Across my conversations with revenue operations, marketing operations, strategy, planning, and transformation leaders, I hear the same challenge: “We’re struggling to run today’s business while preparing for tomorrow’s.” It comes up in conversations about AI, buying groups, process optimization, organizational change, and nearly every major transformation initiative. But the premise behind the question is flawed.

Running the business and transforming the business are not competing priorities. Transformation should change how the business runs. The organizations that make progress on both build operating models that make operational work visible, establish clear ownership and decision rights, and create the capacity and discipline to change.

Stop Treating Transformation As Extra Work

Every organization must manage two realities:

  1. It must keep the business moving. Forecasting, revenue planning, data strategy, tech consolidation, analytics interpretation, and process governance are the operational backbone of revenue generation and customer engagement.
  2. At the same time, it must invest in what comes next: AI, agentic workflows, data modernization, decision intelligence, and other impactful transformations.

The problem starts when organizations treat the second category as work to be layered onto the first. Transformation becomes additional work for teams already consumed by operational demands: Priorities compete; ownership blurs; and initiatives stall. New technology can add complexity rather than remove it.

Clarify Ownership Before Adding Capacity

The first question shouldn’t be, “Do we have enough people?” It should rather be centered around, “Who owns what?” Start specifically with four questions:

  1. What work is required to run the business?
  2. What work is required to transform it?
  3. Who owns each type of work?
  4. Who has the authority to make decisions?

These questions sound simple, but answering them often isn’t. Operations, analytics, technology, planning, transformation, and AI capabilities increasingly converge around the same initiatives. Several functions and subfunctions may own pieces of the work while no one owns the outcome.

When no one owns the outcome, decisions are slower, priorities are fragmented, and accountability is fuzzy. That is why decision rights matter as much as responsibilities. Teams need to know not only who does the work but who decides what gets prioritized, standardized, automated, funded, scaled, or stopped.

AI Makes Weak Operating Models More Visible

AI raises the stakes. What starts as a technology conversation quickly becomes a conversation about data quality, governance, process ownership, prioritization, and cross-functional coordination. You can’t scale what you haven’t standardized. Fragmented processes don’t become coherent simply because AI is applied to them. Inconsistent workflows remain inconsistent, ambiguous ownership remains ambiguous, and automation can make those weaknesses move faster.

So before asking, “Where can we deploy AI?” instead ask: “What needs to be standardized before we automate?” Using AI for process optimization, insights generation, and cross-functional coordination changes AI from a technology deployment exercise into a discussion about how the business works.

Standardize To Scale

Leveraging AI as the foundation for a new way of running the business ultimately requires a shift in mindset. Transformation isn’t something an organization does in addition to running the business. The ability to transform should become part of how the organization runs. That means making operational responsibilities visible: giving transformation clear ownership, establishing decision rights, standardizing what should scale, and using planning to continually reallocate capacity from work that matters less to work that matters more.

The question, then, isn’t, “How do we balance running the business with transforming the business?” Instead, it is, “How do we build the mechanisms that allow change to happen without destabilizing the business?” Organizations that answer that question create something more durable than another transformation program.

Build An Operating Model For Continuous Change

Operations leaders have an important role to play because they sit at the intersection of strategy and execution, technology and process, and data and decisions. Five actions can help operations accomplish their mission:

  1. Make operational work visible. Recurring activities, ad hoc requests, reporting, governance, and support consume real capacity. Leaders need visibility into that work before they can make informed choices about where to invest or what to change.
  2. Give transformation explicit ownership. Transformation cannot survive indefinitely as side-of-desk work. Initiatives need clear accountability, governance, decision rights, and outcomes.
  3. Standardize before you automate. Identify unnecessary variation in processes, definitions, workflows, and decision-making before applying AI or automation. Technology should scale intentional ways of working, not accidental complexity.
  4. Treat decision-making as a capability. Operations isn’t only about delivering data. Its value increasingly comes from helping leaders make better decisions by connecting planning, governance, performance management, customer insight, and AI-driven intelligence.
  5. Use planning to drive transformation. Planning shouldn’t simply allocate resources to an existing list of activities. Use it to decide what should be simplified, automated, scaled, redesigned, or stopped.

Next Steps

Balancing the work required to run the business with the work required to transform it starts with the operating model. Leaders need to make operational work visible, clarify ownership and decision rights, and determine what must be standardized before introducing AI and automation at scale.

Our report, The AI Revenue Operations Leader, explores how revenue operations leaders can evolve their role as AI changes how work gets done and decisions get made. Forrester clients can use the report to consider the capabilities, governance, and operating model changes required to lead in an AI-enabled environment.

Join us at a Forrester B2B Summit to continue the conversation about how AI is reshaping operations, decisions, and go-to-market execution, as well as what leaders should standardize, redesign, and transform next.

Engage with Forrester analysts to discuss how to design an operating model that enables both operational excellence and transformation, clarify ownership and decision rights, determine what to standardize before automating, and use planning to create capacity for continuous change.

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