The Dual Transformation Mindset
How AI Agents Are Redefining Enterprise Evolution and Revolution
Imagine a shipping company faced with digital disruption. One executive focuses on polishing the existing fleet—installing better navigation systems, optimizing fuel consumption, training crews on new technologies. Meanwhile, another executive is reimagining what a "ship" could be in the digital age—perhaps autonomous vessels, drone-based delivery networks, or entirely new logistics paradigms.
Both executives are responding to the same disruption. Both are "transforming." But they're engaged in fundamentally different activities requiring different mindsets, metrics, and approaches.
This tension between incremental improvement (evolution) and radical reimagining (revolution) lies at the heart of today's AI strategy challenges. As Harvard Business Review recently warned:
"Such incremental progress, while valuable, doesn't prepare companies for the larger waves of AI-driven disruption coming their way."
— HBR, "Is Incrementalism Holding Back Your AI Strategy?", March 2025
The hard truth? Transformation requires a fundamental mindset shift, not just new technology implementation. And nowhere is this more evident than in how enterprises are approaching AI agents—the next frontier beyond basic generative AI applications.
In this article, I'll explore how the dual transformation framework—simultaneously optimizing today's business while reinventing tomorrow's—provides a powerful lens for understanding how AI agents are redefining both business evolution and revolution.
The Incrementalism Trap
Most enterprises default to incrementalism in their AI adoption. They focus on automating existing processes, cutting costs, and making modest improvements to customer experiences. This approach is understandable—it's safer, easier to measure, and aligns with quarterly earnings expectations.
But as HBR notes, many companies are "missing the forest for the trees—focusing only on optimizing current processes and products instead of fundamentally reimagining our business model for the AI age".
This incrementalism trap manifests in several ways:
Automation myopia: Viewing AI primarily as a way to automate existing tasks rather than reimagine what's possible
Risk aversion: Avoiding bold moves due to uncertainty about AI's capabilities or regulatory concerns
Transformation theater: Using "transformation" as a buzzword while continuing business as usual
Capability confusion: Failing to distinguish between what today's AI can do versus what tomorrow's AI agents will enable
Consider Blockbuster's response to digital disruption. They made incremental improvements to their stores and rental processes but failed to reimagine what a video rental business could become in the digital age. Meanwhile, Netflix was busy reinventing the entire concept of entertainment consumption.
Key insight: Today's enterprises face a similar choice with AI agents. Will they merely polish their existing ships, or will they reimagine what sailing means altogether?
The Dual Transformation Framework
The dual transformation framework, highlighted in the recent HBR article, offers a powerful approach to this challenge:
Transformation A: Optimizing & strengthening today's business with AI
"Leverages AI to optimize today's business model—refining processes, reducing costs, and enhancing customer experiences"
Transformation B: Creating entirely new AI-driven business models
"Creates new AI-driven business models that unlock opportunities and redefine markets"
The critical insight is that these transformations must be pursued simultaneously but separately. They require different metrics, timelines, organizational structures, and leadership approaches.
Transformation A operates on familiar terrain with clearer metrics: cost reduction, efficiency gains, customer satisfaction improvements. It's about doing what you already do, but better.
Transformation B ventures into uncharted territory with different success metrics: new revenue streams, market creation, disruptive potential. It's about doing what nobody has done before.
"The two efforts should be separate and structured differently."
— Harvard Business Review
This separation allows each transformation to operate with appropriate expectations, timelines, and success metrics.
The dual transformation approach isn't an either/or choice but a both/and requirement. Companies must strengthen their core while simultaneously building their future.
From Tools to Teammates: The AI Agent Revolution
At the heart of both transformation tracks is a profound shift in how we conceptualize AI: from information-based tools to action-oriented teammates.
McKinsey captures this evolution perfectly:
"We are moving from knowledge-based, gen-AI-powered tools...to gen AI–enabled 'agents' that use foundation models to execute complex, multistep workflows."
— McKinsey, "Why Agents Are the Next Frontier of Generative AI", July 2024
What makes AI agents different?
According to McKinsey's framework, they:
Execute workflows: They don't just provide information; they take actions across multiple systems
Interact with systems: They can access and manipulate enterprise applications, databases, and digital tools
Demonstrate autonomy: They make decisions within defined parameters without constant human oversight
This represents a paradigm shift—AI moving from being tools we use to teammates we collaborate with. And this shift enables both transformation tracks:
For Transformation A (optimizing today), agents can enhance existing processes far beyond simple automation. McKinsey notes they can "reduce review cycle times by 20 to 60 percent". They can handle complex workflows like contract reviews, customer service interactions, and financial analyses with unprecedented speed and accuracy.
For Transformation B (reinventing tomorrow), agents enable entirely new business models and customer experiences. They function as "virtual coworkers able to complete complex workflows", opening possibilities for 24/7 personalized services, dynamic pricing models, predictive maintenance systems, and entirely new product categories.
The Mindset Shift Required
Implementing this dual transformation approach with AI agents requires a fundamental mindset shift at both leadership and organization-wide levels.
As McKinsey observes:
"If deploying AI agents is akin to adding new workers to the team, just like their human team members, agents will require considerable testing, training, and coaching."
This mindset shift manifests in several key areas:
1. Work Process Design
Traditional process design assumes human capabilities and limitations. Agent-ready process design must account for different strengths and limitations:
The mindset shift involves designing processes that leverage the unique capabilities of both humans and agents rather than simply automating existing human-centric processes.
2. Decision Authority Allocation
As agents become more capable, organizations must rethink how decision authority is allocated:
Which decisions should remain fully human?
Which can be delegated to agents with human oversight?
Which can be fully delegated to agents?
This requires moving beyond simplistic "humans vs. machines" thinking to a more nuanced understanding of collaborative decision-making.
3. Success Metrics
Traditional productivity and success metrics often fail to capture the value of human-agent collaboration. New metrics might include:
Quality of human-agent collaboration
Novel solutions generated through collaboration
Speed of adaptation to changing conditions
Value created beyond cost reduction
4. Organizational Structure
As McKinsey's research on "Enterprise Technology's Next Chapter" (December 2024) suggests, organizations will need to evolve toward new structures that support "human and AI teams."
These might include:
Factory model: Standardized, high-volume processes where agents handle routine tasks and humans manage exceptions
Artisan model: Creative, high-judgment domains where agents augment human capabilities with data insights and process support
Critical challenge: The biggest barriers to transformation are mental models, not technological limitations. Leaders must shift from viewing AI as a cost-cutting tool to seeing AI agents as collaborative partners in both optimizing today and reinventing tomorrow.
Transformation as a Mindset, Not a Mode
The dual transformation framework offers a powerful approach to navigating the AI agent revolution. By simultaneously optimizing today's business and reinventing tomorrow's, organizations can avoid both the incrementalism trap and the disruption risk.
But implementing this approach requires more than new technology—it demands a fundamental mindset shift. Leaders must move beyond viewing AI as merely a tool for cost-cutting to seeing AI agents as collaborative partners in both evolution and revolution.
As Marc Benioff has observed, we're moving toward a "digital workforce" where "humans and automated agents work together to achieve customer outcomes".
The organizations that thrive in this new era will be those that can simultaneously polish today while reimagining tomorrow—and that begins with embracing the dual transformation mindset.