Why Do AI Projects Fail? IBM Executive: Lack of Leadership and Process Disorder Are the Main Causes
In an interview with CFO Dive, IBM executive Neil Dhar stated that many enterprises' AI projects fall into a 'scientific experiment' dilemma due to insufficient leadership and lack of process reengineering. He suggested that CFOs, as asset stewards, drive AI investments to achieve quantifiable returns, and cited CEO survey data indicating that 80% of executives expect AI to bring significant revenue by 2030, but only 24% are clear about the revenue sources.
Leadership and process gaps are dragging down AI projects: IBM executive views
IBM's Neil Dhar points out that without strong leadership and process discipline, "you're just doing science experiments, and you won't get very far."
According to Neil Dhar, senior vice president of IBM Consulting for the Americas, companies struggling to achieve substantial returns from artificial intelligence often share a common problem: too many isolated pilot projects and insufficient focus on transforming core business processes.
Currently, many organizations are under pressure to shift from AI experiments to a more precise focus on measurable outcomes.
This shift is prompting companies to adopt a more disciplined approach to AI. Dhar said in an interview that the key is to redesign legacy business processes before AI deployment and rely on strong leadership to ensure tangible results.
"Otherwise, you're just doing science experiments, and you won't get very far," he said.
The following is a transcript of the Q&A between Dhar and CFO Dive reporter Alexei Alexis, edited for clarity and brevity.
CFO Dive: How have CFOs' priorities in AI investment changed in recent years?
Neil Dhar: Looking back at the AI wave we've seen, it truly took center stage only a few years ago. The initial focus was clearly on education, because most people lacked basic awareness of AI.
In the early stages, many companies, driven by fear of missing out (FOMO), launched numerous siloed proof-of-concept projects that often failed to make substantial progress and yielded meager returns on investment. In many cases, companies accumulated considerable costs while chasing their AI dreams.
But over the past six to nine months, the industry's focus on return on investment has intensified significantly, and CFOs are at the core of driving this shift.
CFO Dive: Compared to traditional corporate investments, does AI present new ROI challenges for CFOs?
Neil Dhar: I believe AI return on investment is absolutely trackable, but only if there is discipline, just like any previous transformation. Companies with discipline will be able to capture value, communicate value, and reinvest in value.
Take IBM's own AI journey as an example. We identified key workflows critical to the company where there were opportunities to achieve real AI gains. We worked to measure those gains while also paying attention to customer and employee satisfaction.
CFO Dive: When measuring AI return on investment, are some areas easier to quantify than others?
Neil Dhar: At the productivity level, some things are relatively easy to measure. For example, if a task originally took X amount of time, can AI help complete it in less time?
But funding growth or innovation is always harder to evaluate, that's a fact.
We recently released aCEO surveythat contains some very interesting data points: 80% of executives expect AI to drive significant revenue growth by 2030, but only 24% are clear about where that revenue will come from. Simply put, revenue growth is harder to measure.
CFO Dive: Some surveys show that many companiesstill haven't achieved substantial returns from AI investments. What are the biggest mistakes holding them back?
Neil Dhar: First, I think it's the lack of a technology-first mindset among senior leaders; AI projects are delegated to people three levels down, and the executive team isn't truly involved. Second, it's the approach of jumping straight into AI projects without thoroughly breaking down business processes first. I think these are the two most common mistakes.
You have to be willing to look at processes end-to-end and ensure there is strong leadership to drive tangible outcomes. Otherwise, you're just doing science experiments, and you won't get very far.
CFO Dive: What role should CFOs play in ensuring AI investments generate real returns?
Neil Dhar: My view is simple: the CFO is the steward of the company's assets. As a CFO, every dollar of capital you spend should bring a return. In my view, that return should be around 2.5 to 3 times.
AI investment is no exception. CFOs must be highly focused on ensuring the AI journey produces real, tangible benefits.
In many ways, the CFO is responsible for establishing tracking mechanisms to determine whether investments are making a difference. At the same time, the CFO is also responsible for ensuring that any information communicated to the board and investors is backed by auditable data.