Generating value from generative AI

Amid generative AI value discussions, we found AI investments drive market value and improve share price returns.

Brenna Sniderman

United States

Nitin Mittal

United States

Leaders in every industry are clamoring to adopt generative AI. Terms like ChatGPT and large language models have made it into the public lexicon and consciousness. Is this surprising? Not really. The fifth edition of Deloitte’s State of AI in the Enterprise reported 94% of business leaders believe AI is critical to their success strategy over the next five years.1 The generative AI market is expected to double every other year2 for the next 10 years; investments are soaring,3 and it is consumers who are largely driving adoption.4 The technology has, on the one hand, significantly expanded the scope of human creativity,5 and on the other, ignited deep philosophical debates concerning truth,6 consciousness, and humanity.7

As organizations try to crack the code on generating value with generative AI, our analysis offers insights into how AI investments have driven value to date and what their future potential could be.

Business transformation and value creation through generative AI

Generative AI can help organizations drive business transformation and create business value in five major ways: cost reduction, process efficiency, growth opportunities, accelerating products/services/innovation,8 and new discovery/insights.9 In essence, organizations using generative AI are better placed to optimize, preserve, and protect and create value, whether that is by increasing productivity across the value chain,10 institutionalizing knowledge, or contributing to research and development.

But as with any technology investment, leaders need to look past the technology to determine how investing in generative AI aligns with their overall strategy and their ability to affectively adopt and implement it. 

We analyzed 10 years of data from more than 4,600 companies and found strong evidence that successful business transformations combine three elements: strategy, technology, and a strong change capability.11 When organizations get that combination right, our analysis found there could be as much as US$1.25 trillion in market cap to be gained among Fortune 500 companies. Conversely, when they get it wrong, there’s as much as US$1.5 trillion in market cap at risk. The strongest value driver is when the technology investments are closely aligned to the enterprise strategy: Organizations that achieve this double their market cap increases versus the baseline approach.

The bottom line: Investing in a technology that’s not connected to your organization’s strategy will result in value loss, not gain.

AI has been following a similar growth trajectory to cloud—until now

Getting the most out of technology investments comes down to being intentional about aligning tech investments with your organization’s strategy to create the future you imagined. As we’ve seen in our research, it’s important to have a three-dimensional tech strategy that combines innovation with business-led and purposeful technology investments.12 Our data shows that, historically, cloud investments have successfully tapped into all three to drive successful enterprise-scale business transformations. Including cloud, AI, and cyber investments in their innovation strategies can help organizations achieve up to three times market cap increases compared with organizations taking a more standard tech modernization approach.13

Interestingly, a Deloitte and MKT MediaStats analysis14 (figure 1) shows that public-company news mentions related to AI are following a similar trendline to cloud. In 2021, attention on AI peaked and even surpassed cloud before dipping back down again—that is, until this year with the release of ChatGPT and Google Bard, which fueled the generative AI renaissance as these capabilities reach new levels of maturity and adoption. Using these news mentions as a baseline, we can also understand the impact on these same listed company’s share-price returns.

What’s more, the data in figure 1 shows organizations investing in AI outperform others in stock returns five, six, seven, and eight quarters after the investments. Our report also found that financial services organizations have yielded three-year returns that are six percentage points higher than market averages, and technology, media, and telecommunications companies have seen 12% higher three-year returns.15 Consistent with our findings from the digital transformation value research,16 this analysis also showed that when strategy and technology terms were aligned intentionally, organizations overperformed the three-year stock-return average.

AI investments are clearly on the rise. Generative AI alone has the potential to be even bigger than the cloud—with many calling it the next “iPhone moment”—impacting businesses and consumers alike in a way that will revolutionize how we live and interact.17 If you want to tap into the potential of generative AI, take a step back and consider your strategy. Ask where can generative AI help optimize, preserve and protect, and create value for your organization. As cloud’s adoption and value trajectory show, it’s when organizations innovate, lead with business imperatives, and invest strategically in the technology that they see returns. But as we’ve also seen from pivotal innovations like the iPhone—when there is a categorical shift in the way organizations experience technology—the potential is unlimited.

By

Brenna Sniderman

United States

Diana Kearns-Manolatos

United States

Nitin Mittal

United States

Endnotes

  1. Nitin Mittal, Irfan Saif, and Beena Ammanath, Fueling the AI transformation: Four key actions powering widespread value from AI, right now—Deloitte’s State of AI in the Enterprise, 5th edition report, Deloitte, October 2022. 

