Rebuild on AI Principles: From Tools to Transformation

In today’s AI wave, it’s no longer sufficient to ask “Which tools is our firm using?” The real test: what if we reimagined entire functions—backwards from outcomes—on AI-first principles?

"Rather than asking which AI tools the company is currently using, the board should ask: What if we rebuilt this function entirely on AI principles? How much faster, leaner, and more predictive could it be?"

— BCG, Targets Over Tools: The Mandate for AI Transformation, Dec 2025

As articulated in BCG’s December 2025 piece “Targets Over Tools: The Mandate for AI Transformation”, this zero-based mindset may unlock productivity, speed, and predictive capabilities far beyond incremental tool adoption.

Shift from tools to transformative vision

Traditional digital efforts often kick off with pilot programs, focused experiments, and tool roll-outs. BCG warns that this incremental path, while tempting, rarely delivers lasting impact. The real transformation begins by envisioning what a "perfect" version of a function would look like: one built from the ground up, free from legacy constraints. From there, management designs backward—identifying which data, capabilities, and architectures are required to achieve those outcomes. (Targets Over Tools: The Mandate for AI Transformation)

Boards must lead the ambition

Boards can't remain passive. Transformation becomes a central performance agenda when directors ask bold, outcome-driven questions. By treating AI initiatives like financial targets—embedding metrics into P&L, mapping quarterly milestones, pushing for measurable productivity and time-to-market gains—they elevate oversight from checklists to strategic value drivers. Systems of governance, risk, and monitoring must be reworked accordingly. (Targets Over Tools: The Mandate for AI Transformation)

Redesign work, workforce, trust

Rebuilding functions on AI principles demands rethinking work itself. Legacy processes—often manual, siloed, and reactive—must be redesigned. Roles shift; reskilling becomes essential. And, perhaps most critically, trust becomes the foundation: trust in data, in AI systems, and in transparent governance. Boards and executives must champion literacy in AI—all the way to empowering employees to understand both its potential and its pitfalls. (Targets Over Tools: The Mandate for AI Transformation)

Real-world examples of AI-first transformation

Consider how leading organizations are already applying this mindset:

Financial Services: Risk assessment functions rebuilt around predictive AI models can forecast market volatility with 90% accuracy, compared to 60% for traditional models. The result? Portfolio optimization that was previously impossible.

Manufacturing: Quality control processes redesigned with computer vision and anomaly detection can identify defects before they occur, reducing waste by 40% while maintaining production speeds.

Healthcare: Diagnostic workflows rebuilt with multimodal AI can process patient data from multiple sources simultaneously, enabling earlier interventions and personalized treatment plans.

The leadership imperative

This transformation requires a new breed of leadership. Executives must become "AI orchestrators" who understand not just the technology, but how to architect entire business ecosystems around AI capabilities. They need to:

• Master the art of AI orchestration: Understanding how different AI models and agents work together
• Design for continuous evolution: Building systems that can adapt as AI capabilities advance
• Balance human and machine intelligence: Creating the right mix of algorithmic precision and human judgment

Measuring transformation success

Success metrics must evolve beyond traditional KPIs. BCG recommends tracking:

• Predictive accuracy improvements: How much better are AI-driven forecasts?
• Process cycle time reductions: How much faster are end-to-end workflows?
• Quality and compliance metrics: How have error rates and regulatory adherence improved?
• Innovation velocity: How quickly can new capabilities be deployed?

Conclusion

By daring to consider what functions rebuilt entirely on AI might look like, organizations position themselves to leap ahead, not simply keep up. The inquiry shouldn't be around existing toolsets—but around the vision of AI as the core engine of transformation. Boards that start there will lead the race, creating organizations that don't just use AI, but are fundamentally transformed by it.

Source

BCG. (2025, December). Targets Over Tools: The Mandate for AI Transformation. Read the full report