Core Skills vs. Surface Skills Analysis
From the ICLA-Accenture Workshop (November 5, 2025)
Workshop Date: November 5, 2025
Facilitators:
John Ricketts, ICLA
Chris Lowndes, Industry X Lead APAC, Accenture
Analysis Focus: Distinguishing core competencies from surface skills
THE FIRE ANALOGY: Just as humans didn't compete with fire but learned to use it, we don't compete with AI—we work symbiotically with it.
THE FUNDAMENTAL DISTINCTION:
- Surface Skills = How you do things (the tools, the techniques)
- Core Skills = Why you do things and what value you create (the judgment, the purpose)
10 Core Skills (Transcend Technology)
1. Value Recognition & Articulation
"We have to work on how we deliver value. In every situation we are in, we work out how do we deliver value."
What it means:
- Ability to identify what creates genuine value
- Distinguishing between value creation and mere activity
- Understanding the difference between "people who understand value" vs "people who only measure value"
- Constantly asking: "How am I delivering value?"
Why it's core:
- This skill operates above any specific technology
- It guides all decisions and actions
- Can't be automated—requires human judgment
2. Strategic & Contextual Thinking
"Humans decide what the relationships are when setting up systems."
What it means:
- Understanding context and purpose
- Thinking 10 years forward, not just 1 year
- Seeing systems and relationships, not just components
- Determining where and how AI should be deployed
Why it's core:
- AI can optimize but can't set the optimization criteria
- Humans determine the "what" and "why"
- Requires big-picture vision
3. Critical Judgment & Quality Assessment
"Humans decide whether the quality of answers reaches their requirements."
What it means:
- Evaluating AI outputs for quality and appropriateness
- Understanding limitations and capabilities
- Knowing when to trust AI and when to override it
- Assessing risk and safety implications
Why it's core:
- AI can produce outputs but can't judge if they're "good enough"
- Requires domain expertise and contextual understanding
- Essential for responsible AI deployment
4. Adaptive Learning Mindset
"Embrace lifetime learning—your surface skills will change frequently."
What it means:
- Ability to learn new tools and techniques rapidly
- Comfort with constant change and uncertainty
- Meta-learning: learning how to learn
- Intellectual curiosity and openness
Why it's core:
- The specific tools will change every 2-3 years
- The ability to adapt transcends any specific skill
- Foundation for continuous value creation
5. Functional AI Literacy
"An understanding—not technical, but from a functional and social point of view of AI."
What it means:
- Understanding what AI can and cannot do
- Knowing capabilities and limitations
- Understanding safety and responsibility issues
- Conceptual grasp, not technical implementation
Why it's core:
- Enables informed decision-making about AI deployment
- Allows you to work symbiotically with AI
- Helps you identify where human judgment is essential
6. Creative & Innovative Thinking
"They see innovation as a way of keeping ahead of competitors."
What it means:
- Generating novel solutions and approaches
- Challenging assumptions and status quo
- Seeing possibilities that don't yet exist
- Thinking beyond optimization of existing processes
Why it's core:
- AI excels at optimization, not true innovation
- Humans envision what should be created
- Essential for breakthrough thinking
7. Change Leadership & Influence
"The number one problem is you will be surrounded by people who like the idea of change but don't actually want to change."
What it means:
- Ability to lead organizational transformation
- Navigating resistance and fear
- Communicating value to different stakeholders
- Having different conversations with people who understand value vs. those who only measure it
Why it's core:
- Technology alone doesn't create change
- Human systems and culture are the bottleneck
- Requires empathy, persuasion, and political savvy
8. Ethical & Social Awareness
"We feel it's important to turn up the volume on well-being and have well-being really central."
What it means:
- Considering human and societal impact
- Balancing efficiency with well-being
- Understanding the "golden age" vs "dark scenario" choices
- Responsible deployment of technology
Why it's core:
- AI doesn't have values or ethics
- Humans must guide technology toward beneficial outcomes
- Essential for preventing dystopian scenarios
9. Problem Evolution & Improvement Vision
"Humans decide where and how things can be improved. The agentic system is specialized in fixing problems, not in evolving itself."
What it means:
- Identifying what problems need solving
- Envisioning better futures and outcomes
- Evolution vs. optimization thinking
- Seeing opportunities AI can't recognize
Why it's core:
- AI fixes known problems but doesn't evolve itself
- Humans determine what "better" means
- Vision requires human imagination
10. Symbiotic Technology Relationship
"If you have a good enough core skill, you get into a symbiotic relationship with the technology rather than an adversarial relationship."
