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A Practical Executive Language for Run and Change Trade-offs in Banking

How to validate strategic ambition when AI becomes part of the operating core in 2026

InformationFebruary 2026
Reviewed by
Ahmed AbbasAhmed Abbas

Why RTB versus CTB is no longer a finance shorthand

Run The Bank and Change The Bank has long served as a useful shortcut for budget discussions, but it often obscures the real executive question: which capabilities must be stabilized and industrialized, and which must be accelerated to protect competitiveness. In 2026, that question becomes harder because AI is moving from experimental change programs into foundational run operations. As a result, RTB and CTB are increasingly entangled across the same platforms, data, and controls.

This is where trade-off language matters. Without a shared vocabulary, leadership teams default to debates about percentage splits and project counts rather than decision risk, regulatory constraints, and operational resilience. A disciplined framing makes it possible to test whether strategic ambitions are realistic given current digital capabilities and to prioritize the right work in the right sequence.

Core definitions with decision intent

Run The Bank

Run The Bank focuses on operational continuity, service reliability, control execution, and regulatory compliance. It is measured by uptime, stability, controllability, unit cost, and the ability to operate within policy without accumulating exceptions. The executive lens is risk containment: RTB is the capacity that keeps customer impact, losses, and supervisory findings within tolerance.

Change The Bank

Change The Bank focuses on transformation, new product delivery, modernization, and strategic differentiation. It is measured by delivery throughput, time to value, adoption, and growth impact. The executive lens is managed optionality: CTB is the capacity that creates future earnings and reduces structural constraints, including technical debt, platform bottlenecks, and data limitations.

What the labels miss

Both RTB and CTB contain risk and both create value. RTB can be strategic when it removes recurring operational drag through automation and control modernization. CTB can be defensive when it is required to sustain resilience and compliance. Executive trade-offs improve when leaders stop treating RTB and CTB as categories of spending and instead treat them as categories of outcomes and constraints.

The 2026 balancing strategy is a unified operating model

Leading institutions are shifting away from managing RTB and CTB as separate silos and toward a single operating model with differentiated pathways. In practice, this means a shared engineering platform, shared control standards, and a portfolio view of change risk, while still preserving clarity on what must not break. The strategic implication is that prioritization becomes a sequencing problem rather than a binary choice between stability and innovation.

Budget ratios as signals not targets

Many banks still reference a historical 50 50 aspiration and a more common 70 30 baseline. In 2025 and 2026 discussions, leadership teams increasingly question whether an underfunded change agenda creates strategic vulnerability, especially when competitors are modernizing customer experience and industrializing AI. The useful move is to treat ratios as diagnostic signals that prompt deeper questions about bottlenecks, control capacity, and delivery constraints rather than as a universal benchmark.

Incremental modernization to reduce structural drag

Rather than high-risk rip and replace programs, banks are leaning toward hybrid modernization approaches that lower operational risk while steadily reducing technical debt and legacy complexity. The trade-off is explicit: incremental paths may take longer to fully simplify the estate, but they can preserve stability and control credibility during the transition. This approach becomes especially valuable where regulatory commitments and operational resilience expectations limit the appetite for disruptive cutovers.

AI is bridging RTB and CTB

AI is increasingly used inside RTB functions such as fraud detection, monitoring, and compliance automation, while also supporting CTB initiatives such as personalization and accelerated software delivery. This blurs traditional boundaries and makes governance more important, not less. The key executive distinction becomes where AI is used as an operator in controlled run processes versus where it is used as an accelerator for experimentation and new value propositions.

Trade-off and prioritization language executives can use

The point of shared language is to make trade-offs explicit, testable, and defensible under scrutiny. The most effective leadership teams use framing that connects investment decisions to constraints and risks that supervisors, boards, and customers care about.

