We’re at the point where every software developer should be on their journey to adopt AI-native workflows. This is a drastic change. It requires coordination and understanding of impact to the organization at each level. Unfortunately, the leadership needed to drive this change is still missing in nearly every enterprise organization. Most technology leaders are still looking at AI like they have any previous technology or process change over the past decade. In many cases, the brief stints of transformation have either failed, or have been incrementally effective at best. Until now, leaders have been able to set their own pace for organizational change and create metrics that define what success looks like for themselves.
So here we are again. Many enterprises have already rushed to buy the latest AI-powered development tools (and there are many), hoping for an instant productivity boost. But as we’ve all seen before, just purchasing a tool or new platform doesn't move the needle. In fact, without the support and alignment at the team and broader organizational level, dropping a fancy new AI tool into your developers' laps, can even set the organization back.
Why? Because tools don’t drive change. And the move to a modern, AI-native enterprise requires much more than access to the latest LLMs. Don’t get me wrong, the latest tools are amazing. They can certainly ignite interest and get teams excited, but if we’re looking for productivity or efficiency improvements, those aren’t found at an individual developer’s workflow. In every enterprise software development team, it’s the team who’s responsible for delivering value. The productivity gains will only come when you have a strategy to integrate these tools effectively into your teams’ day-to-day work.
Driving intentional integration and enablement support for AI-native tools or platforms is critical if we expect to see the massive improvements in software development efficiency everyone is hoping for.
Yes, you need a new tool. But this time you need A LOT more.
The difference today is that the latest tools could actually be gateways to a completely new way of working for the entire organization. Unfortunately, even though these tools may come with great potential, they won’t drive change on their own. New AI tooling will promise big productivity boosts (because that’s how product marketing works!), but enterprises see limited impact from these tools when they lack an enablement strategy that follows through. We've seen companies buy thousands of Copilot licenses expecting a jump in productivity. But just six months later, they wonder why nothing has changed.
The truth is, handing developers any tool and expecting improvement is unrealistic. Bringing in AI tools is just opening a door. Without clear guidance, alignment on current best practices (which are changing rapidly) even the best tools can cause friction, confusion, or become “shelfware”.
Technology is only as transformative as the organization's ability to use it effectively.
As we’ve said before, "What will separate organizations that thrive with AI from those left behind is enablement. It’s not enough to buy licenses for Copilot or install Cursor and call it a day. Teams need a holistic strategy and support...". In other words, success with any new tech hinges on training and supporting your teams.
For example, our team has led hundreds of GitHub Copilot workshops and have seen first hand how enterprise teams engaged with these new technologies. Because of the frequently siloed nature of dev teams, they struggled to maintain consistency with even relatively small updates to their SDLC. And as we began evaluating more capable agentic tools, we recognized that if an organization struggled with simple code completion with Copilot, they had no path to implement anything requiring significant change.
So that’s what we focused on. Our team collaborated on successes (and challenges) with workflow changes for 2-3 months prior to seeing them stabilize. Once we had the right approach, having a great tool did help us accelerate. Here, Windsurf elevated itself as a tool that both enabled the AI-native workflows we were adopting and was also truly enterprise-ready. When real-world results came back from our client engagements, we doubled down to make sure we could scale the success.
At the enterprise level, you need to embed new workflows, establish smart governance, and get everyone on the same page about how these new capabilities will drastically impact their day-to-day work. Skipping this step has meant that developers are using AI capabilities inconsistently or even bypassing established security guidance with “shadow AI”, which causes more harm than good. Establishing change management, hands-on coaching, AI communities of practice, and ongoing enablement programs ensure that instead of ad-hoc or fractured workflows, you see consistent, sustainable change across the organization.
The bottom line is that just buying a tool won't automatically yield positive ROI. ROI from AI tooling that shows up as improved productivity or efficiency requires organizational support to drive and scale integration and adoption. And this time, it’s a change that could mean amplifying benefits exponentially.
So how do you navigate this journey? What should this look like from adopting a new tool to ensuring everyone in the organization is getting the benefits they expect to see from AI?
To dig in a bit more on our journey and how we see this taking shape for enterprises, check out our upcoming posts on why we’re “All-In” on AI-native enablement with Windsurf and The Vibe Coding Revolution How Agentic Platforms are Changing the SDLC.
