Despite the hype, big investments, and growing sense of urgency, digital transformation continues to face alarming failure rates. In 2024 alone, multiple reputable sources confirmed that the vast majority of transformation efforts failed to achieve their intended goals.

Why tech transformations fail?

Recent reports including from Bain & Company found that 88 percent of business transformations failed to achieve their ambitious initial goals. Harvard Business Review (HBR) echoed similar sentiments and estimated the failure rate at 80 percent. 

These statistics paint a sobering picture of a global trend: organisations are investing billions in digital initiatives, but only a few achieve sustained success.

At the other end of the spectrum, success rates are just as revealing. According to a 2024 report from BCG, 74 percent of corporate transformations fail — largely due to persistent challenges organisations face in achieving lasting success.

A further report from April 2025 found that the average transformation success rate stands at just 28 percent for firms that do not apply specific success factors. It added that implementing five or more critical enablers — including investments in innovation, rapid optimisation of cost structures, crafting compelling transformation narratives, building transformation experience, and initiating change from a position of strength — can increase this success rate to 55 percent.

These figures underscore a key paradox: while the technology landscape is evolving rapidly, our ability to implement and sustain change effectively is not keeping pace.

So what is going wrong?

Confusing tools with transformation

The fundamental problem lies in a widespread misconception: that digital transformation is primarily about technology. While platforms, software, and automation tools are essential, they are only enablers. True transformation happens in people, processes, and organisational culture.

HR leaders are uniquely positioned to influence this, yet the human side of transformation is too often overlooked or underestimated. Success requires strategic planning, disciplined execution, and data-driven analysis.

A recent striking example is Skype, once a legendary tool for video communication. This tool was a dominant player in the workplace until it lost touch with user needs. Its acquisition by Microsoft did little to prevent its eventual market stagnation. Gradually, the worktech became cumbersome, unintuitive, and failed to evolve in the face of hybrid working.

Zoom and Microsoft Teams, being more aligned with market needs, succeeded where Skype failed by prioritising a fluid, people-centric design.

Skype's downfall serves as a warning: trying to be everything to everyone can dilute a product's core value proposition.

The human cost of digital blindness

One of the most common and costly mistakes organisations make is neglecting the human dimension.

For example, the UK’s NHS Digital Service mistakenly sent 850,000 emails to the wrong recipients. Regardless of fault, the real problem was deeper: a lack of oversight, planning, and systemic thinking.

Too often, leaders become obsessed with launch dates and launch day fanfare, but lack a post-launch adoption strategy.

The real challenge begins after implementation: training users, creating change advocates, integrating new tools into everyday workflows, and measuring real impact beyond technical KPIs.

Without this foundation, even the best technology risks being relegated to the sidelines.

Recent McKinsey research shows that digital blindness remains a significant barrier. For example, 22 percent of employees say they receive little or no support to develop generative AI skills, while only 40 percent of organisations offer some form of incentive, such as recognition or rewards, for adopting these tools.

Despite the fact that 13 percent of employees already use generative AI for doing 30 percent or more of their work, senior managers significantly underestimate this usage, estimating it at only 4 percent. This disconnect reveals a lack of visibility and commitment at the highest levels of leadership.

Psychological and cultural barriers

Gartner research shows that only 22 percent of executives truly understand what digital transformation means for their business.

And Korn Ferry report finds that 65 percent of companies lack digital talent.

This reveals a triple failure in vision, skills, and culture—three elements essential to any meaningful transformation.

From a psychological standpoint, transformation can cause fear, resistance, and confusion.

As Nino Letteriello pointed out in Forbes, the problem is not only operational, but also emotional and cognitive. Using psychodynamic theory, he explains how traits such as perfectionism and paranoia in leadership can derail projects.

Business simulations often ignore the mental state of employees and decision-makers, leading to unrealistic expectations and poor execution.

The famous adage “culture eats strategy for breakfast” is especially true in the digital realm.

If people don't understand the why, don't feel supported during change, and don't trust the process, the initiative is doomed to fail, no matter how innovative the technology is.

This dynamic was evident in the fate of Yammer, also known as Viva Engage, and marketed as the “Facebook for work,” - it often failed because it didn't reflect how teams actually communicated.

In contrast, tools like Slack thrived by mirroring the organic dynamics of teams and offering intuitive, frictionless experiences.

Lessons from consumer tech failures

This mismatch between human needs and digital offerings isn't limited to corporate transformations. High-profile consumer tech failures also reflect a lack of empathy and understanding of the user.

For instance, Google Glass, while innovative, failed to consider social context and privacy concerns. 

The Samsung Galaxy Note 7 literally exploded due to rushed design and inadequate safety testing.

The Amazon Fire Phone was dismissed as a publicity stunt, and Apple's butterfly keyboard sacrificed comfort for elegance, frustrating loyal users.

Even Windows Phone, which boasted a beautiful interface, failed due to a lack of developer support and meaningful app integration.

Each of these failures highlights a crucial truth: technology must serve people, not the other way around.

How to succeed: a people-first framework

So how can organisations reverse the trend and ensure the success of their transformation efforts?

#1 Start with people, not platforms

Technology is the enabler, not the hero. Any transformation must begin with understanding the needs, habits, and challenges of the people who will use the technology.

#2 Be agile and iterative

Five-year plans are often obsolete within two years. Embrace customer feedback, experiment quickly, and adjust course based on actual results.

#3 Redefine leadership

Modern leaders must act as enablers. They must foster psychological safety, support learning, and bridge the gap between strategy and frontline experience.

#4 Measure what really matters

Success isn't defined by downloads or uptime alone. Focus on adoption rates, user feedback, productivity improvements, and cultural alignment.

Where companies fail: summary of failure cases

Despite growing demand, many organisations are not rising to the occasion. Here are the main pitfalls we've seen:

• Lack of AI skills training, as employees receive little or no support to develop generative AI skills.
• Leadership underestimating AI adoption, despite employees using generative AI tools to complete around 30% of their tasks.
• Inadequate integration of AI into workflows, as employees need better integration of AI into everyday tools to increase usage.
• Neglected incentives for AI adoption; more companies should offer incentives such as financial rewards or recognition to encourage AI use.
• Delayed access to AI tools, as companies are slow to provide the tools employees need to improve adoption.
• Lack of personalised training, as companies often implement generic programs that do not match employees' roles or needs, leading to demotivation and poor learning outcomes.
• Ignoring employees who advocate for AI and want to become trainers and change agents.
• Last but very important — overlooking concerns about cybersecurity and privacy, as companies need to include these in their training programs to build trust.