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Generating ROI with AI

Building six AI capabilities drives world-class results from AI investments.

Generative AI has taken the business world by storm, with large language models (LLMs)—including OpenAI’s ChatGPT—splashed across the news. And executives aren’t immune to the hype. AI is becoming an ever-larger component of IT budgets, with worldwide spending on AI-centric systems expected to hit $154 billion this year—up 27% over 2022.

But will enterprises spend these resources wisely? Our research says yes—if organizations take a disciplined approach.

Can the ROI of AI match the hype?

To come to this conclusion, we surveyed 2,500 global executives in 34 business and technology roles across 16 countries from all major regions. We asked them to deconstruct how their companies are investing in AI today, what real-world ROI is being produced, and which elements are required to boost effectiveness.

Strike gold with the right approach

Our findings reveal that few AI projects deliver the financial value shareholders expect. In fact, average ROI on enterprise-wide initiatives is just 5.9%‚—well below the typical 10% cost of capital.

Yet, there are distinct improvements as you move along the AI maturity continuum—with best-in-class companies reaping an enviable 13% ROI. As organizations figure out where and how to deploy AI, bold bets translate into bigger and bigger gains.

Best-in-class companies reap a 13% ROI on AI projects—more than twice the average ROI of 5.9%.

What sets these world-class performers apart? And how can leaders across sectors emulate their success? Download this report to learn:
 

  • Why ad hoc AI projects deliver less value than strategic programs
  • The impact of trusted data and the virtuous cycle of AI-data symbiosis
  • Six key capabilities that define and enable top-tier organizations.
     

Becoming best-in-class: Companies that see the highest ROI from AI have matured 6 key capabilities—with trust at the core.

Six key capabilities for high AI ROI: Vision and strategy, AI operating model, AI engineering and operations, data and technology, talent and skills, and culture and adoption


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Meet the authors

Maryam Ashoori

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, Director, Product Management, Emerging Technologies Software, IBM


Brian Goehring

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, Global Research Lead, AI, IBM Institute for Business Value


Timothy Humphrey

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, Chief Analytics Officer, IBM


Mahmoud Naghshineh

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, Vice President of AI Impact and Partnerships, IBM Research


Cathy Rodenbeck Reese

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, Americas Data & Technology Transformation Leader and Senior Partner, IBM Consulting

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    Originally published 09 May 2023