Transforming Medtech Company Workflows Through AI Adoption

By Andrew Savarese and James Edwards, PA Consulting

Across industries, innovation platforms constantly monitor device usage and anticipate future needs, fueling breakthrough ideas in real time. AI agents are dissolving silos in large organizations, allowing cross-functional knowledge and expertise to flow freely. As AI continues to mature, medtech ideation and development timelines shrink from years to days, resolving challenges before they even surface. Every medical device launch is safer, smarter, and faster — transforming patient outcomes and elevating business performance.

This isn’t science fiction. But in today’s reality, medtech leaders are understandably wary of AI deployment within their organizations. Despite huge investment in intelligent tools, the results are patchy. Ownership is unclear, integration is limited, and teams grapple with fear of failure or replacement. As a result, AI projects stay stuck in pilot purgatory — and so do the potential benefits.

So how can medtech companies learn from other industries and escape this vicious cycle to turn AI aspirations into tangible, visible, organization-wide benefits that accelerate innovation?

Where Are We Now?

Moving forward with clarity means being honest about current capabilities. In most medtech companies, AI-driven development is underway. But the agentic factories that combine autonomous AI agents with human teams to spur people-led, AI-enabled innovation aren’t yet a pervasive reality. Is the medtech industry simply lagging in psychological readiness, or is technology playing catch-up?

Unfortunately, the data points to the former. Examples from outside of medtech show that progress is, in fact, widespread. AstraZeneca’s ServiceNow platform overlays many of their systems, saving over 30,000 hours of low-value time per year to help solve complex pharmaceutical challenges. Beyond healthcare, nuclear site Sellafield and hygiene company Rentokil Initial use intelligent tools to offload repetitive but vital tasks onto machines, empowering humans to focus on the high-value delivery they were hired to complete. This was not an overnight phenomenon. These companies built their solutions on a solid foundation of data, processes, and governance, while also ensuring a consolidated organization-wide understanding of the value that AI tools bring. Board and CEO buy-in was equally important, ensuring the transformation was top to bottom as well as organization-wide.  

Conversely, many medtech companies remain trapped in analog. Legacy processes document what happens, rather than digitally accelerating toward better outcomes. Standardization and knowledge capture within and across organizations are limited, while digital transformation responsibility is unclear. Some of the world’s biggest medtech companies have yet to hire chief digital officers or chief AI officers to lead these efforts with vision, passion, and tactical execution. The approach to internal AI activation is scattershot, often causing confusion among teams and disillusionment when the initial results are lackluster. This has created a pilot purgatory, where overly ambitious ROI targets lead to the eventual abandonment of promising AI projects — and wasted investment. No wonder 80 percent of AI healthcare projects fail to scale. 

The Practical Pathway

To serve their purpose as the developers of life-changing medical devices that improve human health, medtech companies need fast, relevant, and safe innovation. AI supports this in two core ways: it shoulders repetitive internal tasks and synthesizes vast amounts of information to formulate ideas. Without the drudgery of paperwork and processes, humans can turn ideas into transformative concepts rapidly. And while that paper trail is essential for regulatory compliance and development rigor, there’s no reason it can’t be offloaded to a series of agents working in concert with the engineering teams bringing the device to life.

Looking deeper, AI agents can enhance every stage of a medically compliant product life cycle, from accelerated design and development to controlled deployment and rigorous testing. They can rapidly iterate against validated simulations and, under human oversight, continuously analyze performance. Beyond improving how products are made, AI can become part of the product itself, powering advanced diagnostics and evidence‑based medical recommendations. Together, these capabilities drive productivity, strengthen clinical robustness, and enable the faster delivery of safer, more effective medical products to patients. So, how can medtech leaders kickstart this journey?

1. Focus On Your People, Not The Tech

Many organizations adopt AI tools but retain legacy planning cycles and governance models. The result is fragmentation and lost value. The solution calls for a ”perpetual beta” mindset — a fundamental shift from simply providing tools toward continuous evolution. Organizations in perpetual beta continuously reinvent how they operate, asking human-centered questions to unlock the sharpest benefits.

These organizations don’t shoehorn AI into existing workflows. They identify which time-consuming, high-friction tasks swallow the lion’s share of employees’ time and energy. Two hours of wrestling with documentation is two hours of lost innovation — could AI shoulder that burden? This determines which use cases will drive the most value, strengthen organizational strategy, and achieve key milestones.

Realistic high-value applications with visible benefits foster an internal network where individuals see and share the advantages of intelligent tools – both for them and others. This will encourage individuals to let go of legacy tools and behaviors that consume significant time and effort. Small wins spark wider use cases while building a bank of best practice. Internal sharing can be amplified through training, digital champions, and education opportunities that encourage organization-wide experimentation. Ultimately, AI is a tool that unlocks human potential through augmentation. Medtech companies can tap into this capability by prioritizing human-in-the-loop solutions that enhance expertise.

