Execs Believe in AI Business Model Reinvention, But Often Can Cite Little in the Way of ROI

I’m always a bit circumspect about surveys of C suite executives about their expectations about business challenges and opportunities, but more so about perceptions of opportunities than challenges. For example, a recent PwC survey of C suite execs shows high belief that generative AI (large language models) will enable business model reinvention. 

 

source: PwC 

At the same time, those same executives report--as virtually always is the case--that return on investment from technology investments remains “elusive.” 

source: PwC 

That is basically in keeping with a general rule of thumb that up to 70 percent of information technology initiatives and projects fail to produce the desired business upside. 

In other words, C suite executives typically have high hopes for what new technology can do, but 70 percent of the time find that the expected payoffs do not materialize. 

So it would be rational indeed to expect that generative AI will mostly fail to enable “new business models” for most companies and projects. 

So the findings should not come as a surprise. Many studies suggest that such transformations are relatively rare. 

Study	Methodology	Key Findings	Limitations
McKinsey & Company (2020):	Survey of 1,200 executives	Only 8% of digital transformations deliver more than 10% improvement in financial performance.	Focuses on broader digital transformations, not solely new business models.
BCG (2020):	Analysis of 1,000 transformation efforts	Only 30% of transformations met or exceeded their target value and resulted in sustainable change.	Doesn't differentiate between types of transformations.
Standish Group Chaos Report (2020):	Survey of IT professionals	Only 29% of projects are successful (meet scope, schedule, and budget).	Doesn't distinguish between types of IT projects.
MIT Sloan Management Review (2019):	Survey of 448 executives	70% of respondents reported challenges in scaling and measuring the impact of their new business models.	Limited sample size, self-reported data.
McKinsey & Company (2021):	Surveyed 1,500 executives	20%	Only 20% of digital transformations achieve their full potential, while 70% fall short.
McKinsey & Company (2021):	Surveyed 1,500 executives	20%	Only 20% of digital transformations achieve their full potential, while 70% fall short.
Boston Consulting Group (2020):	Analyzed 1,200 transformation initiatives	30%	30% of transformations met or exceeded their target value and resulted in sustainable change, while 44% created some value but didn't meet targets.
Standish Group Chaos Report (2020):	Analyzed 50,000 IT projects	64% successful	64% of projects were considered "successful" based on meeting scope, schedule, and budget, but only 29% were considered "highly successful" with significant business value.
MIT Sloan Management Review (2018):	Surveyed 1,500 executives	33%	33% of digital transformation initiatives met or exceeded expectations.
Capgemini Invent (2022):	Surveyed 1,000 global executives.	59% of respondents reported success with IT projects aimed at business model innovation, but only 22% considered it "highly successful."
PMI Pulse of the Profession (2023):	Analyzed data from over 34,000 project managers.	75% of projects met their original goals or were considered successful, but only 37% met all predefined success criteria.

And even within the AI category, it seems likely that “predictive” use cases--where past and present data is analyzed to make predictions about future behavior--is going to generate most of the identifiable returns. 

As a tool for writing code or generating content, generative AI only solves some problems. Data mining about actual customer behavior is likely to find more substantial application on the revenue and cost functions for most companies.