3 Proven Strategies: How Leaders Turn GenAI Investments into ROI | Anna E. Molosky

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The “95% of GenAI Pilots Fail” Headline Confuses Signal for Noise

Reaching the top of the AI game takes commitment, vision, and code. © 2025 Anna E. Molosky. All rights reserved.
Reaching the top of the AI game takes commitment, vision, and code. © 2025 Anna E. Molosky. All rights reserved.

Three Strategies: Transform GenAI Investments Into Positive ROI

1️⃣ REALLOCATE EARLY AI SPEND TO BACK-OFFICE AUTOMATION

Executives allocate, on average, 50% of their GenAI budgets to Sales and marketing, according to the MIT The Gen AI Divide 2025 study¹. However, back-office process automation yields the clearest near-term ROI. Target process-specific automations and integrate robust AI solutions — not all of which require GenAI — with existing systems to reduce spend and minimize business process outsourcing.

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CIO Magazine² reported that AT&T saved 16.9 million minutes of manual effort per year, recognized “hundreds of millions of dollars in annualized value”, and delivered 20x ROI by scaling an enterprise-wide AI automation program across Finance and Operations.

2️⃣ LEVERAGE EMPLOYEES’ APPETITE FOR AI EFFICIENCY

A thriving “shadow AI economy” exists within enterprises.

90% of employees surveyed use personal AI subscriptions — such as OpenAI’s ChatGPT or Anthropic’s Claude — to automate significant portions of their daily work. However, only 40% of companies surveyed distribute LLM subscriptions to employees.

For AI success at scale, determine which tasks employees already automate, prioritize based on the value added before procuring (or building) new AI tools, and then embed the highest-value workflows into robust, customizable, enterprise-grade tools.

3️⃣ SET REALISTIC TIMELINES FOR ENTERPRISE AI PROJECTS

Major technology deployments within multinational organizations typically span 1 to 3 years, depending on the scope and depth of integration. The 

MIT Media Lab

 study’s 6-month observation window is insufficient to project long-term AI ROI for enterprise-wide deployments. Recalibrate and set organization-wide expectations for the speed of enterprise deployment.

Reframe the “95% failure³” statistic as a maturity signal for the 5% that have achieved positive AI ROI, not a stop sign for the 95% yet to realize AI ROI.

To maximize enterprise P&L impact and AI ROI, shift early-stage AI spend to back-office automations, analyze shadow-AI usage to identify high-value use cases, and set realistic expectations for enterprise deployment velocity.

References

Challapally, Aditya, et al. The Gen AI Divide: State of AI in Business 2025. Massachusetts Institute of Technology Media Lab, Project NANDA, July 2025.

Thor Olavsrud

. “AT&T Embraces Intelligent Automation at Scale.” CIO Magazine, December 9, 2022.

Failed AI investments, as defined by the MIT study and confirmed by 

The New Yorker

, are projects that were not deployed beyond the pilot stage and/or those without measurable return or P&L impact within six months.

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