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GEN AI ISN'T JUST A TOOL. IT'S A TEST

  • Writer: Yanai Klawansky
    Yanai Klawansky
  • Oct 2
  • 5 min read
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By Yanai Klawansky


Gen AI is not just another tool. It’s a capability that should fundamentally rewire how organisations

think, work and adapt. Anything less is not just shortsighted. It signals a strategic failure in the making.


Because the truth is: Your employees are using ChatGPT right now. Not for fun. For actual work. While your leadership team debates governance frameworks and best practice, knowledge workers are quietly reinventing workflows with AI use cases they've discovered themselves. And adoption will only get faster and more pervasive: 76% of workers surveyed by Microsoft believe Gen AI is already improving their productivity, while McKinsey reports that 94% of employees and 99% of executives now say they are at least familiar with generative AI tools.


One of the biggest outtakes from our work with clients across the continent is this: change capability

– not just change – will determine which organisations thrive in a Gen AI era, and which are left behind.


Why traditional change management falls short

For decades, organisations have managed change through structured programmes with neat beginnings and rigid endpoints. Yet only 34% of major change initiatives achieve their stated goals, even as most organisations now face five significant shifts every three years. The traditional change playbook, already under strain, simply cannot keep pace with the exponential disruption of Gen AI.


Because Gen AI doesn’t behave like past technologies, it demands a rewiring of capability.

 

Take Singtel, Asia’s largest telecom operator with a footprint in more than 20 countries. By creating an AI Academy to train 10,000 employees, they signalled the real shift: the work isn’t about software – it’s about institutionalising capability at scale. But Singtel is the exception: most organisations remain stuck in outdated assumptions about AI’s scale and speed – and what it really means for daily work.


The evidence is striking: employees believe Gen AI could replace 30% of their work, yet only 2% are engaged in formal transformation efforts. This isn’t resistance; it’s leadership lag – and leadership lag is now the critical risk to universal adoption.


The people paradox: ready employees, unprepared systems

Leaders often assume that their people resist change. But the research tells us something different. When it comes to Gen AI, employees are ahead of the curve, with almost half (48%) saying formal Gen AI training would increase their daily use.


The readiness data:


81%

44%

37% 

of workers 
of HR leaders
of the workforce

expect their employer to provide AI skills training.

plan semi-autonomous

AI agents within the next

12 months.

faces Gen AI disruption soon.

The message is clear: employee eagerness is outpacing organisational preparation. This readiness gap is both the greatest risk in AI transformation, and the biggest opportunity.


Building change as capability


Forward-thinking organisations are abandoning the programme mindset, embracing what my colleague, TPA senior partner Brandon Lawrence calls "change as a capability." This isn't semantic repositioning,  it's a fundamental reimagining of how organisations adapt and evolve.

 

Here’s what we know leaders need to focus on to make it real:


1. Continuous learning infrastructure

Leaders must create perpetual learning ecosystems, not one-off training. Singtel's AI Academy exemplifies this, teaching AI thinking, not just tool usage. The focus shifts from completing training to building ongoing competence.


2. Distributed leadership model

Mid-level leaders are crucial multipliers, embedding AI into personal practices, team workflows and translating strategy into action. They become translators, educators, and advocates who bridge the gap between strategic vision and operational reality. They're uniquely positioned to identify AI opportunities that senior leadership might overlook.


3. Adaptive governance

Traditional governance assumes predictable change trajectories. AI demands something different.

The best organisations are using a two-in-the-box approach where business and technology teams work together to define new ways of working. Business teams ensure value delivery while technology teams ensure feasibility - a dynamic partnership rather than sequential handoffs.


Building trust alongside capability


Fear is still one of the biggest barriers to adoption. Nearly half of employees worry about AI inaccuracy and cybersecurity risks. Yet organisations investing in transparency see results: two-thirds of HR leaders trust AI agents when proper governance exists.


However, trust requires more than compliance checklists. It demands transparency about AI’s role as a performance enabler, inclusive development that actively involves employees in shaping solutions, and quick wins that prove impact early.


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A practical to-do list for leaders


  • Start with skills, not systems: Use strategic workforce planning to anticipate AI's impact. Map capabilities, identify AI-augmented roles, and create personalised development pathways.

  • Create AI champions everywhere: The best organisations rely on their workforce, not executives, to lead change. Empower advocates who demonstrate practical applications.

  • Measure capability, not completion: Assess whether employees can independently identify AI opportunities, risks and implement solutions, not just training attendance. This shift from activity to outcome measurement fundamentally changes how organisations evaluate progress.

  • Build resilience through iteration: Organisations face technical barriers such as poor data quality, integration complexity, or infrastructure costs, but the primary obstacle is the ability of companies to adapt, reinvent, and scale new ways of working. Create safe spaces for experimentation, celebrate intelligent failures, and continuously refine approaches based on learning.


The TPA Perspective: Muscle memory over management


At TPA, we treat change as organisational muscle memory, not project management. Because we understand that real change doesn't live in slide decks. It lives in actual, on-the-ground capability.


What does this look like? When change becomes capability:

  • Leaders build lasting resilience that outlasts any single transformation.

  • Teams develop adaptability that accelerates future change.

  • Organisations create sustainable competitive advantage through continuous evolution.


The evidence is clear: organisations that embed change as capability – rather than manage change as programmes – will define the next era of business. The question is no longer whether to adopt Gen AI. Employees already have. The real question is whether leadership will build the organisational muscle to harness and scale this transformation.


Three things to do right now


1. Audit your approach.

Are you still running programmes, or are you building capability?


2. Back your mid-level leaders.

They are multipliers of change, not obstacles to it.


3. Follow your employees.

They are already ahead. Build from the AI adoption that is happening today.



The bottom line


Organisations treating Gen AI as technology implementation will be disrupted by those who've built change into their DNA. The era of change programmes is ending. The age of change capability has begun. Ultimately, leaders who build resilience, adaptability, and continuous learning into their core won't just survive the Gen AI transformation, they'll lead it.


Yanai Klawansky is an executive consultant and former commercial lawyer with expertise in organisational capability, translating strategic vision into action to harness the transformative power of Gen AI.


Are you ready to transform your organisation's change capability? 
The Performance Agency has spent 25 years building resilient, adaptable organisations across Africa and globally. Explore how we can help you move beyond traditional change management to build true organisational capability for the AI era.


Further reading

 



Read more about Yanai's recent projects

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