In 2026, the Gap Won’t Be About AI Adoption - It Will Be About Leadership

Happy New Year!

The beginning of a new year always invites reflection - not just on personal goals, but on how we work, lead, and build companies.

Having moved across and worked with organizations in the US, UAE, and Japan, one thing has become increasingly clear:

In 2026, your AI strategy will define the future of your company - whether you like it or not.

Not because AI is magical.

And certainly not because every company needs to become an “AI company.”

But because the way leaders respond to AI pressure reveals how decisions are made, how change is led, and how organizations adapt under uncertainty.

What’s particularly interesting is how differently this is unfolding across regions.

UAE: Individuals Are Moving Faster Than Organizations

In the UAE - particularly in Abu Dhabi and Dubai - governments are investing aggressively in AI, spanning public services, infrastructure, education, and industry-wide initiatives.

At the same time, corporate adoption remains relatively cautious.

The contrast is striking:

• Organizations move carefully, often waiting for direction

• Individuals move fast

At the individual level, generative AI adoption is already high. Professionals actively use tools like ChatGPT to:

• Upskill

• Improve productivity

• Stay competitive in a highly international, performance-driven job market

AI has become a personal differentiation and survival tool, even as organizational structures lag behind.

The result is a growing gap: productivity gains are happening quietly at the individual level, while organizations struggle to translate that momentum into coordinated action. For many companies, AI remains a marketing term rather than a clearly understood capability.

This gap between individual capability and organizational readiness is likely to persist in the near term. The open question is when - and how - corporate adoption will begin to convert national ambition into operational impact.

Japan: High Awareness, Low Internal Ownership

In Japan, awareness of AI - especially generative AI - has grown rapidly over the past two years. Surveys show that over 40% of companies are now experimenting with or partially deploying generative AI in some form. On the surface, this suggests steady progress.

But a closer look reveals a different pattern.

Most initiatives remain narrow in scope:

• AI chat assistants added to existing products

• Internal pilots limited to single departments

• Experiments driven by external consultants rather than internal ownership

What’s missing is not interest - it’s strategic capability inside the organization.

AI adoption in Japan remains largely outsourced.

Job postings for AI consultants, DX advisors, and transformation specialists continue to rise, reflecting a strong dependence on external expertise. Large consultancies dominate, often deploying standardized frameworks with teams that rotate frequently and may lack hands-on implementation experience.

This model works well for analysis and planning.

It struggles, however, when it comes to:

• Building internal decision-making confidence

• Translating AI concepts into daily operational behavior

• Sustaining momentum after consultants exit

As a result, many initiatives look strong on paper but stall during execution.

At the employee level, generative AI usage is already happening - quietly and unevenly. A small number of highly motivated individuals are experimenting and benefiting, but their insights rarely reach management. Most employees wait for clear leadership direction before taking action.

Companies that recognize AI’s potential and actively empower employees to become “AI-enabled” - rather than treating AI as an external initiative - are likely to be significantly ahead in 2026.

The US: Speed, Pressure, and the Fear of Being Replaced

In the US, particularly among large tech and product-driven companies, AI adoption is moving at full speed.

AI is being embedded into:

• Internal workflows

• Customer-facing products

• Performance expectations

But speed comes with pressure.

Many professionals now operate under a new reality:

The tools they are implementing may eventually replace parts of their own role.

This creates a paradox:

• AI acts as a powerful productivity accelerator

• AI is simultaneously perceived as a job threat

Organizations push aggressively to stay ahead, while individuals scramble to remain relevant. This model delivers visible short-term gains but raises questions about long-term sustainability - both for organizations and for the people operating within them.

What All Three Regions Have in Common

Despite regional differences, the same pattern appears everywhere.

AI initiatives don’t fail because of technology.

They fail because of:

• Unclear priorities

• Decisions made without shared understanding

• Execution gaps between strategy and reality

AI amplifies what already exists:

• Strong leadership becomes stronger

• Weak decision-making becomes more visible

This is why AI strategy is not a tooling problem.

It is a leadership and execution problem.

Why the Start of the Year Matters

According to research by Dr. Katy Milkman, a behavioral scientist humans are uniquely motivated by “fresh starts.” New years, birthdays, and career transitions create psychological permission to change behavior - not just set intentions.

Yet knowing what to change is rarely the hardest part.

The first challenge - whether personal or organizational - is getting started.

At an individual level, AI can support new habits, clearer thinking, and faster experimentation.

At an organizational level, AI can accelerate value creation - internally and externally - if leaders understand where it fits and how to begin.

Used well, AI becomes a force multiplier for clarity and action - including the ability to take the first step.

A Note from GetItDoneWith.AI

At GetItDoneWith.AI, we work with leaders and teams who feel the pressure of a rapidly changing AI landscape - and want to respond thoughtfully, not reactively.

Whether you are:

• Rethinking leadership behaviors

• Aligning teams around smarter execution

• Exploring how AI can support real business outcomes

We focus on helping organizations start well - because how you begin will shape what follows.

If this year marks a new chapter in how you lead, decide, or work with AI, we’re here to support that start.