Unlocking the Value of AI: Five Strategies to Measure Success

The realm of artificial intelligence (AI) has taken center stage in today’s business landscape, promising transformative solutions that can reshape organizations. However, executive teams are grappling with one crucial question: How do I prove that investments in AI generate tangible returns? Insights from recent discussions among digital leaders at the Informatica World Tour in London unveil strategies that can help businesses navigate this challenging terrain.

Understand When to Start and Stop

The journey into AI isn’t a straightforward one. Gro Kamfjord, head of data at paint manufacturer Jotun, shares a pivotal lesson: leaders need to be well-informed enough to decide when to proceed with a project and when to pull back. She emphasizes the importance of starting with simpler initiatives. "You can either scale up the project when the time is right or withdraw if it isn’t yielding the anticipated return," advises Kamfjord.

For instance, by modernizing its data infrastructure and forming partnerships, Jotun facilitated faster AI preparations. This streamlined approach enables their teams to get key insights that guide decisions effectively.

Win Hearts and Minds

One of the most significant hurdles business leaders face is convincing the organization of AI’s potential benefits. Nick Millman, senior managing director at Accenture, underscores that measuring the complete value of AI can be intimidating. "CFOs are not easily swayed by generic ROI estimates," he points out.

To navigate this landscape, leaders should adopt a three-pronged strategy:

1. Use Recognizable Metrics: Tailor ROI calculations to metrics that resonate with business stakeholders. Some might prefer detailed spreadsheets, while others may focus on overall revenue impact.

2. Involve Business Stakeholders: It’s essential for business leaders to be part of the measurement process. If data teams are seen as the sole source of value, credibility may falter.

3. Engage the Finance Function: Collaborating with finance can yield better investment cases. A CFO vested in the ROI process will likely advocate for AI initiatives more passionately.

Foster Two-Way Discussions

Patience is essential when investing in foundational AI elements, according to Boris van der Saag of Rabobank. "Focus on the eventual benefits rather than immediate returns," he suggests. This mindset can facilitate meaningful conversations with senior management, who often desire quick results.

Van der Saag emphasizes the importance of establishing a two-way dialogue with stakeholders. Instead of merely presenting ROI, he advocates for an open exchange: "Ask how senior managers can adjust their decisions to leverage data opportunities." Such interactions encourage a more inclusive environment, enabling collective insights into AI’s potential.

Connect to Bigger Goals

Business leaders should refrain from limiting discussions around AI to narrow use cases. Farhin Khan, head of data and AI at AWS, encourages digital leaders to narrate AI outcomes in the language of business. "Articulate the impact on business goals that matter to stakeholders, such as reducing customer churn for a CMO," she advises.

Moreover, illustrate how AI initiatives align with broader business transformations. "When businesses aim for market expansion, link your AI use cases to this larger objective," she suggests. This storytelling approach can galvanize support for AI projects.

Track the Moving Parts

Successful AI ROI measurement hinges on collaboration among all project participants. Kenny Scott, a data governance consultant at EDF Power Solutions, emphasizes maintaining a clear framework of accountability. "Ask the right questions to ensure everyone is on the same page about their responsibilities," he cautions.

Scott illustrates the importance of a well-structured data infrastructure—comprising tools like Informatica, Snowflake, and Power BI—as the backbone for effective project management. Monitoring and documenting costs, expected outcomes, and milestones enable teams to steer projects without losing direction.

In summary, while measuring the return on AI investments can seem daunting, implementing these strategies may help spare organizations from the pitfalls many face. By fostering clear communication, aligning projects with organizational goals, and ensuring collaboration, businesses can unlock the full potential of their AI initiatives.