Next in medtech 2025: Prepare to win in the future of health

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  • October 01, 2025

The US healthcare system is poised for a fundamental transformation, with more than $1 trillion of annual spend expected to shift from today’s fragmented, infrastructure-heavy model toward digital-first, consumer-centered, and data-powered care. The next 12–24 months are a critical window for medtech companies to put the building blocks in place, modernizing commercial execution making data AI-ready, reshaping operating models for speed, launching ecosystem partnerships and actively reshaping portfolios. Those who embrace this new way of operating can create differentiated outcomes and free up the capacity to reallocate toward higher top-line growth — performance that investors will reward.

The future of health will reward companies that take action now on five key pillars:

  1. Redefine commercial excellence as the engine of adoption and revenue
  2. Treat data as a product to power connected, outcome-driven care
  3. Rewire operating models to embed AI and agility
  4. Build connected ecosystems with partners across care pathways
  5. Reshape portfolios with an innovator’s mindset, reallocating capital to growth

For decades, medtech companies thrived by delivering exceptional product innovation, generating strong growth, high margins and consistent market outperformance. But this performance often masked operational inefficiencies such as disconnected systems, fragmented teams and underdeveloped enterprise capabilities. That margin for error is gone.

Medtech leaders now face a far tougher environment. Investor scrutiny is rising, regulatory and reimbursement hurdles are intensifying, AI-native competitors are entering the market and customers are demanding more for less. In this climate, leaders should show they can create value beyond the product itself.

Rewiring how medtech works

Medtech is being reshaped by powerful disruptions. The home is becoming the hub for diagnosis, intervention and recovery. Hospitals are evolving into modular care ports designed for short-stay procedures. Virtual teams, remote monitoring and AI-supported decision-making are extending care far beyond traditional facilities. At the same time, new entrants, digital platforms and data-native competitors are redrawing the lines of competition.

In this environment, breakthrough products alone are no longer enough. Profit pools are shifting toward product-enabled services, data-driven solutions and integrated care models where value is created over time. Medtech companies can serve as connectors across the healthcare industry and devices can become entry points into wrap-around offerings — analytics, digital monitoring and service pathways — that deliver measurable outcomes. Top performers will be defined by their ability to consistently execute across five foundations: data, operating model, ecosystems, portfolio and commercial excellence. The most successful medtech companies will be those that let go of legacy models and adopt this new playbook, positioning themselves to lead the future of health.

1. Redefine commercial excellence as the engine of adoption and revenue

Even a future-ready portfolio cannot deliver its full potential without effective commercial execution. You can build the most innovative, synergistic portfolios in the market, but they may never realize the value without today’s version of commercial excellence.

Importantly, commercial excellence is not one-size-fits-all. Different parts of your portfolio demand different models. High-growth categories merit full sales coverage, digital engagement and AI-augmented account teams, while mature businesses may be sustained through leaner approaches such as AI agents and centralized account support. Reallocating your commercial spend this way can drive outsized top-line growth without equivalent downside risk, freeing up capital to reinvest in priority areas. This is the commercial/portfolio connection that separates leaders from laggards.

Many companies still run outdated go-to-market strategies to grow sales. But customers no longer buy in a straight line; marketing “reach” does not equal influence and long-standing sales processes have outlived their value.

Leaders are pivoting their commercial efforts to where decisions are made. They fund and activate the most critical call points, use influence maps to navigate complex buying journeys, design coverage for how buyers behave and segment by value and propensity to buy. Their marketing content focuses on the real drivers of adoption-clinical outcomes, workflow impact and economics. And they relentlessly measure the metrics that matter: share of wallet, market share and headroom, where they’re winning or losing by segment, and the mix of new versus existing customer contribution.

Commercial processes are being rebuilt to be AI native. Manual quoting, pricing, contracting and customer service are automated or moved to self-service. Frontline teams are amplified with customer insights, guided players and digital enablers to workflow.

Commercial excellence, done this way, is a force multiplier. It aligns efforts to influence, matches how stakeholders make decisions and uses AI to turn everyday interactions into faster, sustained adoption.