What it means:
- Viewing AI as amplifier, not competitor
- Knowing when to use AI and when to rely on human judgment
- Collaboration rather than competition mindset
- Seeing how AI enhances rather than replaces your value
Why it's core:
- Determines your entire relationship with technology
- Foundation for thriving rather than fearing AI
- Multiplies your effectiveness
Surface Skills (Tool-Specific, Change Frequently)
1. Specific AI Tools & Platforms
Examples: ChatGPT, Claude, Midjourney (current tools), specific LLM interfaces, proprietary AI platforms, today's coding assistants
Why it's surface: These tools will be replaced by better versions. The specific interface changes constantly. What matters is understanding what they can do, not how to use this specific version.
2. Technical Implementation Details
Examples: Specific programming languages (Python 3.11 vs 3.12), framework-specific knowledge (React vs Vue), current API structures, specific libraries and dependencies
Why it's surface: These change every few years. AI can handle much of this implementation. The "how" of coding vs the "what" and "why".
3. Current Best Practices
Examples: Today's prompt engineering techniques, current UI/UX patterns, specific workflow methodologies, tool-specific optimization tricks
Why it's surface: Best practices evolve rapidly. AI handles more of this over time. The tactics change even when strategy remains constant.
4. Specific Industry Tools
Examples: Current design software (Figma today, something else tomorrow), project management platforms (Asana, Monday, etc.), communication tools (Slack, Teams, etc.), industry-specific software packages
Why it's surface: Tools consolidate, disappear, get replaced. Features migrate between platforms. The communication/collaboration skill matters, not the tool.
5. Procedural & Routine Tasks
Examples: Data entry and formatting, basic report generation, routine calculations, standard document creation
Why it's surface: AI increasingly handles these. Low-value tasks that get automated first. Being good at these doesn't create future value.
The Critical Relationships
The Multiplication Effect:
Strong Core Skills + AI = 10x Value Creation
Weak Core Skills + AI = Replaced by AI
The Time Horizon:
Surface Skills: 2-3 year relevance cycle
Core Skills: 10-20+ year relevance (potentially lifetime)
The Investment Strategy:
Time spent developing core skills = compound returns
Time spent only on surface skills = constant retraining treadmill
Accenture's Strategic Insight: "AI Won't Lead, But Your People Will"
This slogan captures the essence:
What AI Does:
- Executes tasks
- Optimizes processes
- Fixes known problems
- Generates outputs
What Humans Do:
- Set objectives
- Define relationships
- Judge quality
- Envision improvements
- Make ethical choices
- Create new value
The Two Paths Forward
Golden Age Scenario
- Humans focus on high-value work
- AI handles tedious tasks
- Same pay for fewer hours
- Focus on well-being and quality of life
- Symbiotic human-AI collaboration
Enabled by: Strong core skills across the workforce
Dark Scenario
- Extreme capital concentration
- Massive unemployment
- Race to bottom on labor costs
- Optimization for profit over people
- Humans compete with AI and lose
Result of: Workforce with only surface skills
Action Framework
Immediate (This Week)
- Identify your core skills—what transcends tools?
- Start using AI tools—build familiarity
- Reflect: "How do I currently deliver value?"
Short-term (This Semester)
- Develop functional AI literacy
- Build symbiotic relationship with AI
- Position for value creation, not just management
Ongoing (Career)
- Embrace lifetime learning
- Constantly ask: "How am I delivering value?"
- Think 10 years forward
- Deepen core skills—they're your foundation
Self-Assessment Questions
Testing if something is a Core Skill:
- Will this be valuable in 10 years regardless of technology changes?
- Can AI do this, or does it require human judgment?
- Does this help me create value or just complete tasks?
- Would this skill transfer across different tools/platforms?
- Does this require understanding "why" not just "how"?
If yes to most → Core Skill (invest heavily)
If no to most → Surface Skill (learn efficiently, don't over-invest)
The Real Challenge
"The number one problem is you will be surrounded by people who like the idea of change but don't actually want to change."
The ultimate core skill might be:
- Embracing actual change, not just the idea of change
- Being willing to continuously evolve
- Having the courage to let go of surface skills that become obsolete
- Focusing relentlessly on creating value, not protecting territory
The Bottom Line
"We have to work on how we deliver value. In every situation we are in, we work out how do we deliver value, and if we keep on doing that, we'll be okay."
— John Ricketts
"If you know what AI is capable of, what its limitations are, the safety, the responsibility, and you could think through a problem... you're a very useful member of the future workforce."
— Chris Lowndes
This is the core skill that encompasses all others:
The relentless focus on understanding and delivering value.
Everything else—tools, techniques, technologies—are just means to that end.
Workshop Analysis
ICLA-Accenture Workshop on Value Creation in the AI Era
November 5, 2025