Editorial
CEOs are now publicly predicting that AI could replace half of all white-collar workers in finance, automotive and beyond. The big question is what will be left for humans to do when organizations have more digital workers, and how should we be training humans to prepare for these new roles?
Sidebar: The Critical Mindset Shifts
From: "How can AI make my job easier?"
To: "How can the job be done better?"
From: "We've always done it this way."
To: "How do we reinvent how we do it?"
From: "I'm not technical enough."
To: "I can do most things with the right tool."
The Risk of Mediocrity in AI Adoption
While leaders grapple with these workforce questions, a more immediate threat is emerging: the slide toward mediocrity. A company can lose its competitive edge when everyone is using the same models trained on general data to power similar responses and actions.
We see this today when we are using AI to offload email responses, meeting notes, social media content and anything text-based. We’ve become more productive, but less insightful, and we're flooding the system with generic, empty-calories-content that promotes average thinking.
Every forward-thinking organization is offloading tasks to AI. Consumers and readers already recognize that generic ChatGPT tone and tune it out. They are tired of AI-generated images and content that all feel the same. This approach won't keep organizations competitive for long.
Related Article: 3 Work Roles in the AI Era: Innovators, Operators and Translators
Two Paths Forward for AI in Business
This is both a very exciting and dangerous moment for leaders as they figure out where to steer their companies. There are two distinct paths to choose from, each with different outcomes.
Path One: The 'Acceleration First' Trap
The obvious path that many organizations are taking is to focus on AI literacy and encourage employees to accelerate their current tasks, but thinking of AI as only a productivity tool isn’t sufficient to remain competitive. Unlike word processors or calculators, AI is a power tool, amplifying everything equally, including inefficiencies and weaknesses. To gain a competitive edge, generic models need to be trained on proprietary data. Proprietary insights and experience scattered among millions of documents encode a company’s differentiating knowledge base.
At the heart of all great innovations is a great innovative question. A mindset of asking truly new questions will create global business brands and change the world — new questions like: How do I facilitate faster, learn from the best research and create new solutions?
Employees who meet their KPIs faster certainly play a crucial role in any business with customers to serve, but this can lull us into passivity, as motion can mitigate imagination. What’s the forcing function to provoke the question: “While we’re doing this thing better, is it still the right thing to do?”
Even when the acceleration approach seems successful, it creates underlying problems. Workforce anxiety can increase as the duration to complete a task shrinks. Workers can then become disenchanted, their personal and professional purpose seemingly diminished, as most people want their roles to count and be relevant to the organization. We need to enable the workforce to rapidly redefine the scope of their job, as the tasks that comprise it are simplified. Done well, this can be a significant force multiplier. Done poorly, the competitive spirit of an organization can be destroyed as a disengaged workforce stops asking: “Can this be done better?”
History offers stark warnings about this approach. It’s how Blockbuster missed the rise of the internet and lost to Netflix and how Kodak missed the smartphone camera revolution entirely. You can optimize your operations all you want, but when a fundamentally different disruption is looming, optimization and acceleration aren’t enough — you’ve got to remember that the right, new-to-the-world question is often the real innovation.
Path Two: Organizational Reimagination & the AI-First Approach
The second path is one that a few leaders and startups are taking — stepping back and asking hard existential questions regarding their organizational structure and culture. It's not about infusing AI into everything humans do, it's about designing everything we do around AI in the same way business processes were eventually redesigned around the internet. This “AI First” approach releases enormous emotional forces that often repel one another. Fear, loss of relevance and purpose all surface. But in the end, an AI First mindset will lead to highly optimized companies that serve their customers better than those unwilling to reconcile AI’s capabilities with their culture.
”It is critical to have a genuinely inspiring vision of the future [with AI], and not just a plan to fight fires”
Co-Founder and CEO, Anthropic
A better approach is to empower and AI-enrich employees, upgrading their skills and challenging them to take a radical systems-view of how they can do the job anew. We must reimagine workflows and KPIs around innovation.
As Satya Nadella, Chairman and CEO of Microsoft, noted, "This new generation of AI will remove the drudgery of work and unleash creativity." The old adage, “You get what you measure,” applies here too, and the struggle is to create business-impacting AI KPIs that drive change. These KPIs need to be expressed in the language of things the business cares about, e.g., better production planning that reduces inventory impacting cash flow or engineering teams that deliver better products faster.
