve. Still, a lot of what’s happening with AI on an organizational level is just that: Talk. 

Why? A lot of companies that want to transform their workflows with AI dream about the end state, but don’t know how to find the starting point.  

Ask most technology leaders if their organization is ready for AI, and you’ll hear either an enthusiastic yes that dissolves into vague pilots and proofs of concept that don’t scale, or a frustrated no followed by a long list of reasons why the timing isn’t right yet. 

Still, some companies are doing it right – and “right” isn’t always exciting at first. In fact, it can feel downright tedious.  

At GM Financial, for example, Larry Bennett and his Process Excellence team have spent years doing something that rarely gets celebrated at technology conferences: Systematically documenting how work actually happens across the organization.  

Process by process and department by department, Bennett and team built a repository of priceless institutional knowledge that most organizations carry only in the heads of their longest-tenured employees. 

As a result, GM Financial is now positioned to do something genuinely powerful with AI. 

The bottlenecks blocking AI readiness 

Here are three things we at Nintex know to be true: 

1. AI agents need to understand your workflows to improve them.  
2. Automation tools need defined processes to automate.  
3. Compliance systems need documented controls to audit.  

But if you’re trying to shoehorn AI capabilities into processes that live in email threads, meeting transcripts, or the institutional knowledge of people who’ve been around long enough to just know how things work, you’re going to struggle.  

How GM Financial developed their automation foundation 

GM Financial’s approach was deliberate, patient, and focused on the work that was already being done. Bennett’s team didn’t chase quick wins or deploy automation everywhere at once. They focused on capturing and organizing the enterprise’s institutional knowledge first – creating documented, accessible, connected process maps that anyone in the organization could reference. 

“You have to know what is happening behind the scenes to be able to use anything effectively. You have to start with the foundation and then build and grow upon that.” 

— Larry Bennett, Process Excellence Manager, GM Financial 

That foundation-building phase was slow, and early adoption was gradual. But as the repository grew, teams that had previously operated in silos began to see how their processes connected to others:   

• Leadership could step back and look across six, seven, or eight linked processes and spot optimization opportunities that were invisible when each process was isolated.  
• Audit and compliance teams could map controls to the documented steps.  
• IT teams had something real, documented process flows to automate. 

The AI readiness payoff 

As if that visibility and control wasn’t enough, Bennett’s patient foundation-building is still paying off as GM financial looks to the future. 

The organization is now preparing to roll out Nintex Process Capture – an AI-powered capability that can dramatically accelerate the creation of process documentation.  

The irony isn’t lost on them: Those years spent slowly, manually building the repository are now enabling AI to help grow it faster.  

And that work can also serve as the foundation for even greater efficiency as Bennett and his team keep their eyes on what’s next, like connecting their process repository to the organization’s enterprise AI assistant, Copilot, via MCP server integration. The vision is a future where any employee can query the organization’s institutional knowledge directly – asking how a process works, what the approval steps are, who is responsible for what – and get an accurate, governed answer drawn from a reliable source of truth. 

“Being able to link in our enterprise Copilot to [Nintex Process Capture] and be able to access it for those queries that any end user may be asking about a certain process or how something is done is just going to continue to show how valuable this enterprise repository actually is.” 

— Larry Bennett, GM Financial 

What your organization can learn from GM Financial 

The lesson from GM Financial isn’t that you need to spend years documenting processes before you can touch AI. It’s that the organizations seeing real, scalable results from AI and automation aren’t the ones who moved fastest, but the ones who gave the technologies a solid foundation to build on. 

If your pilots keep stalling, your implementations don’t quite fit your workflows, or your compliance team keeps surfacing gaps in your documented controls, the bottleneck probably isn’t the technology but the foundation. 

Foundation first. Everything else follows. 

Nintex was honored to have Larry Bennett, Process Excellence Manager at GM Financial, participate in the Customer Panel as part of NintexConnect 2026. Hear more about how GM Financial is capitalizing on Nintex software by watching the customer panel in its entirety on demand.