The gap between individual AI productivity gains and organizational transformation reveals four critical barriers to AI value realization.

During a recent IT strategy workshop with a major bank’s leadership team to help them develop their strategic technology roadmap for an upcoming board presentation, I witnessed something expected but still remarkable: All 20 participants were using their favourite AI tools (ChatGPT, Copilot, Claude … ) to accelerate their ideation, refine their language, and explore strategic initiatives. Yet despite this widespread adoption, the organization struggled to use AI alone to define a unified IT strategy.

This paradox encapsulates one of the most pressing challenges facing enterprises today: the disconnect between ubiquitous AI adoption at the individual level and the absence of transformational business impact at the organizational level.

The AI Adoption Paradox

We’re experiencing an unprecedented convergence of three powerful forces:

  • Accelerating AI capabilities. The pace of AI advancement has reached a weekly cadence, with new models and capabilities emerging faster than organizations can absorb them. As Andrej Karpathy recently noted, we’re still in the “mainframe era” of this new computing paradigm, with chat interfaces serving as our primary gateway to increasingly sophisticated AI systems.
  • Employee-led AI adoption. Knowledge workers are bringing AI to work whether management knows it or not. They’re experiencing real productivity gains: writing faster, thinking more clearly, and tackling previously impossible tasks. The individual value is undeniable and growing. Like the internet and mobile, AI computing is shifting powerful capabilities directly into the hands of people, both employees and customers, creating new possibilities but also new challenges for organizations trying to harness this democratized power at scale.
  • Missing organizational impact. Despite widespread individual adoption, we’re not seeing corresponding improvements in corporate balance sheets, GDP figures, or macroeconomic productivity metrics. The micro-level gains aren’t translating to macro-level transformation.

Four Barriers To AI Value Realization

Based on extensive client engagements and industry observations, four fundamental barriers prevent organizations from capturing AI’s transformational potential:

  1. The vision vacuum. Most organizations lack a compelling vision of what AI means for their specific business context. They haven’t answered fundamental questions: What does AI mean for the future of banking? How can manufacturing be reimagined through AI? What new value propositions become possible? Without this North Star, AI initiatives remain scattered tactical implementations rather than strategic transformations. The bank I was working with needed external guidance to develop its technology roadmap — a capability that should be core to any financial institution’s strategic competence.
  2. The use case trap. Organizations are drowning in discussions about individual AI “use cases” and “agents” while missing the bigger transformation story. This myopic focus, often driven by vendors that benefit from keeping enterprises locked into tactical implementations, prevents leaders from developing the comprehensive transformation plans they actually need. Just as moving from mainframe to PC required a fundamental shift in computing architecture and not just a catalog of individual programs, the AI transformation demands strategic planning at the platform and ecosystem level. The unit of planning has been usurped by vendors that want to sell point solutions rather than enable true transformation. As our CEO George Colony argues in his blog The Seventh Wave: How AI Will Change The Technology Industry, legacy vendors are “faking it until they can make it, pretending that their platforms can transition to the Seventh Wave” — keeping organizations trapped in tactical thinking rather than true transformation.
  3. The middle management bottleneck. While individual contributors gain value from AI tools, middle management often becomes an inadvertent barrier to scaling these benefits. The challenge isn’t capability; it’s courage. No manager wants to take responsibility for saying, “This process that’s working fine today? We’re going to stop doing it this way and try something completely new because I’m confident AI can help us do it 10 times better.” This risk aversion is compounded by the current environment, with headlines regularly featuring major layoffs at tech companies and middle management bearing the brunt of these cuts. When job security feels precarious, taking bold innovation risks becomes even less appealing.
  4. The innovation muscle atrophy. Many organizations have lost their capacity for self-directed innovation and strategic thinking. They’ve become dependent on external consultants for capabilities that should be internal competencies. This dependency creates a dangerous cycle: The more they outsource strategic thinking, the less capable they become of leveraging AI for true competitive advantage.

The Path Forward: Beyond Paving Cow Paths

Real AI transformation requires more than applying new technology to existing processes. It demands fundamental process reinvention across core business functions such as customer onboarding, order to cash, procure to pay, claims processing, customer service, and beyond. Organizations that break through the ROI barrier will need to:

  • Develop a dynamic strategic approach. Rather than relying on a single fixed vision, leaders must combine a directional view of how AI will reshape value propositions (including revenue models, products, and services) with methodologies that continually explore and test new ideas. The fast-changing nature of AI demands adaptive strategies that can evolve as the technology landscape shifts.
  • Invest in deep AI literacy and innovation. Move beyond basic prompt engineering to develop organizational capabilities in AI strategy, implementation, and governance while rebuilding the innovation muscle that many organizations have lost.
  • Incentivize bold experimentation. Create reward systems that encourage employees to pursue 10x improvements in speed and cost reduction, not just incremental gains.
  • Plan for platform migration. Prepare for the shift from deterministic to agentic computing. Just as organizations migrated applications from mainframe to PC to mobile, tomorrow’s AI landscape will require running both newly automated processes and transformed legacy workflows on entirely new computing platforms that extend far beyond today’s chat interfaces.
  • Embrace process reinvention. Challenge every existing workflow and business process to identify opportunities for fundamental redesign rather than superficial optimization.

The Forrester Advantage: Build Strategic Capabilities, Not Dependencies

As I observed during the bank workshop, there’s still tremendous value in research-based guidance that helps organizations navigate the complexity of AI transformation. But here’s the crucial difference: Rather than creating dependency through traditional consulting models, Forrester’s research and continuous guidance approach aims to build internal strategic capabilities and competency.

The bank workshop exemplified this distinction. Instead of delivering a finished roadmap, we provided frameworks, best practices, and methodologies that equipped the leadership team members to think strategically about their AI future. The goal wasn’t to do the thinking for them but to enhance their ability to think systematically about technology strategy: a core competency that every organization needs to develop internally.

This capability-building approach becomes even more critical in the AI era, where the pace of change demands that organizations develop their own strategic agility rather than relying on external execution or undifferentiated AI-generated strategy content.

Organizations that successfully bridge the gap between individual AI adoption and organizational transformation will create sustainable competitive advantages. Those that remain trapped in the paradox of widespread AI adoption without strategic AI impact will find themselves increasingly left behind.

What’s your organization’s experience with AI ROI? Are you seeing the transformation you expected, or are you caught in an adoption paradox? Let’s meet and discuss at Technology & Innovation Summit APAC 2025 in Sydney on August 19!