The Pivot: From Tools to Resource Allocation

For the past few years, executives have asked a very simple question about Artificial Intelligence: "Where can we use it?" 

This question is natural, but it is also superficial. It has triggered thousands of pilots, new software tools, and productivity experiments across every department. But a much more difficult, and far more important, question is now taking its place: "Where will AI actually create true value for the enterprise, and who is responsible for capturing it?" 

Two recent events show us why this question is becoming the central challenge for leadership. First, new research from the Boston Consulting Group (BCG) shows that AI is changing where profits are made across entire industries. Second, the global consultancy firm EY is building an internal "AI Value Realization Office" to oversee its investments and ensure they turn into real, measurable business outcomes.

Together, these developments tell us that the first phase of AI is over. The next phase is not about adoption; it is about allocation.

By allocation, we mean three things:

• Allocation of capital (money)

• Allocation of organisational capacity (work)

• Allocation of leadership attention (time)
  

Ultimately, leadership must decide where the future of the organisation lies.

1. The Anatomy of Industry Profits

The BCG research, published on 13 August, starts with a fundamental truth: the economic rewards of a new technology are never distributed evenly.

With AI, some industries will see their total profit grow. Others will see it shrink. Within a single industry, profits will shift away from old giants and move toward new startups, suppliers, or entirely new types of businesses. This shifts the leader's job completely.

Most companies still focus only on use cases. They ask:

• Where can we automate?

• Where can we raise productivity?

• Where can we improve customer service?
  

These are operational questions. They are about doing what you already do, just slightly better. The true strategic question is different: Does AI change which parts of our business are worth being in at all? 

BCG warns that new, AI-native competitors will not try to steal your entire business. Instead, they will target your highest-margin products, the parts where you make the most money. They will leave you with the low-value, high-cost activities.

Therefore, strategy leaders must ask new questions:

• Where is AI moving the money in our industry?

• Which of our current advantages will AI make stronger?

• Which advantages will become easy for rivals to copy?

• Which parts of our company deserve more funding, and which will be worthless in five years?
  

AI is not just a new tool to add to your existing plan. It changes the foundational assumptions your plan was built on. 

2. The Friction of Modern Structure

Even if a leadership team figures out where the money is moving, they face a structural obstacle. Organisations are built to manage functions, not value. 

Companies are divided vertically. Departments have budgets. Business units have profit targets. IT teams have technology plans. But AI does not care about your department boundaries.

The consulting firm EY-Parthenon estimates that 70% to 75% of AI’s potential value lies in the spaces between departments, rather than inside them.

[ Marketing ]  -->  ( AI Value Opportunity ) <--  [ Sales ]

    |                                                |
    +-----> [ Unowned Customer Experience ] <--------+

Consider a simple goal: improving the customer journey. This task touches marketing, sales, customer service, operations, finance, and IT. Each department can optimise its own small piece. But usually, no single person owns the performance of the whole chain.

This is a critical distinction. You can have brilliant AI projects inside individual departments while failing completely to improve the company as a whole. EY calls this "optimising locally" while the overall business remains slow and friction-filled.

The result is a strange paradox: more AI activity, but no increase in total enterprise value. 

3. The Control Tower: Who Owns the Results?

To solve this, EY is trying an internal experiment. It has created an AI Value Realization Office to watch over AI spending, track how tools are used, measure returns, and decide which projects deserve to grow.

The underlying concept is an enterprise "control tower" with executive authority. This tower has the power to move resources and money across departmental lines.

EY’s internal experiment matters because it forces us to answer a vital question: Who owns the value? 

These are not technical decisions. They are portfolio decisions. They are choices about how to deploy the company's scarce resources.

4. The New Work of Strategy

Does every company need an "AI Value Realization Office"? Not necessarily. Adding another central department often just adds more bureaucracy to a company that is already too complex.

However, the capability must exist somewhere. Someone must:

• Maintain a bird's-eye view of where value is appearing

• Challenge investments when old strategic assumptions die

• Connect projects that cut across separate departments

• Help leaders decide what to grow, what to kill, and where to send capital
  

The corporate strategy team is the natural home for this work. Strategy teams already sit at the intersection of company priorities, budgets, and executive decisions.

Historically, however, strategy teams have focused only on the very beginning of the business cycle:

Analyse Market ---> Design Strategy ---> Set Priorities ---> Hand off to others

AI forces strategy to move further down the stream. Strategy must now maintain a continuous loop:

Strategy ---> Investment ---> Execution ---> Value ---> Reallocation

This final step, reallocation, is the key. The goal of management is not to prove that a project met its original budget. The goal is to constantly ask whether the company's money and talent could create more value somewhere else.

5. Five Questions for Leadership

To determine if your organisation is managing AI correctly, bring these five questions to your next leadership meeting:

1. Where is AI moving the money in our industry? Do not look inward at your own tools. Look outward at how industry economics are shifting.

2. Which parts of our business become more or less attractive as a result? The answer should change where you invest your capital long before it changes how individual employees do their daily work.

3. Where is value currently trapped between our departments? Look for customer experiences and workflows where no single executive owns the final outcome.

4. Who has the actual authority to stop, scale, or redirect our investments? A committee that is built to approve projects is rarely capable of stripping resources away from underperforming ideas.

5. What are we going to stop doing today to fund the opportunities of tomorrow? If you cannot name what you are abandoning, you do not have an AI strategy, you have a wish list.