How Oshkosh Corp. turns AI hype into measured business value

At the heart of Oshkosh’s approach is a four-part AI strategy that brings structure and discipline to value creation.

First, Khare describes the importance of AI Scope. Rather than treating AI as a single technology, Oshkosh treats it as a portfolio combining ML, RPA bots, gen AI, off-the-shelf applications, and analytical models to automate tasks and improve decision-making. Second is AI Technologies. Leveraging scalable cloud platforms like Azure and Databricks, Oshkosh deliberately avoided building a massive data lake or data warehouse and instead made infrastructure scalable based on the value proposition, focusing on agility rather than size for its own sake.

The third pillar, AI Prioritization and Focus, is where value becomes most visible. Once a year, as part of the company’s strategic planning process, Oshkosh convenes joint workshops with business units and functions to identify the most impactful opportunities. Business leaders share their problems, IT brings the art of the possible, and together they size the potential value. Khare says if a business unit tells them solving a particular problem could deliver millions in benefit, they capture that upfront, deliver the solution, and then compare actual results to projections.

Finally, there’s Value Measurement. After a project is deployed, IT partners with the finance team to calculate how much of the business outcome can be attributed fairly to AI versus human decision-making. Khare stresses that AI is augmenting humans, not replacing them, and it’d be wrong to credit all the value to AI when people still do much of the heavy lifting.

Case in point: Boosting aftermarket sales

One powerful example comes from the strategic goal to grow aftermarket sales to 30% of revenue. To get there, they needed to rethink service part availability to achieve delivery within 24 hours without ballooning inventory costs.

Through their AI framework, Oshkosh analyzed demand patterns for parts, existing warehouse capacity, and customer proximity to determine exactly which parts to stock in which locations, optimizing availability and minimizing waste. The result was faster delivery, more satisfied customers, and measurable revenue lift. Khare says this is where AI shines, not by simply automating tasks but enabling smarter and faster decisions that move the needle on business performance.

Khare has made culture change and governance core to Oshkosh’s AI journey. In 2025 the company ran an eight-part AI literacy series that drew over 1,200 team members eager to understand how AI applies to their roles. On-demand digital training, for instance, supplements live sessions, making AI education available across the organization. According to Khare, ongoing AI education is critical to build trust and engagement.

The AI Enablement Council, including IT, legal, cybersecurity, and business leaders, also meets regularly to address risks, accelerate adoption, and prioritize investments. The team tracks model usage and accuracy as well, intervening when adoption lags. Khare explains that trust is a two-way street since they measure whether models are being used and how they’re performing, and have honest conversations when adoption isn’t where it should be. He adds that this level of engagement helps build lasting credibility with the business.

The 80/20 rule for AI value

As Khare looks to the future, he sees AI becoming seamlessly embedded into workflows, from ERP systems to day-to-day decision-making, rather than functioning as a separate tool. His advice for other CIOs is to focus on the 20% of initiatives that create 80% of the value, and stay laser-focused on business problems and opportunities. Khare cautions against getting caught up in the gen AI frenzy, urging peers to start with what matters most and let the technology follow.