Gary Drenik, Contributor
2025-09-02 10:00:00
www.forbes.com
AI ROI
Getty Images – Anton Petrus
The AI return on investment debate is largely over. Companies are no longer asking if it delivers value; they’re asking where it delivers the most and how to scale those gains across the business.
Cross-industry research from TAG Infosphere, supported by WitnessAI, examined 20 sectors and found a universal truth: everyone is projected to see a positive return from AI. The biggest wins are showing up in functions with rich, structured data and repeatable processes. By contrast, areas that rely heavily on human judgment and nuance are progressing more slowly.
Where AI Is Paying Off Fastest
The TAG Analyst Report, Ranking Industries by Their Expected Benefit from Artificial Intelligence (AI) Usage, listed data analysis as the top ROI-positive function, followed by manufacturing and customer service. All three share the same advantage: clear goals, plenty of data to train models, and outputs that can be measured in hard numbers.
- Data Analysis – Drives productivity gains, trims staffing needs over time, and reduces IT costs by replacing less efficient platforms.
- Manufacturing – Predictive maintenance, robotics, and automation that improve output and cut downtime.
- Customer Service – Chatbots, personalization, and smart routing that boost satisfaction while lowering labor requirements.
Lower-ranking functions, such as HR, still yield returns, just not as quickly. That’s less about AI’s capability and more about the nature of the work, which depends on empathy, negotiation, and situational judgment.
Why These Areas Lead
AI shines where inputs are consistent, data is plentiful, and the work can be done at scale. In data analysis, algorithms process massive datasets more efficiently and accurately than humans. In manufacturing, predictive models identify equipment issues before they escalate into costly failures. When it comes to customer service, human agents are freed up for more complex interactions with AI handling common requests instantly.
That doesn’t mean slower-moving industries should sit back and wait. The most effective approach is to invest first in areas that can produce measurable cost savings or new revenue within months, then expand into other functions as the organization builds confidence and skills.
How Leaders Are Using AI Today
According to a recent Prosper Insights & Analytics Survey, 50.2% of executives and 43.6% of business owners already use AI in their daily work
Prosper – Heard of Generative AI
Prosper Insights & Analytics
Top applications:
- Research and summarization
- Writing assistance
- Content Creation
Prosper – What You Use Generative AI For
Prosper Insights & Analytics
These activities line up neatly with high-ROI functions; they’re also relatively low-risk starting points.
The performance picture is more complex. IBM’s 2025 CEO Study found that only 25% of AI initiatives hit their expected ROI in the past three years, and just 16% have scaled enterprise wide. Yet confidence remains high: 85% of CEOs expect efficiency-focused AI investments to deliver positive ROI by 2027, and 77% expect the same for AI growth initiatives.
The Visibility Gap
Even leaders in organizations that have adopted AI lack insight into its actual application. Rick Caccia, CEO of WitnessAI, has seen the disconnect firsthand.
“Executives might think that blocking AI usage is a fine strategy for now, Caccia said, “but employees want to use these tools they’ve been reading about for years. In practice, employees are using anywhere from 2 to 5 times more AI apps than company leaders expect. That makes it impossible to measure what’s really driving value, and it means some of the biggest productivity gains and the risks never show up in official reports.”
Caccia points out that most risks aren’t deliberate. They come from people trying to work better and faster, but in doing so, they expose sensitive data or IP. His advice: enable AI use with the right safety rails instead of banning it outright.
AI as the Main Event
Some executives still treat AI as an add-on to existing tools rather than a core driver of business. Gil Spencer, CTO of WitnessAI, thinks that the mindset is already obsolete.
“The reality is that AI is the main attraction,” Spencer stated. “Pretty soon, you’re just going to tell your AI to research a topic and draft a document or presentation. Business models, development methods, and daily work have undergone fundamental shifts. Organizations that place AI at the center of their workflows will see returns that compound over time. Treat it as a peripheral tool, and you’ll miss out on the exponential ROI curve.”
That shift in thinking is key to unlocking the kind of compounding returns Spencer describes. AI woven into core processes has a multiplying effect; kept at the edges, its impact is incremental at best.
From Proof to Scale
Every sector in the TAG Infosphere and WitnessAI analysis is positioned to benefit from AI. The real differentiator will be how quickly leaders transition from proof of concept to scaled adoption in the areas that matter most. This involves selecting the right starting points, tracking the relevant metrics, and incorporating safety and governance into the plan from the outset.
The ROI conversation has moved on. Now it’s about ensuring the return is not just real, but also repeatable.
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