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A OneStep View
December 2025
Why Too Many AI Initiatives Wither Before They Bloom
OneStep’s AI ‘gardening guidance’.
Cultivate digital dexterity
Assess current capabilities: Can your people confidently navigate technology, or do they struggle with basic digital tools?
Build foundational skills: Train teams in digital literacy, data interpretation, and comfort with experimentation
Remove rocks and weeds: Clear away outdated processes, legacy systems thinking, and technology fear
Equip managers to lead change
Assess manager readiness: Only 23% of IT leaders say their managers are ready to help employees navigate technological change - where do yours stand?
Strengthen change leadership capability: teach managers (gardeners) how to nurture growth through resistance and ambiguity - not just communicate a plan
Clarify their role: What are managers accountable for cultivating? What decisions can they make?
Enrich with trust & psychological safety
Create manager support systems: Peer networks, coaching, safe spaces to process personal concerns before leading others
Create a culture of learning: Make it safe to ask ‘dumb questions’ about AI
Build trust gradually: Start with AI that augments (not replaces) human work
Address fears openly: Talk about job evolution honestly - ditch the "AI won't replace you" platitudes
Show the humans behind the AI: Demystify how AI works, its limitations, and who's ultimately accountable
Establish ethical boundaries & governance
Set clear guardrails: Define what AI can and can't do in your context
Respect data privacy: Clear policies on what data feeds AI and how it's protected
Address bias and fairness: Ensure AI doesn't perpetuate harmful patterns
Create accountability structures: Who reviews AI decisions? What's the human override process?
Organisations that skip ‘soil preparation’ see low adoption, resistance, and failed pilots. Early adopters who are leap-frogging ahead with AI in their personal lives need clear guardrails at work. Those not used to AI need to feel capable and safe before they'll embrace it. And line managers need to be confident and capable to land the changes.
Adequate preparation becomes the critical factor for whether AI investments create value or expensive chaos.
Phase 1: Prepare the soil
Poor soil = failed crops. Before you plant anything, the ground must be ready.
Phase 2: Plant the right seeds
Now that the soil is ready, choose your seeds wisely and plant them with care.
Select the right AI solutions
Match to soil conditions: Don't plant orchids in clay. Choose AI that fits your organisation's ambition and maturity level
Start with high-impact, low-risk: Quick wins build confidence (eg meeting summaries before autonomous decision-making)
Don't just scatter seeds: Be clear on the strategic rationale and introduce structured rollouts with robust "why, what, how"
Introduce with appropriate support
Communicate continuously: What's coming, when, how it helps people (not just the business)
Provide hands-on learning: A quick reference guide and vendor videos won't cut it. Try contextualised 'day in the life' guides, interactive workshops, peer champions
Offer differentiated support: Power users need different guidance than reluctant adopters
Create early champions & proof points
Identify your ‘early bloomers’: People excited to experiment
Document and share wins: Real stories from real colleagues, not corporate messaging
Make it visible: Show AI in action, demystify the magic
Here's the stark reality: for every 100 days of AI implementation, expect 25+ days of training and 100-200 days of change management. That's not overhead. That's the actual work.
Even the best AI tools fail without thoughtful introduction. People need to understand their WIIFM (what's in it for me), have support when they struggle, and see peers succeeding. Build trust and momentum, one product introduction at a time.
Phase 3: Nurture the garden
You can’t just plant seeds, then walk away. Gardens need ongoing care – and so does your AI transformation agenda.
Cultivate new ways of working
Model new behaviours from the top: Help leaders visibly use and trust AI. If they aren’t, ask yourself - do you have a tech adoption challenge, or a leadership tech adoption challenge?
Redesign workflows around AI: Don't just add AI to old processes - rethink the work itself. If teams use AI tools but keep the same structures and processes, you've automated mediocrity
Embed into rituals: Make AI part of how teams meet, decide, and create. Celebrate experimentation.
Enable new collaborations
Human-AI partnerships: Help people understand when and how to act on AI insights
Break down knowledge hoarding: AI can democratise expertise if you let it
Cross-functional pollination: AI often reveals connections between silos - facilitate those conversations
Unlock business value and protect against skills atrophy
Define the time dividend: What will people do with hours saved? Define this proactively
Build critical capabilities: As AI handles routine work, develop the higher-order skills that matter - thinking, motivating, communicating
Defend against skills atrophy: Let note-taking and minor editing fade, but fight to retain security awareness, people management, and critical thinking
Tend to the garden continuously
Feed with feedback: Regularly gather input and adjust
Protect against over-reliance: Watch for AI misuse, over-dependence, or erosion of judgement
Prune what isn't working: Not every AI tool will thrive - be willing to cut losses and make space for something better
AI transformation isn't a ‘one and done’ project with an end date. It's an ongoing practice of growing new capabilities, behaviours and value – and adapting structures, processes and ways of working in parallel. It’s a careful balance – you don’t want your people to rely too heavily on AI and stop exercising core capabilities (as those muscles will atrophy). Equally, it’s crucial to let old ways of working go, which is sometimes the hardest thing to do.
To sustain AI value, fundamentally remodel how your organisation works - and how you tend your garden.
Maintaining a gardener's mindset
You can't force flowers to bloom faster. Adoption takes time. Don’t rush human change – enable it.
Different plants need different care. One-size-fits-all approaches fail. Customise support for different teams, roles, and readiness levels.
The best gardens are ecosystems. AI doesn't work in isolation. It thrives when integrated with culture, process, people, and strategy.
Weather changes fast. AI capabilities are likely to evolve at a pace your organisation can't match. Build adaptive capacity, not just specific skills.
Monitor across all seasons: Track and communicate the garden's yield. There will be setbacks, resistance, and failures. This is normal. Keep tending.
A final thought
Most organisations focus on phase 2 (introducing AI tools) and under-invest in phases 1 and 3.
The real work of AI transformation isn't technical - it's human. It's preparing people to receive change, supporting them through adoption, and nurturing new ways of working as they blossom into even greater opportunities.
Your job as a change leader isn't to deploy AI. It's to cultivate the conditions where AI can flourish and deliver lasting value.
That's the garden worth growing.
References:
Many conversations with cross-industry executives!
Harvard Business Review. (2025, July 29). A guide to building change resilience in the age of AI. https://hbr.org/2025/07/a-guide-to-building-change-resilience-in-the-age-of-ai
MIT Sloan Management Review. (2025, April 9). Why AI demands a new breed of leaders. https://sloanreview.mit.edu/article/why-ai-demands-a-new-breed-of-leaders/
Gartner. (2025, June 30). Survey finds 45% of organizations with high AI maturity keep AI projects operational for at least three years [Press release]. https://www.gartner.com/en/newsroom/press-releases/2025-06-30-gartner-survey-finds-forty-five-percent-of-organizations-with-high-artificial-intelligence-maturity-keep-artificial-intelligence-projects-operational-for-at-least-three-years
Gartner. (2025, September 8). How your CEO is thinking about AI. https://www.gartner.com/en/articles/how-your-ceo-is-thinking-about-ai
Gartner. (2025, September 12). The 2025 Hype Cycle for Artificial Intelligence. https://www.gartner.com/en/articles/hype-cycle-for-artificial-intelligence
Pratt, M. K. (2025, September 15). CIOs set talent strategies for a future-ready IT workforce. CIO. https://www.cio.com/article/4051056/cios-set-talent-strategies-for-a-future-ready-it-workforce.html