Maximizing AI ROI: Lessons from the top 10%

Why do only a sliver of businesses—5-10%, according to Laks Srinivasan—manage to extract meaningful value from AI investment, while the vast majority see their AI pilots never take off (or, worse, crash and burn)?

Laks Srinivasan , co-founder of the Return on AI Institute, and bestselling author, professor, and AI expert Tom Davenport set out to solve that problem when they launched their AI advisory firm back in 2019. Today, they help enterprise companies convert their AI pilot projects into profitable realities.

In our most recent story for The Works , Srinivasan explained why ROI success relies much more on the human factors—teams, talent, and culture—in play, not AI.

“It’s not about how much data you have or how big a model you build,” Srinivasan says. “It’s about human behavior. How do you change the company, the way they think, the way they behave? That’s how to leverage AI for meaningful value.”

What does that mean in practical terms? Check out the article on The Works for full details, but here are some of the tactics and principles that have emerged from the institute’s top case studies:

• Mobilize your in-house talent: Winning companies build internal AI capabilities rather than relying solely on external consultants. They ensure that their teams are not just familiar with AI but can wield it effectively to solve business problems.
• Assess your AI readiness: The institute’s approach starts with assessing a company’s AI readiness. This involves examining strategic alignment, infrastructure, and the presence of a supportive leadership culture.
• Boost organizational AI knowledge: They offer a 12- to 18-month program featuring AI primers, workshops, and coaching to ensure that AI knowledge and practices stick within the organization.
• Focus first (not last) on outcomes: Too many companies let AI solutions chase problems. Instead, successful AI strategies begin with clearly defined business problems that AI can solve.
• Follow dual-track deployment:

1. Tactical: Use AI to improve existing processes for cost savings and efficiency.
2. Strategic: Adopt a disruptive mindset, exploring new business models and innovative solutions.

Srinivasan’s core success principle is simple but too often overlooked: “Measuring meaningful value has more to do with culture than it does with AI.”

Read the full story on The Works.

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