  • Redesign go-to-market models to focus on solutions and pathways, not just products, aligning resources to the most critical call points.
  • Segment customers by value potential and propensity to buy, tailoring coverage and engagement strategies to maximize return.
  • Activate influence mapping to navigate nonlinear decision-making and identify high-impact stakeholders across the buying ecosystem.
  • Digitize and automate commercial processes, including quoting, pricing, contracting and service to free up capacity and accelerate speed-to-close.
  • Equip frontline teams with AI-driven insights and digital tools, enabling guided conversations, predictive targeting and personalized engagement.
  • Continuously measure the right metrics like share of wallet, win rates by segment, adoption velocity and contribution from new versus existing customers.
  • Accelerated adoption: Faster uptake of new products and solutions across priority segment.
  • Stronger customer economics: Measurable increases in share of wallet, win rates and market headroom.
  • Digitized operations: Most commercial processes (quoting, contracting, customer service) automated or self-service enabled within 12 to 18 months.
  • Frontline productivity uplift: Sales and service teams consistently using AI-enabled tools to drive higher-quality interactions and conversion rates.
  • Customer and stakeholder impact: Improved customer satisfaction and loyalty scores tied directly to commercial process improvements.
Actions over 12–24 months to achieve commercial excellence
  • Redesign go-to-market models to focus on solutions and pathways, not just products, aligning resources to the most critical call points.
  • Segment customers by value potential and propensity to buy, tailoring coverage and engagement strategies to maximize return.
  • Activate influence mapping to navigate non-linear decision-making and identify high-impact stakeholders across the buying ecosystem.
  • Digitize and automate commercial processes, including quoting, pricing, contracting, and service, to free up capacity and accelerate speed-to-close.
  • Equip frontline teams with AI-driven insights and digital tools, enabling guided conversations, predictive targeting, and personalized engagement.
  • Continuously measure the right metrics, i.e., share of wallet, win rates by segment, adoption velocity, and contribution from new vs. existing customer.
Key success indicators
  • Accelerated adoption: Faster uptake of new products and solutions across priority segment.
  • Stronger customer economics: Measurable increases in share of wallet, win rates, and market headroom.
  • Digitized operations: A majority of commercial processes (quoting, contracting, customer service) automated or self-service enabled within 12–18 months.
  • Frontline productivity uplift: Sales and service teams consistently using AI-enabled tools to drive higher-quality interactions and conversion rates.
  • Customer and stakeholder impact: Improved customer satisfaction and loyalty scores tied directly to commercial process improvements.

Actions over 12–24 months to achieve commercial excellence

  • Redesign go-to-market models to focus on solutions and pathways, not just products, aligning resources to the most critical call points.
  • Segment customers by value potential and propensity to buy, tailoring coverage and engagement strategies to maximize return.
  • Activate influence mapping to navigate non-linear decision-making and identify high-impact stakeholders across the buying ecosystem.
  • Digitize and automate commercial processes, including quoting, pricing, contracting, and service, to free up capacity and accelerate speed-to-close.
  • Equip frontline teams with AI-driven insights and digital tools, enabling guided conversations, predictive targeting, and personalized engagement.
  • Continuously measure the right metrics, i.e., share of wallet, win rates by segment, adoption velocity, and contribution from new vs. existing customers.

Key success indicators

  • Accelerated adoption: Faster uptake of new products and solutions across priority segment.
  • Stronger customer economics: Measurable increases in share of wallet, win rates, and market headroom.
  • Digitized operations: A majority of commercial processes (quoting, contracting, customer service) automated or self-service enabled within 12–18 months.
  • Frontline productivity uplift: Sales and service teams consistently using AI-enabled tools to drive higher-quality interactions and conversion rates.
  • Customer and stakeholder impact: Improved customer satisfaction and loyalty scores tied directly to commercial process improvements.

2. Treat data as a product to power connected, outcome-driven care

Medtech companies generate vast volumes of data across the value chain whether commercial, R&D, manufacturing, regulatory, quality or customer service and, increasingly, through connected devices as well. Too often, this data remains locked in silos, constrained by outdated governance and legacy IT systems, limiting visibility, slowing decisions and leaving value on the table.

That model no longer works. In an AI-driven world, leaders will treat data not as a passive asset but as a product that is discoverable, consumable and actively exchanged both internally and through a robust data marketplace accessible to partners across a continuum of care. When executed well, this approach makes data interoperable, AI-ready and directly linked to outcomes such as faster regulatory approvals, predictive quality, stronger compliance and better patient experiences. It also accelerates product development, improving success rates, performance and market impact.