From the CEO down, reconstructing a company around the banner of radical business change, enabled by AI, requires completely overhauling team structures and retraining employees to develop agency and self-efficacy as innovation drivers.
Why Mindset Matters More Than AI Tools
Most organizations are grabbing AI tools and focusing on prompt engineering. But without systems thinking, you just digitize dysfunction. First, you have to teach your people to see the whole system, then, identify the parts that shouldn’t exist. Only then can you apply technology thoughtfully and create a culture where innovation is expected.
Three frames provide three different lenses for looking at systems, while enabling each employee to bring their unique perspective and expertise to help innovate:
- Map
- Spot
- Upgrade
1. Map Your Real Value
The first frame enables your employees to step back and view the big picture through different templates — like looking at the world through a series of stencils, where each cutout pattern reveals certain possibilities while concealing others. Guide them to ask questions like: which products or services are most distinct, which are most profitable and which customers are most satisfied.
From there, have your teams determine which organizational activities are most differentiated and effective, listing significant activities and grouping them under Porter’s categories. Examples include inbound, operations, marketing and sales and so on. Then, for each activity they should:
- Ask can it be done more efficiently (cost focus)
- Ask can it be made more valuable to customers (differentiation focus)
- Analyze data exhausts for new insights
- Score on data richness and AI-leverage potential (1-5)
- Highlight two bottlenecks where AI could cut costs and raise differentiation
Once your teams have done these steps, they can benchmark against competitors to spot gaps. LLMs are particularly effective in this step. Look for linkages or changes in one activity that ripple into others (e.g., better forecasting cuts both inbound inventory and outbound stock-outs). Finally, prioritize initiatives that strengthen multiple links and fit your firm’s strategic position.
2. Spot Innovation Opportunities Everywhere
Once your organization develops an understanding of the systems-level view of the organization, the second frame helps your teams figure out what type of innovation to develop.
David H. Cropley, in his book "Creativity in Engineering," outlined four types of innovation to consider:
- Product (tools, devices)
- Process (a production line, a procedure)
- System (an aircraft, a communication system)
- Service (bank accounts, home delivery)
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Using this framework, your teams can go back to the systems level map to see where the next innovation will come from.
3. Upgrade Tensions Into Breakthroughs
Every breakthrough innovation starts with a tension — a trade-off everyone accepts as inevitable. "Quality costs more." "Convenience reduces choice." "Technology is complicated." But these tensions aren't laws of physics and can be broken with new technologies and ways of thinking.
The Innovation Tension Framework
Step 1: Identify the Tension
Guide your teams to ask: What trade-off are we accepting as inevitable?
Some examples of such are: "We can't be both fast AND thorough" or "Quality increases cost" or "Personalization doesn't scale."
Step 2: Choose Your Innovation Strategy
Train your teams to select from five proven approaches from TRIZ — the Theory of Inventive Problem Solving:
- Optimize → When the current approach is sound but needs refinement. Toyota faced the tension of automation eliminating human value. Through jidoka — automation with a human touch — they empowered workers to stop any machine when detecting problems, making humans the quality controllers rather than machine watchers. As a result, defects dropped from 1 in 100 to 1 in 1 million while creating a culture where human wisdom and technology amplify each other.
- Simplify → When complexity is the enemy. Apple's iPhone challenged "more features mean better phones." While competitors added physical keyboards, styluses and removable batteries, Apple eliminated them all for a single touchscreen. And as a result the iPhone redefined the entire mobile industry, making Apple one of the world's most valuable companies.
- Repurpose → When existing solutions can solve new problems. Nintendo’s competitors built "ferocious dinosaurs," high-performance consoles priced at $450 and above. Nintendo took a radically different approach. They aimed for a $100 price point with consoles that "moms would approve of." Their breakthrough came from repurposing existing MEMS motion sensors that were already used in automotive and industrial applications. The problem was that these sensors contained moving parts requiring bulky, expensive protective packages — making them impractical for game controllers. Analog Devices, which supplied the Wii Remote's sensor, found an elegant solution: they capped the sensor elements directly at the wafer level during manufacturing. This created an effective seal and the device could be protected with a cheap, small, lightweight case. The Wii outsold both the PlayStation 3 and Xbox 360 despite not having HD graphics.
- Combine → When integration creates new value. Amazon started as a bookselling platform and continuously layered new value into Prime — first adding free shipping, then streaming video, music, grocery delivery and prescription medicines. Each addition reinforced the ecosystem rather than diluting it. As a result, prime members spend $1,400 annually vs. $600 for non-members, with 200 million members locked into their ever-expanding ecosystem.
