Capital rewiring in pharma and health systems

Strategic signals from the CB Insights Book of Strategy Maps

Healthcare strategy in 2026 is being shaped less by technological possibility and more by constraint. The CB Insights Book of Strategy Maps: Pharma & Health Systems reveals how capital is being reallocated under pressure from patent cliffs, labor shortages, geopolitical fragmentation, and infrastructure limits. Across regions, organizations are converging on a similar response: concentrate capital, compress timelines, and secure control over platforms—data, diagnostics, and delivery—rather than expand pipelines indiscriminately.

This is not a cyclical adjustment. It is a structural reset in how growth, resilience, and competitiveness are pursued.

From expansion to compression

Two forces dominate the strategic landscape. The first is economic: sustained higher capital costs have sharply reduced tolerance for long-dated or speculative bets. The second is technological: AI, diagnostics, and biologics platforms have matured enough to deliver measurable operating leverage rather than incremental experimentation.

The interaction of these forces is producing compression. Fewer initiatives receive funding, but those that do are larger, later-stage, and closer to revenue impact. Across pharma and health systems, acquisitions, partnerships, and internal investment increasingly target assets that shorten time-to-value—whether by accelerating development cycles, defending near-term revenue, or manufacturing capacity digitally.

This compression is visible in deal structures, capital commitments, and the strategic logic behind them. Growth is no longer pursued through breadth. It is pursued through control.

Revenue defense as strategy

A defining, though often understated, driver of current capital flows is the generic patent cliff. As major therapies approach loss of exclusivity, the imperative to defend revenue has intensified. The Strategy Maps show multiple large-scale acquisitions and platform investments that function less as growth bets and more as revenue replacement mechanisms.

This dynamic has several second-order effects. Deal urgency increases, competitive tension rises, and valuation discipline weakens—particularly for late-stage or de-risked assets. In some cases, this urgency spills into earlier stages, inflating preclinical valuations as organizations seek optionality wherever it can be secured.

The strategic implication is clear: capital deployment today often reflects pressure, not confidence. Understanding where defensive motives dominate helps explain both elevated deal premiums and the clustering of activity around similar therapeutic areas.

Diagnostics as control points

One of the most consequential shifts highlighted in the report is the rising strategic weight of diagnostics. Rather than treating diagnostics as supporting tools, leading organizations are positioning AI-powered diagnostic platforms as market gatekeepers—particularly in immunotherapy and precision oncology.

This marks a subtle but important reframing of innovation strategy. Control over diagnostics increasingly determines which therapies are prescribed, to whom, and when. In effect, diagnostics become demand-shaping infrastructure rather than ancillary services.

The margin profile reinforces this logic. Diagnostic platforms offer high scalability, recurring revenue, and defensible data advantages, while simultaneously reinforcing downstream therapeutic portfolios. The result is a flywheel effect that favors those who integrate diagnostics early and deeply into their strategy.

AI moves from narrative to cost structure

AI’s role has also changed materially. The report documents a transition from pilot programs to scaled deployments with direct financial impact. In clinical trials, AI-enabled tools are reducing documentation and reporting cycles from weeks to days, directly attacking one of the largest cost centers in drug development. In health systems, ambient AI and automation are manufacturing capacity in the face of structural labor shortages.

What matters strategically is not the technology itself but its placement. AI is being embedded at bottlenecks—clinical trials, documentation, scheduling—where marginal efficiency gains compound across the system. This shifts AI from an innovation narrative to a cost-structure instrument.

The implication is that competitive advantage will accrue less to those with the most advanced models and more to those who integrate AI into operational choke points with discipline and governance.

Infrastructure returns to the foreground

Alongside digital platforms, physical infrastructure has re-emerged as a strategic priority. The report highlights substantial long-term commitments to domestic manufacturing and R&D capacity, particularly in biologics. These investments reflect more than supply chain caution; they signal a rebalancing toward policy-aligned resilience.

Geopolitical fragmentation has increased the value of physical proximity—to regulators, markets, and labor pools. Infrastructure spending therefore serves multiple objectives: operational continuity, regulatory alignment, and strategic optionality under uncertain trade and policy regimes.

This trend challenges the assumption that healthcare strategy is primarily digital. In practice, competitive positioning now depends on the interaction between digital leverage and physical capacity.

Health systems: manufacturing capacity without hiring

On the provider side, the Strategy Maps reveal a parallel logic. Faced with persistent labor shortages and rising demand, health systems are increasingly manufacturing capacity through technology and cross-sector partnerships rather than expanding headcount.

Ambient AI, workflow automation, and predictive scheduling tools are reducing administrative burden and improving throughput. At the same time, partnerships with retail clinics and alternative care models are enabling labor substitution, shifting routine care to lower-cost settings staffed by non-physician clinicians.

This is not incremental optimization. It is a redesign of care delivery economics, aimed at preserving access and margins without relying on scarce labor. Systems that execute this transition effectively gain structural cost advantages that are difficult to replicate.

Capital concentration and competitive dynamics

Across both pharma and health systems, capital concentration is intensifying. Large incumbents with balance sheet flexibility are deploying capital into platforms—AI, diagnostics, data infrastructure—while smaller innovators increasingly position themselves as partners or acquisition targets rather than independent scalers.

Regionally, distinct patterns emerge. North America leads in AI deployment and infrastructure investment. Europe emphasizes therapeutic specialization and diagnostics integration to navigate pricing pressure. Asia, particularly through China-linked collaborations, functions as an innovation accelerator rather than a purely cost-driven extension.

Despite these differences, the underlying strategy converges: secure control over assets that shape demand, reduce unit costs, or compress timelines.

Actionable risks to monitor

Several risks surface repeatedly across the Strategy maps:

Valuation Risk Competitive bidding—particularly under defensive pressure—raises the likelihood of overpaying for assets whose returns depend on optimistic integration assumptions.

Governance Drag As AI and data monetization scale, uneven governance capabilities can become binding constraints, limiting deployment or triggering regulatory friction.

Integration Friction Complex combinations of AI, data, diagnostics, and clinical workflows carry execution risk that can dilute expected gains if change management lags.

Geopolitical Exposure Cross-border collaborations face increasing regulatory and data-sovereignty constraints, complicating global innovation strategies.

These risks are not hypothetical. They are already shaping which strategies scale and which stall.

Strategic takeaways

The CB Insights Book of Strategy Maps makes one conclusion unavoidable: healthcare strategy has entered an era defined by constraint-driven choice. Capital is no longer abundant, labor is structurally scarce, and geopolitical certainty has eroded. In response, organizations are narrowing their focus and raising their threshold for investment.

Success under these conditions depends on three capabilities:

• Capital discipline: allocating resources where execution leverage is demonstrable.
• Platform control: owning diagnostics, data, and infrastructure that shape demand.
• Operational integration: embedding technology at bottlenecks rather than edges.

Those who align innovation with these constraints are not merely adapting to 2026—they are shaping the competitive terrain that follows.

Source: Insights based on the CB Insights “Book of Strategy Maps: Pharma & Health Systems” (2026).