Technology alone is not strategy
A new MIT study shows again that AI is not a panacea for stalled revenue or lost competitiveness, as some have claimed. This paired with IBM’s recent CEO Study, shows a clear message is emerging to the myriad stakeholders in enterprise AI; whilst generative AI has become a strategic imperative and near ubiquitous investment, its successful implementation is more elusive.
The burgeoning gap between AI capability and profitable utilisation makes clear that business fundamentals remain essential; the true differentiator is how and where AI is applied.
Sheryl Estrada
IBM’s 2025 CEO Study: 5 Mindshifts to Supercharge Business Growth, surveying over 2,000 CEOs across 24 industries, outlines five conceptual “Mindshifts” intended to guide enterprise leaders through structural and operational change. Yet the most compelling insight lies not in the shifts themselves, but in the dissonance between executive belief and organisational readiness.
Tom Hogan
Unsurprisingly, 68% of CEOs believe that generative AI is fundamentally transforming their business models. 61% agree that competitive advantage will increasingly depend on their ability to adopt and scale it. However, 25% of AI initiatives have not delivered their desired results. The Issue is not willingness to implement but the actual use cases and methods that are being adapted.
At Felix Research, we interpret this divergence as validation of our central philosophy: the future of enterprise AI lies not in general-purpose automation, but in domain-specific human-centric Augmented Intelligence applications. The difference is nontrivial. Most Large Language Models currently deployed in enterprise settings are designed for maximum generality. The demand for purpose-built tools that champion human-in-the-loop principles remains neglected in the market.
The IBM report’s fourth Mindshift, Ignore FOMO, lean into ROI, speaks directly to this challenge. The data confirms that early adopters who rushed into AI pilots often did so without clear KPIs, governance, or integration pathways. Felix Research believes that the future of AI implementation will be with platforms that allow humans to focus on high value critical task using AI to handle routine functions. In turn, high-value research is generated, and ROI is clearly measurable.
The third Mindshift, Cultivate a vibrant data environment, is another area wherein the gap between vision and execution remains wide. Although 72% of CEOs consider integrated data architecture essential for AI success, actual approaches to achieve this shift are far and few between.
Perhaps the most important theme emerging from IBM’s report is that trust remains a structural constraint on AI adoption. Though not framed as a discrete Mindshift, it permeates each of the five. In high-stakes, research-rich fields, model transparency, auditability, and explainability are not optional, they are the bedrock of ethics-by-design and consequentially, sourcing, trust and functionality. There is little use for work you cannot trust.
IBM’s final Mindshift, Borrow the talent you can’t buy, may be the most telling. In a landscape where speed-to-deployment and domain expertise are both required, external partnerships are not a liability; they are a strategic advantage. There is a dearth of institution-grade tools, developed in close collaboration with project-based professionals, and tested against the real workflows it aims to support. Felix Research encourages you to watch this space.
IBM’s 2025 CEO Study provides a useful framework for assessing the future of AI adoption. But the study’s most important implication may be that generative AI alone will not produce transformation.
Only well-scoped, governed, and trusted AI systems, purpose-built for specific domains, will do so.
Felix One is that system.