CIOs are grappling with how to leverage AI, but most are asking the wrong question. It’s not about an “AI strategy.” It’s about a business strategy powered by AI.

At Samsara, when we focused AI on clear business problems, we cut support chat volume by 59% with virtual agents, our IT help assistant auto-resolved 27% of tickets during the pilot, and engineers accepted about 40% of suggested code from AI code-assist, freeing teams to ship faster and tackle harder work.

My takeaway is that if you treat AI as a separate initiative, you’ll chase tools. If you treat it as leverage on a business KPI, you’ll create impact.

The VC Mindset: Investing in AI

My philosophy on AI investment mirrors how a Venture Capital firm manages its portfolio. While every investment should strive for success, organizations must adopt a portfolio mindset: expecting only 10% of AI pilots to yield a high return. This crucial insight is what drives a VC firm, and what should drive your AI funnel.

This means maintaining an active, well-fed funnel of AI investments. Working diligently to narrow this funnel through rapid pilots and experimentation allows businesses to move fast and fail quickly on small, contained experiments to find the few truly transformative applications.

This approach is crucial given the sheer volume of AI solutions available. The typical vendor evaluation process might involve vetting three or four key solutions. In the AI space, that number can balloon into the thousands. Applying a VC mindset allows us to efficiently triage and prioritize, focusing our resources where the potential business impact is highest.

Scaling AI Through Change Management

Investment is only half the battle. The most sophisticated AI tool is worthless if employees don’t use it effectively. Success demands a robust AI change management program that builds new organizational muscles.

1. Driving Adoption: A Top-Down and Bottom-Up Engine

True organizational change requires synchronized effort from the C-suite to the front lines. This is the top-down and bottom-up mandate for AI adoption.

• Top-Down Commitment: This begins with the CEO and C-suite making AI a core business priority. At Samsara, two of our four company priorities are explicitly AI-related—one focused on internal efficiency, and the other on product innovation. This executive mandate, championed by leaders like our CEO and reinforced through my partnership with our CFO, ensures AI initiatives are treated as strategic imperatives, not discretionary projects.
• Bottom-Up Application: While CIO organizations are natural early adopters, the people best positioned to apply AI are those who live with the business problems daily—in supply chain, finance, sales, and operations. These colleagues have a nuanced, first-hand understanding of where AI tools can create the most value. And they can bridge this gap by empowering those teams to identify and lead implementation.

2. Scale Literacy with an AI Champions Network

To connect the top-level vision with bottom-up execution, businesses must actively cultivate AI literacy. At Samsara, we’ve implemented a two-pronged approach to ensuring that AI skills and uses are being scaled across our business.

• AI Champions Network: Our AI Champions are a bridge to realizing our AI ambitions. We identify individuals across every function with a strong understanding of technology—the natural thought leaders—and designate them as AI Champions. We give them concrete roadmaps for how to use AI in their specific function, making them evangelists who drive enablement and comfort within their teams.
• General Education: We use channels like our daily Slack digest to deliver short, 5-minute to 10-minute lessons to provide general AI education and demystify the technology for all employees.

3. Frame AI as Partnership, Not Replacement

Any company’s ethos on AI should be clear: AI won’t replace people who embrace it. They should position these tools to their staff as partners that will better their teams and outputs, freeing them up for higher-value work.

As I alluded to above, for our R&D and BizTech teams, we’ve implemented AI Code Generator tools. Our teams accept, on average, over 40% of the prebuilt code suggested, accelerating development cycles and allowing them to focus on complex, innovative challenges.

On the service side, our use of AI chat agents has driven a 59% reduction in chat ticket volume in customer support, allowing staff to focus on complex issues. Similarly, our internal Generative AI-powered help assistant for the IT Help Desk resolved 27% of tickets with no human touch during the pilot, freeing up IT staff for strategic work.

The CIO’s Evolving Role

In this new era, the CIO’s job is to stay intensely agile. They must mirror the company’s need for external innovation with a commensurate drive for internal modernization.

The path to AI success is not paved with technology alone, but with strategic discipline and cultural transformation. The new CIO mandate is simple: Stay intensely agile. Mirror the company’s need for external innovation with an equivalent drive for internal modernization. The path to AI success is not paved with technology alone, but with strategic discipline and cultural transformation. Stop chasing the latest platform and start asking: What is the core business problem we need to solve? Anchor your investments in quantifiable business value, embrace a venture-style portfolio approach to experimentation, and aggressively equip your employees to be partners of AI, not its victims. This shift from technology buyer to strategic portfolio manager is the key to enduring competitive advantage.