    View in Article
  2. Deloitte, The implications of generative AI for businesses: A new frontier in artificial intelligence, accessed October 2023. 

    View in Article
  3. Chris Arkenberg, Generative AI is already disrupting media and entertainment, Deloitte Insights, June 29, 2023. 

    View in Article
  4. Phil Fersht, “Gen AI is meaningless, unless it is toasted,” Horses for Sources, August 6, 2023. 

    View in Article
  5. Tojin T. Eapen, Daniel J. Finkenstadt, Josh Folk, and Lokesh Venkataswamy, “How generative AI can augment human creativity,” Harvard Business Review, July–August 2023. 

    View in Article
  6. Dave Wright, “Can we ever trust generative AI?,” Workflow, July 26, 2023. 

    View in Article
  7. Duleesha Kulasooriya, Michelle Tan, and Michelle Khoo, Being human in a digital world: Questions to guide the internet’s evolution, Deloitte Insights, June 26, 2023.

    View in Article
  8. Karan Girotra, Lennart Meincke, Christian Terwiesch, and Karl T Ulrich, “Ideas are dimes a dozen: Large language models for idea generation in innovation,” Mack Institute for Technological Innovation Working paper, July 10, 2023. 

    View in Article
  9. Deloitte, Top applications of AI in every major industry: Considerations for trustworthy AI and risk management, accessed October 2023. 

    View in Article
  10. James Glover and Robyn Peters, “Why should CFOs care about generative AI?,” Wall Street Journal, August 2, 2023. 

    View in Article
  11. Tim Smith, Tim Bottke, Gregory Dost, and Diana Kearns-Manolatos, Unleashing value from digital transformation: Paths and pitfalls,” January 31, 2023. 

    View in Article
  12. Deloitte, Closing the cloud strategy, technology, and innovation gap—Deloitte US Future of Cloud Survey report, accessed October 2023.

    View in Article
  13. Smith, Bottke, Dost, and Kearns-Manolatos, Unleashing value from digital transformation; David Linthicum, Garima Dhasmana, Ranjit Bawa, Diana Kearns-Manolatos, and Ahmed Alibage, “Driving enterprise value with a three-dimensional tech strategy, enabled by cloud,” accessed October 2023.

    View in Article
  14. This Deloitte/MKT MediaStats analysis includes aggregate news media data from 2015 to 2022 for over 700 US organizations. Data was analyzed using stock price returns and regression modeling to determine stock return over/under performance for the next 12 quarters. 

    View in Article
  15. Linthicum, Dhasmana, Bawa, Kearns-Manolatos, and Alibage, “Driving enterprise value with a three-dimensional tech strategy, enabled by cloud.” 

    View in Article
  16. Smith, Bottke, Dost, and Kearns-Manolatos, Unleashing value from digital transformation.

    View in Article
  17. Glover and Peters, “Why should CFOs care about generative AI?”; Prarthana Prakash, “Artificial intelligence like ChatGPT is on the brink of an ‘iPhone moment’ thanks to ‘warp-speed’ development, Bank of America says,” Fortune, March 2, 2023.

    View in Article

Acknowledgments

The authors would like to thank Dr. Ronnie Sadka, senior associate dean for faculty, chairperson and professor of finance, and the Haub Family professor at the Carroll School of Management at Boston College, as well as Gideon Ozik, faculty professor, Risk Institute research associate at the EDHEC Business School for their input provided through our Research Advisory Board.

Our special thanks goes to Tim Smith, Tim Bottke, Sam Roddick, David Linthicum, Garima Dhasmana, and Greg Dost for their collaboration on the “Unleashing digital transformation value” and “Three-dimensional Tech Strategy” research that informed this publication.

The depth and rigor of this analysis would not have been possible without the incredibly skilled Deloitte Data Science and Survey Advisory (DSAS) team, including Alok Ranjan, David Levin, Narasimham Mulakaluri, Paula Payton, Rohan Girish Amrute, Sameen Salam, Sandeep Vellanki, and Utkarsh Londhe. The authors are grateful for their partnership, expertise, and support.

Thanks also to Lynne Sterrett, Rod Sides, Elisabeth Sullivan, Blythe Hurley, Rupesh Bhat, Preetha Devan, Matt Lennert, Molly Piersol, Govindh Raj, Andrew Ashenfelter, and Saurabh Rijhwani for your input, support, and expertise.

Cover image by: Jim Slatton