2. Set The Vision

Giving someone a tool they don’t know how to use is like handing them a pair of running shoes and telling them to start sprinting. How far? In which direction? What happens when they get there? A single enterprisewide vision for AI and digital — a North Star — sets the goalposts while codifying privacy, safety, and compliance principles from the start. For example, for R&D or operations teams, explain that the tool will free up 20 percent of their day by automating appropriate tasks so they can focus on what matters.

In addition to the North Star, tell a story. People remember and share stories, not bullet points. For instance, in sales, a story could paint a picture of a representative using a territory app and AI agent to offer innovation to millions of people. Before going to visit the hospital CEO, the rep could find out if any products are on back order, whether there are any outstanding POs, clinical news, or board minutes of relevance, and which proposals from other business units are being considered. All of this is provided instantly via AI agents, saving numerous phone calls and research time while accelerating the sale. What sales rep isn’t going to want this capability at their fingertips?

Setting a North Star marks out the finish line, but providing a story and achieving a minimum viable product sets the realistic goal of getting through the next lap. The aim isn’t to simply provide a tool — it’s ensuring that successful internal digital transformation supports the broader organizational vision of placing life-changing products into the hands of practitioners and patients.

3. Build Iteratively — Don’t Wait For Perfection

Start small, gather evidence, and iterate quickly. Plan for scale from day one to avoid pilot purgatory, while achieving demonstrable, early ROI to inspire repeat use and wider adoption. Importantly, feed results back into the business so they support continual improvement and align with strategy. And finally, set accountability, with a business leader responsible for identifying AI or digital initiatives that drive productivity and efficiency gains and embed AI into daily practice.

Structurally, medtech leaders need to collaborate internally, seeking to build or expand the infrastructure to join up data and integrate value-adding solutions across different functions. Cross-functional leadership and new operating models help to break down silos, while evidence from successful initial projects should be rapidly disseminated to justify expansion and drive adoption.

And let’s not forget all of this is with the aim to bring life-changing innovations to patients to build a healthier future. Continued engagement with regulators and clinicians during the transformation process drives the transparency needed to ensure efficiency isn’t driven in one area only to slow down in others. Large transformations often require a trusted partner who understands medical device development, change management, and the technologies to help build the data architecture, processes, and governance capabilities needed to have robust conversations with clinicians and regulatory bodies.

4. Measure What Matters

The intelligent enterprise is constantly evolving, and as such there is a mindset shift that requires comfort in a state of perpetual beta. But if the goalposts keep moving, teams will eventually get bored of running. They need to see results so they can move forward with confidence. The more transparent AI-related metrics are, the more employees will understand the advantages and trust in new tools. This applies to employees in its broadest sense: leaders need to see that AI is worth the investment to continue to back projects, while on-the-ground operational teams need to know that familiarization efforts and training time will be more than justified by reduced low-value tasks and stress. Set realistic goals framed appropriately from an employee’s view. Relevant statements and questions will ensure the psychological buy-in needed for these large-scale endeavors.

It’s important to contextualize AI within broader business goals — it’s not AI for AI’s sake; it’s a tool that is meant to work alongside you to augment what you are doing that allows us all to meet business objectives. When applied to the right use cases with the right governance frameworks, AI mitigates risks, saves time, unlocks productivity, and drives data-rich innovation. All of this can support better internal processes, improving employees’ work life while accelerating the development of powerful medtech devices that reach people in record time.

Conclusion: From Marathon To Sprint

AI adoption fails when goals are unclear and aspirations are too lofty, and the same is true for any new technology or process. Medtech leaders can escape AI pilot purgatory through realistic applications, achievable goals, and incremental steps.

Moving from a marathon to a sprint mentality avoids the temptation to plow on in pursuit of a mythical finish line. Hit mile one, assess, and move forward — always with a firm focus on what will help those who use and benefit from AI tools. By measuring what matters, proving value, and supporting the case for investment, AI will head toward the path of adoption rather than abandonment.

About The Authors:

Andy Savarese is a partner in PA Consulting’s U.S. Digital Surgery practice. He has two decades of experience helping clients in the surgical robotics industry turn their digital surgery aspirations into commercial reality. At PA, Savarese supports clients to bring digital surgery solutions to market, helping clients realize the promise of digital transformation of surgery, and improving patient outcomes. He is based in Boston, MA. He can be reached on LinkedIn.

James Edwards is a medtech digital transformation leader at PA Consulting. He helps clients reimagine and deliver digital experiences that improve outcomes for patients and participants, streamline clinical and operational workflows, and accelerate innovation, while meeting the demands of regulated environments. Edwards has led global programs for multinational medtech and healthcare organizations, bringing a blend of product strategy, delivery leadership and engineering expertise to turn ambitious visions into secure, scalable platforms and services.