The Great GenAI Divide: Debunking the Myth of 95% Failure
These days, we are drowning in conflicting information about the value of generative and/or agentic AI. I, myself am researching for good studies that dive into the ROI that is generated by this technology, with limited success. Most information is anecdotal, or comes from success stories, which cannot get used too literally. Two major 2025 reports from MIT and Wharton, respectively, paint starkly different pictures of AI adoption and adoption success. While the meanwhile often quoted MIT NANDA “report” on the state of AI in business often gets quoted with 95 percent of all businesses not getting any ROI from their gen AI initiatives, a recent study by the Wharton Business School shows a very different result with 74 per cent of enterprises showing a positive ROI. Why is one so pessimistic and the other so optimistic? As I have written before, a closer look at the data reveals the 95% “failure” narrative is a myth, or even a scare, and the real story is probably a different and far more differentiated one, which Wharton names Accountable Acceleration. Is GenAI really a 1-in-20 lottery ticket or is it rather a core business function? So, let’s have a look. Methodology matters – debunking the 95% failure rate In contrast to the NANDA “report” that relies on a fairly small sample of about 150 survey responses and 52 structured interviews, the. Wharton report bases on a large-scale, quantitative and longitudinal study. It surveyed around 800 senior decision-makers at businesses of different sizes and is tracking trends for the third consecutive year. Therefore, its data is built for statistically valid conclusions. In...
Beyond the Hype: Unlocking GenAI ROI in the Enterprise
My past two column articles on CustomerThink dealt with how to determine the return of agentic investments and whether agentic AI delivers at all. The question of ability to deliver is particularly interesting for me, as I am researching measurable results other than cost savings in contained business areas for some months now, and regularly find a very strong focus on customer service and marketing, with customer service functions being best able to report measurable results. This is evidenced by the number of success stories I find, supported by the publication of a recent TEI of Zendesk customer service study. However, most of this is anecdotal evidence, or vendor sponsored/commissioned. And which vendor likes to speak about failures? Similar for buyers who understandably do not like to be in the spotlight with investments that turned out to be less than successful. There hasn’t been too much in depth research on whether generative and/or agentic AI deliver to promise or not. Luckily, there has been at least some research evaluating the capabilities of LLM based AI agents in business environments published this year. CRMArena-Pro by Salesforce Research naturally has a focus on CRM tasks across B2B and B2C scenarios. The authors identified nineteen tasks commonly executed in CRM systems and categorize these tasks in the four business skill categories database querying and numerical computation, information retrieval and reasoning, workflow execution, and policy compliance and includes a confidentiality awareness evaluation. TheAgentCompany on one hand covers a wider area along the business value chain but on the other hand has a narrower focus on software engineering companies. One other main difference between...
Does Zendesk enable a true human – AI partnership?
The news On October 9, 2024, Zendesk held its AI Summit in New York’s Chelsea Industrial. The AI Summit is an event mainly for customers to inform themselves about what is new at Zendesk but also to network with each other. The event featured an interesting lineup of customer and partner speakers, headlined by New York Times bestselling author and podcast host Kara Swisher. My estimate is that there have been more than 250 customer representatives in attendance who not only could listen to the speakers but also get in-depth demos of Zendesk’s updated offerings, following real-life use cases. True to its name, the event centered around the use of AI, in particular bots, to increase not only efficiency, but also customer- and employee satisfaction. CEO Tom Eggememeier opened the event with an emphasis that Zendesk’s AI is built to support humans by stating that it “is designed for humans”, and Zendesk’s service solution is built to strengthen the human – AI partnership. Kara Swisher talked about the promise and peril of AI, giving the audience some food for thought on the day after Geoffrey E. Hinton, the godfather of machine learning turned AI warner got co-awarded the 2024 Nobel Prize in Physics for his “foundational discoveries and inventions that enable machine learning with artificial neural networks”. While Swisher sees the value that the use of AI can bring, she, too, warned about the hurdles that still need to be overcome, namely the concentration of power that the technology creates and its immense hunger for energy. The tie into the Zendesk story is that customer service is a prime...