This transformation is as much cultural as it is technical. Success requires new ownership models that empower your company to act on insights. It demands aligned incentives, modern capabilities and a shared data vision. Without this discipline, even the largest digital investments will underperform. With it, medtech leaders can turn data into a true growth engine — one that improves margins, accelerates innovation, and strengthens investor confidence.

  • Establish ownership and accountability: Appoint business-unit-level data product owners outside of IT responsible for data quality, availability and impact. Define incentives so leaders are measured on how data improves outcomes.
  • Build a minimum viable data marketplace: Pilot with one or two high-value workflows (regulatory submissions, quality reporting) and make data sets discoverable, interoperable and AI-ready with clear metadata, governance and access protocols.
  • Modernize infrastructure and governance: Where possible, retire legacy systems in priority areas and implement cloud-native, API-enabled platforms to enable cross-enterprise data flow, while creating pathways to accelerate impact through AI and agentic AI applications.
  • Link data directly to outcomes: Develop dashboards and predictive models tied to specific business outcomes and Track ROI by measuring how data use accelerates time-to-market and reduces compliance risks.
  • Scale culture and capability: Train cross-functional teams in data literacy and AI enablement. Embed a data-as-a-product mindset into workflows so data isn’t just stored but actively exchanged and used.
  • Measure what matters: Set baselines and target improvements in efficiency, speed, and quality within 12 to 18 months.
  • Business-led data ownership: Every critical workflow has a named business-unit data product owner with incentives tied to outcomes.
  • Data marketplace operational: A minimum viable data marketplace live within 12 months, making high-value datasets discoverable, interoperable and AI-ready.
  • Tangible business impact: Demonstrated improvements such as faster regulatory approvals, reduced compliance risks or accelerated time-to-market.
  • Cultural adoption at scale: Cross-functional teams trained in data literacy and AI enablement, with a visible shift to treating data as a product.
  • Measured performance gains: Efficiency, speed, and quality metrics (automation rates, first-pass quality, customer satisfaction) showing measurable improvements within 12 to 18 months.

Actions over 12-24 months for turning data into a growth engine:

  • Establish ownership and accountability: Appoint business-unit–level data product owners outside of IT responsible for data quality, availability, and impact. Define incentives so leaders are measured on how data improves outcomes.
  • Build a minimum viable data marketplace: Pilot with 1–2 high-value workflows (e.g., regulatory submissions, quality reporting) and make data sets discoverable, interoperable, and AI-ready with clear metadata, governance, and access protocols.
  • Modernize infrastructure and governance: Where possible, retire legacy systems in priority areas and implement cloud-native, API-enabled platforms to enable cross-enterprise data flow.
  • Link data directly to outcomes: Develop dashboards and predictive models tied to specific business outcomes and Track ROI by measuring how data use accelerates time-to-market and reduces compliance risks.
  • Scale culture and capability: Train cross-functional teams in data literacy and AI enablement. Embed a “data as a product” mindset into workflows so data isn’t just stored but actively exchanged and used.
  • Measure what matters: Set baselines and target improvements in efficiency, speed, and quality within 12–18 months.

Key success indicators

  • Business-led data ownership: Every critical workflow has a named business-unit data product owner with incentives tied to outcomes.
  • Data marketplace operational: A minimum viable data marketplace live within 12 months, making high-value datasets discoverable, interoperable, and AI-ready.
  • Tangible business impact: Demonstrated improvements such as faster regulatory approvals, reduced compliance risks, or accelerated time-to-market.
  • Cultural adoption at scale: Cross-functional teams trained in data literacy and AI enablement, with a visible shift to treating data as a product.
  • Measured performance gains: Efficiency, speed, and quality metrics (e.g., automation rates, first-pass quality, customer satisfaction) showing measurable improvements within 12–18 months.

3. Rewire operating models to embed AI and agility

The medtech sector cannot build the future in the image of the past. Legacy structures and rigid processes are incompatible with the speed, integration and intelligence the market demands. Despite heavy investment in digital transformation, many organizations still move slowly, fail to work effectively across functions and struggle to fully leverage disruptive technological innovations.