- Reinvent → When incremental change isn't enough. Netflix challenged the belief that physical media was essential in the age of the internet. They abandoned their profitable DVD business to bet everything on streaming. Their revenue grew to $33.7 billion, fundamentally changing global entertainment. Similarly, Microsoft shifted from selling software licenses to cloud subscriptions — now 98.5% of their systems run on Azure, opening a $4.5 trillion market opportunity.
These innovation exercises can be done through hackathon or ideation workshops and sprints on a regular basis, but your real challenge as a leader is to build a culture of self-efficacy, agency and lifelong learning. This is critical in a time when the tools and workspace are changing rapidly and in unexpected ways.
LLMs at the moment can only remix what is on the internet, the majority of content representing mediocre thinking. Innovation and creativity are still areas that your people can own and drive, if you optimize your culture for that. And the very first building block for that is agency and a mindset of lifelong learning and self-efficacy, giving your team the confidence that they can do this.
Related Article: Building the Skills to Succeed as an AI-Augmented Worker
The 4 Es Framework for Innovation Confidence
Based on Bandura's social cognitive psychology, confidence in innovation grows through four channels that you as a leader can activate.
- Exposure builds capability through vicarious modeling — when employees see peers or leaders successfully learning AI skills, it signals the task is achievable and lowers psychological barriers.
- Experience creates the strongest confidence through scaffolded personal victories, starting with easy wins and gradually increasing complexity (within the zone of proximal development) like a well-designed video game.
- Expectations leverage social persuasion through concrete mechanisms: team hackathons, reverse mentoring (pairing AI-savvy juniors with senior leaders), innovation showcases on Slack and rotating "AI Champions Councils" where volunteers coach peers and curate resources.
- Energy recognizes that physical and emotional states directly impact creativity. Employees need supportive environments with appropriate autonomy, feedback and stress management to sustain innovation.
Together, these 4 Es transform how employees think and behave with AI, directly affecting their creative output.
Launching a 2-Hour Weekly Innovation Pilot
You read the articles about how AI is changing the landscape. You have read “The Innovator's Dilemma: When New Technologies Cause Great Firms to Fail.” But completely reimagining your organization feels impossible when you are already so tired.
The uncomfortable truth is that the world continues to turn and disruption will happen. But here is the good news: You can catch up with just 2 hours per week. This isn't another consultant-heavy transformation program. It's a lightweight pilot that proves your organization can make the mindset shifts necessary to survive.
The commitment is simple: 36 hours over 18 weeks.
Let volunteers self-select. Have them identify two meetings each week where they don't contribute much and swap those for Friday afternoon innovation sessions. After each session, participants share their discoveries and ideas on Slack, creating a ripple effect that pulls insights from the broader organization and builds momentum.
With this approach there's no failure scenario. Even in the worst-case outcome - employees will gain systems-thinking capabilities and successfully integrate AI into several workflows. This will put you ahead of your competition. In the best case you've built an innovation engine that compounds week after week.
The 18-Week Sprint to AI-Driven Reimagination
| Map (Weeks 1-3) | Spot (Weeks 4-6) | Upgrade (Weeks 7-12) | Empower (Weeks 13-18) |
|---|---|---|---|
| Understand Current State | Identify Challenges | Build Solutions | Scale & Sustain |
| Value chain analysis | Problem identification workshops | 5-mode improvement analysis | Showcase & reflect, demo days |
| Data streams assessment | User research & journey mapping | Rapid prototyping sprints | Mentorship program launch |
| Stakeholder engagement | Gap analysis | AI/tech integration | Institutionalize Build-Measure-Learn Loops |
| Innovation-type scoping analysis | Competitor analysis | User testing & iteration | Continuous learning Culture |
The real question isn't "How many jobs will AI replace?" It's "What will make your company irreplaceable?"
Right now, you're likely doing everything "right" — using AI to optimize operations, accelerate workflows, meet quarterly targets. But that's how great companies fail. They perfect what they do today while missing what they could become tomorrow.
Every day you use AI to do the same things faster, you're perfecting yesterday's business model. The disruption won’t come from competitors with better AI — it will come from those asking better questions.
The innovator's dilemma is real. The solution is simple: Stop innovating on what you do. Start innovating on what you could become. Start this Friday.
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