As part of our Edge Thinkers’ series, Anneke Quinn-de Jong, Founder of AI & U, shares her expert view on why brands are struggling to implement AI optimally and what they can do to drive better value and organizational change from future AI investments.

Introduction

When GenAI burst into the mainstream at the end of 2022, many business leaders jumped on board, initiating AI investments with expectations of a long-term competitive edge. Two years along the line, technology continues to evolve at unprecedented speed, but a sobering reality has emerged: most organizations have failed to transform their AI investments into lasting competitive advantage, with up to 80% of AI initiatives never fully delivering on their promise. (1)

The consequences are widespread disappointment, confusion, and even complete abandonment of AI efforts: 42% of companies have already walked away from the majority of their AI projects. (2)

It is easy to point the finger at AI (“you see, it is all hyped up”), but the reality is different: the technology isn’t failing us; we’re failing ourselves.

So, what exactly is going wrong? And more importantly – how can we fix it?

In my ongoing conversations with leaders across organizations – reinforced by various research reports – two significant blind spots consistently emerge:

• Organizations often have a constrained view of AI’s role. Many see AI primarily as a productivity enhancer, a tool to cut costs and increase efficiency, rather than harnessing it to drive higher-quality outcomes or enable transformative, system-level innovation.

• There’s a widespread lack of organizational readiness. Companies tend to approach AI implementation purely as a technical project. As a result, they underinvest in their people – neglecting to upgrade skills, address cultural barriers, and overcome resistance to change – crucial steps that ultimately determine whether AI will thrive or fail within an organization.Your bran is wired to think about the future – but not always in ways that serve you well.  Our instinct is driven by short-termism – whether, for individuals, cashing in for a smaller but instant reward today, or for business leaders, short-changing longer term strategy in favour of next quarter’s results.

Blind Spot 1: A Constrained View on the Role of AI

Viewing AI primarily as a technological tool to boost productivity has two significant consequences.

First, it severely underuses AI’s transformative potential. Focusing solely on productivity improvements, such as automating emails or speeding up current workflows, won’t create long-term competitive advantage because competitors have access to the same AI tools. AI’s true power, lies in radically re-imagining our world and fundamentally transforming how businesses and individuals operate.

Second, a narrow productivity focus makes companies vulnerable to “shiny object syndrome.” People get distracted by the buzz and adopt tools without clearly connecting them to concrete business needs. The real power of AI comes from aligning tools directly with strategic goals and specific organizational challenges. This requires a holistic approach and active collaboration between technical teams, HR, ethics committees, domain experts, and senior leadership. Without this multidisciplinary approach, AI tools risk being underutilized, misaligned with company needs, and ultimately disappointing in their impact.

Blind Spot 2: A lack of organizational readiness

According to World Economic Forum research, the most significant barriers to business transformation aren’t technological – they’re human. Specifically, the lack of appropriate skills and deep-rooted resistance to change within organizational culture consistently emerge as major obstacles. Yet, many organizations still fall into the trap of approaching AI as a project rather than a Change Management exercise.

The first misstep is overlooking the profound psychological and cultural barriers to adoption. Implementing AI demands people to rewire deeply entrenched habits, routines, and workflows – something inherently uncomfortable and resisted by our brains. Organizational cultures are rarely ready for the scale of change AI demands; many leaders fail to acknowledge that resistance isn’t stubbornness or incompetence but a natural human response to significant shifts. Overcoming this resistance isn’t about forcing adoption – it’s about creating psychological safety, clear purpose, and alignment around AI’s strategic role.

The second fundamental misstep is that most leaders significantly underestimate the need to equip employees not just with basic technical proficiency but also with the cognitive and interpersonal skills to leverage AI’s real value. Training employees merely on the mechanics of AI tools (if they get training at all) is inadequate. They must learn how to creatively prompt, critically interrogate, and intelligently integrate AI-generated insights. Without these deeper human capabilities, AI remains at surface-level productivity rather than becoming a transformative tool.

At its most dangerous, AI implementation without human readiness can lead to cognitive offloading, where employees lean passively on AI rather than engage critically with it. Instead of enhancing decision-making, AI risks eroding the human ability to think deeply, reason effectively, and challenge assumptions – unless organizations consciously cultivate a culture of active, thoughtful collaboration with AI.

The Horizon

The organizations that will lead in the next five years won’t be the ones with the flashiest AI tools. They’ll be the ones that rethink how humans and machines work together – and prepare their people accordingly.

By 2030, employers expect work to be split almost evenly between humans, technology, and human–machine collaboration. At the same time, nearly 40% of today’s skillsets are expected to become outdated. (3)

The challenge ahead isn’t just about keeping up with AI innovation. It’s about reimagining how work happens, how talent is developed, and how value is created. This requires a shift in mindset – from viewing AI as a set of tools to implement, to embracing it as a catalyst for deep organizational change.

The most forward-thinking leaders are already moving in this direction. They’re not asking “how can AI save us time?”, they’re asking “how can AI help us think better, design better, and lead better?” They’re investing in people as much as platforms, and making sure AI enhances (not erodes) the uniquely human capabilities that drive real innovation.

How to approach the future

To move confidently into this co-intelligent future, organizations must confront the blind spots holding them back today – and turn them into deliberate strategic shifts. Here’s what that transformation could look like in practice:

Conclusion

The real competitive advantage in the age of AI doesn’t come from the technology itself – it comes from how you combine widely available tools with your unique data, your unique assets, and your unique people. This is what makes transformation real, resilient, and hard to replicate.

To lead in this new era, we must define and shape a co-intelligent future – one where humans and machines complement each other to create more value than either could alone. That requires a new mindset: human-cantered, ethically grounded, and focused on long-term capability-building – not just quick wins.

So, the question isn’t “Are you using AI?” It’s “Are you using AI to fundamentally evolve how your organization thinks, works, and grows?”

To see more updates from Next Up’s expert network, please visit our edge thinkers page on our website: https://nextupforesight.com/edge-thinking/

Sources:

1. The Root Causes of Failure for Artificial Intelligence Projects and How They Can Succeed | Rand
2. Win with AI: Lead the Human Side of Change | Prosci
3. Future of Jobs | WEF
4. Why AI isn’t delivering and what you can do about it | Dave Birss
5. Co-Intelligence | Ethan Mollick
6.  The Cybernetic Teammate | Ethan Mollick
7. Making AI Work: Leadership, Lab, and Crowd | Ethan Mollick
8. AI Strategy Playbook | BOI
9. Leadership Futures | World of Work institute
10. AI’s Biggest Threat Isn’t Technology – It’s Us | Mo Gawdat