Future leaders will operate as intelligent enterprises that are outcome-oriented, data-enabled and built for agility at every level. This means breaking down silos, embedding analytics into everyday workflows and redesigning org structures and processes to empower a hybrid workforce of human and AI agents.

One proven accelerator is the creation of AI centers of excellence where business, technology and clinical teams co-design, test and launch solutions in rapid, iterative sprints. The concept of multifunctional teams working in sprints isn’t new. The critical difference is the industrialization of this process and commitment to make it a permanent fixture in the operating model.

  • Define a pragmatic transformation playbook that addresses both technical and nontechnical considerations, including data readiness, workflow reimagination, role definition shifts, KPI redesign, AI orchestration and change management.
  • Assign accountable leaders across functions to own each chapter of the playbook, confirming transformation is repeatable and enterprise-wide.
  • Select one priority area for improvement like product innovation or call center operations and apply the playbook to redesign work, identifying required digital/AI solutions and estimating their business impact.
  • Deliver solutions at speed-to-value, measure timelines in weeks, not months, to emphasize rapid impact and scalability.
  • Codify lessons learned and scale the approach across other functions and processes to institutionalize agility.
  • Faster cycle times and decision velocity: Demonstrable reductions in lead times across priority workflows like product development or regulatory submissions with measurable improvement in speed-to-value.
  • Cross-functional process orchestration: Improved coordination across functions like R&D, regulatory and commercial, tracked through reduced handoffs, streamlined approvals and integrated KPIs.
  • Increased automation and AI-powered decisioning: Higher automation rates and AI usage in targeted processes, with uplift in first-pass quality and system-recommended actions.
  • Improved workforce and customer experience: Positive feedback on new workflows from employees and customers, as measured by satisfaction, adoption and engagement scores.
  • Self-funding transformation: Digital/AI initiatives begin generating run-rate value within 6 to 12 months, unlocking capital for reinvestment and scaled deployment.

4. Build connected ecosystems with partners across care pathways

The next wave of medtech growth will come from reimagining the value proposition and the business models that deliver it. To lead, medtech companies should become orchestrators of care with diagnostics and therapeutics converging into one seamless, adaptive system. Medtech should evolve from stand-alone hardware to intelligent infrastructure.

Devices won’t just collect data, they will enable real-time diagnostics and insights that guide decision-making across the care continuum. Embedded intelligence will link devices directly to care teams, enabling timely interventions whether the patient is at home, in the hospital or on the move. The next wave of differentiation will come from brain-computer interfaces between patient and device, remote monitoring, robotics and neuromodulation as software and connectivity.

Leaders are making deliberate choices about where to compete, where to partner and how to share value — sometimes through joint ventures, sometimes through co-development partnerships and increasingly through collaborations with retailers, payers or digital platforms to create integrated care pathways that combine diagnostics, therapies and services.

But success requires internal readiness. Harmonized data, interoperable technology, flexible structures and outcome-based revenue models are essential for sustaining collaboration. Too many partnerships fail because incentives are misaligned, technology cannot scale or internal teams remain siloed. Companies that succeed apply the same clarity, accountability and discipline internally that they demand from their external partners. Early movers are already realizing benefits such as faster product uptake, stronger provider relationships and distinctive positioning in a crowded market.

  • Identify priority care pathways where an ecosystem model can meaningfully improve outcomes (chronic disease management, post-surgical recovery, at-home monitoring).
  • Define the roles and incentives within the ecosystem to clarify if the company will lead, enable, or participate and establish outcome-based KPIs with partners.
  • Launch 1 or 2 pilot ecosystems with carefully chosen partners (digital platforms, payers, retailers, tech companies) to test integrated pathways.
  • Enable interoperability from the start by investing in harmonized data systems, open APIs, and scalable technology to ensure ecosystem solutions can grow across markets.
  • Embed commercialization into the ecosystem model by retooling go-to-market strategies to emphasize care pathways and solutions, not just stand-alone devices.
  • Pilot ecosystems live within 12 to 18 months, demonstrating integrated diagnostics, therapies, and services in priority care areas.
  • Outcome-based partnerships in place with aligned incentives, clear governance, and measurable shared value creation.
  • Adoption and uptake gains with faster product adoption rates, stronger provider and payer relationships, and improved patient engagement within pilot pathways.
  • Commercial model shift with measurable revenue contribution from ecosystem-driven offerings (not just product sales).
  • Scalable infrastructure including interoperable data and technology platforms proven to support cross-partner integration.