Use four decision frames that travel well across functions

  • Capacity frame What scarce capacity is limiting outcomes engineering throughput, control testing, data readiness, or change enablement
  • Constraint frame Which constraints are binding regulatory commitments, resilience obligations, third-party dependencies, or architecture bottlenecks
  • Risk position frame Which risks increase if we accelerate customer harm, loss events, audit issues, or operational fragility
  • Option value frame Which investments unlock future moves platform modularity, data foundations, or reusable control automation

Translate RTB CTB into portfolio questions

  • Which run activities are truly non-discretionary, and which are symptoms of structural issues we can eliminate
  • Which change initiatives reduce future run cost and risk rather than adding new complexity
  • Where does accelerating change create a control capacity problem, and what must be industrialized first
  • What work increases dependency risk, model risk, or resilience exposure and therefore needs stricter pathways

Define success as paired outcomes

Executives can reduce unproductive RTB versus CTB debates by requiring paired metrics that keep stability and progress in view at the same time. Examples include release frequency paired with change failure rate, automation coverage paired with exception aging, and innovation throughput paired with operational incident trends. Paired outcomes prevent one agenda from crowding out the other while keeping decision risk visible.

Best practices that make the trade-offs governable

Adopt a product management mindset

Organizing around customer value streams helps connect run stability and change delivery to the same business outcomes. This reduces the risk that CTB becomes a disconnected set of projects and that RTB becomes a permanent tax. Product operating models also create a clearer home for platform investments that reduce friction and improve control consistency across the portfolio.

Manage in dual forums with linked decisions

Many leadership teams use two agendas and two scorecards to preserve focus, but they link the decisions explicitly. Run forums prioritize resilience, control health, and service performance. Change forums prioritize sequencing, adoption, and strategic impact. The connection point is capacity and constraint management so that change plans do not assume run capacity that does not exist and run remediation does not indefinitely defer strategically required modernization.

Use partnerships to buy time not to outsource accountability

Fintech partnerships and third-party capabilities can accelerate CTB outcomes, but they can also increase operational and compliance complexity if oversight is weak. The executive trade-off language should focus on where external solutions reduce time to value while maintaining a clear accountability model for controls, resilience, data, and customer outcomes.

Run resilience simulations against the change agenda

Stress testing the operating model against aggressive change plans helps surface whether governance and architecture can absorb delivery speed without eroding stability. This is particularly important when AI capabilities introduce new failure modes and when modernization increases dependency chains. Simulations turn abstract trade-offs into observable impacts and create a defensible basis for pacing decisions.

Validating ambition and prioritizing with digital maturity evidence

Capability-based assessment is a practical way to convert RTB and CTB debates into decision-grade trade-offs. Executives can benchmark whether control automation, platform standardization, data foundations, delivery discipline, and operational resilience are strong enough to support the stated change agenda without creating hidden fragility. The same lens also clarifies where run cost is structural and therefore best addressed through targeted modernization rather than ongoing remediation.

Sequencing decisions improve when assessment dimensions are mapped directly to the trade-off language used by leadership teams, including capacity bottlenecks, constraint removal, risk position, and option value. Within that framing, the DUNNIXER Digital Maturity Assessment supports decision confidence by showing where strategic ambition is misaligned with current capabilities, where investments will reduce both run cost and control risk, and where accelerating change would require tighter pathways, stronger evidence, or additional operating model reinforcement. DUNNIXER can then be used as a governance input to maintain consistency in prioritization as conditions shift across the year.

Reviewed by

Ahmed Abbas
Ahmed Abbas

The Founder & CEO of DUNNIXER and a former IBM Executive Architect with 26+ years in IT strategy and solution architecture. He has led architecture teams across the Middle East & Africa and globally, and also served as a Strategy Director (contract) at EY-Parthenon. Ahmed is an inventor with multiple US patents and an IBM-published author, and he works with CIOs, CDOs, CTOs, and Heads of Digital to replace conflicting transformation narratives with an evidence-based digital maturity baseline, peer benchmark, and prioritized 12–18 month roadmap—delivered consulting-led and platform-powered for repeatability and speed to decision, including an executive/board-ready readout. He writes about digital maturity, benchmarking, application portfolio rationalization, and how leaders prioritize digital and AI investments.

References

A Practical Executive Language for Run and Change Trade-offs in Banking | DUNNIXER | DUNNIXER