5. Reshape portfolios with an innovator’s mindset, reallocating capital to growth

Delivering leading shareholder returns in the medtech industry will require a strategy to achieve durable, industry-leading top line growth. Rapid technology shifts and new care models demand continuous portfolio shaping — balancing organic innovation with bold inorganic moves.

Leading medtech companies will focus on:

  • Organic growth levers: Efficiently reallocating resources to priority growth programs, funding internal ventures and accelerating R&D in high-potential categories.
  • Inorganic growth levers: Using M&A to access capabilities, geographies and channels faster than organic build; conduct regular and proactive portfolio reviews and leverage divestitures to align along growth vectors and free up capital for growth.
  • Transformational intent: Viewing transactions not just as scale plays, but as strategic tools to reshape the business model, pivot to higher-margin segments or enable entry into the next wave of medtech innovation.

The most agile players will make disciplined, data-driven capital allocation decisions while also building the capabilities to capture value.

Proof points

4.4x

rate of acquisitions among S&P 500 companies as compared to divestitures

3.8%

median increase in a company’s stock price relative to their industry index around the date of a divestiture

10.4%

shareholder returns achieved by the top-quartile of divesting companies

Source: PwC analysis of Capital IQ data on 297 transactions between December 31, 2011, and October 31, 2022

  • Conduct disciplined portfolio reviews at least annually, asking:
    • Where is value being created or consumed?
    • Would we acquire this business again today?
    • Are there higher growth opportunities capital could be reallocated to?
  • Reallocate resources toward priority growth programs by funding internal ventures and accelerating R&D in high-potential categories.
  • Pursue inorganic growth strategically using M&A to acquire capabilities, channels or geographies faster than organic build; actively consider divestitures to free capital for redeployment.
  • Anchor deals in strategic repositioning to reshape the business model, pivot to higher-margin segments or position the company in next-wave medtech innovation.
  • Build integration and execution capabilities to capture value from portfolio decisions.
  • Capital reallocation at scale: Measurable shift of investment toward priority growth categories with clear divestiture or funding redeployment outcomes.
  • Balanced growth levers in action: Increased weighted average market growth rate because of innovation (accelerated R&D, internal ventures) and inorganic moves (M&A, partnerships, divestitures).
  • Transformational transactions executed: Deals completed that reposition the company into higher-margin segments, new geographies or breakthrough innovation categories.
  • Shareholder value uplift: Demonstrable financial proof points such as faster top-line growth relative to industry peers, margin expansion or stock performance around portfolio actions.
  • Institutionalized discipline: Regular portfolio reviews embedded into leadership routines with decision-making tied to data-driven metrics and future growth vectors.

A call to action

The next generation of medtech leaders will not be defined by products alone, but by how they rewire their businesses across five dimensions: commercial excellence, data, operating model, ecosystems and portfolio. Discipline is the differentiator. This is not only financial discipline but also operational clarity, decision-making speed and cultural accountability.

The opportunity is clear: Strengthen five foundations and create the discipline gap that separates leaders from laggards. Small differences in execution over the next 18 to 24 months will compound into lasting advantages in growth, competitiveness and investor returns.

Ask yourself:

  • Are our commercial models designed to drive faster adoption and deeper impact?
  • Are we using our data to generate insights and outcomes, not just reports?
  • Are our teams structured to move with speed, autonomy and AI-enabled intelligence?
  • Are we building partnerships and ecosystems that amplify value, not just expand reach?
  • Is our portfolio strategy, M&A, divestitures and organic investments creating the business we aim to become?

If the answer to any of these is no, it’s time to make a change.

Contact us

Glenn Hunzinger

Glenn Hunzinger

Health Industries Leader, PwC US

James Woods

James Woods

Principal, PwC US

Kevin McLellan

Kevin McLellan

Principal, PwC US

Dave Powell

Dave Powell

Principal, PwC US

Elena Pretto

Elena Pretto

Principal, PwC US

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