Moving at the Speed of Trust

Veeva MedTech Summit 2026 Event Brief

The Veeva MedTech Summit 2026 convened over 100 companies and more than 400 attendees in Chicago, Illinois. Seth Goldenberg, Ph.D., President of Veeva MedTech, opened with a keynote affirming Veeva MedTech’s long-term industry  commitment and placing AI at the center of current investment and future competitive positioning

At the event, I had the privilege to connect with leaders including:

This Event Brief provides Axendia’s analysis of the MedTech Summit, the market forces shaping the industry, and the implications of Veeva’s announcements.

The Platform as Generational Commitment

Goldenberg reframed the vendor relationship from the outset.

“Our goal is to be the best technology partner MedTech has ever had,” he stated, adding the aspiration to “be your partner for decades to come.”  – Seth Goldberg, Ph.D., President, Veeva

Vishaka Rajaram gave that commitment operational meaning: “I think it is a different muscle for a lot of MedTech organizations to take a partnership approach. Historically, this used to be a transactional vendor relationship. Our commitment to customer success is very sincere. There is not a single person at Veeva that would prioritize anything over doing the right thing for customer success.”

The Summit touched on product developments such as Veeva Basics, pre-validated, zero-implementation applications targeting the 10,000-plus MedTech companies not yet using enterprise software, and Steve Chalgren presented “the first purpose-built PLM solution for MedTech,” now in early adopter deployment, with bill of materials management, supply chain, and requirements management targeted for release by end of 2026

Goldenberg connected platform readiness directly to AI value: “AI is not going to drive efficiency if everything’s locked in a basement and it’s not ready for agents to work.”

AI Strategy: Moving at the Speed of Trust

Artificial intelligence dominated the Summit, with Veeva’s message focused on readiness. Goldenberg argued the industry is “very early” in the AI revolution. Rajaram noted the transition from legacy ways of working: “What I am hearing is the knowledge management void that could be created by AI. On the one hand, folks that have deep grounds of knowledge, the tenured folks, are somewhat resistant to adopt new technologies. On the other hand, organizations hire new graduates accustomed to using AI for everything. So, it is about balancing how to ensure that companies are using advanced technology to improve efficiency and accuracy while not losing sight of genuine product and process knowledge that humans must have.”

Vault AI capabilities will be available to all customers in the 26R2 release in August 2026.  The underlying MAAP architecture integrates Models, Agents, and Applications — as applications remain the system of record enforcing business rules, audit trails, and security. Matthew Kopecky described the approach: “We are building AI into our platform. We’re not purchasing it, we’re not partnering, we’re not labeling it. We’re building it in organically at the very foundation.” Demonstrated capabilities for quality management include a complaint intake agent automating email parsing, classification, and investigation initiation; an investigation summary agent generating narrative conclusions from complaint record families; and a super agent routing queries to the appropriate underlying tool without requiring users to specify which capability to invoke.

Goldenberg introduced Falcon, “the next big leap for Veeva,” an autonomous agent initiative extending beyond Vault toward cross-system operation, currently in early development. His preparatory roadmap centers on three disciplines: migrating to dual-mode applications serving both human users and agents, cultivating a data curation mindset to displace document-centric workflows, and aligning operating model changes enterprise-wide. In that context, the dual-mode application transition emerged as the single most important preparatory step organizations can take to position themselves for agentic AI workflows. 

Quality Cloud: Connected, Proactive, and Risk-Based

The Quality Cloud discussions reframed quality as a continuous enterprise feedback system. Rajaram opened with a foundational premise: “Most of a device’s lifetime being postmarket means a few things. Quality risk management, as part of the quality management system, is fundamental. Your decisions, the data, the way you analyze it, has to feed back to risk and influence your postmarket improvements, whether that is in the form of device design or improving process.”

The Veeva Quality Cloud roadmap for MedTech concentrates on three process priorities: “Postmarket is one. Risk management is the second process of focus, and not just the hazard analyses and FMEAs, but use cases of being able to connect it with the rest of the quality system. And the third process of focus is supplier quality, which is the underdog of the quality system. It is my favorite process, but so much of MedTech relies on supplied products and supplied instruments,” added Rajaram.

Those priorities map to three strategic themes: proactive quality management, user empowerment, and operational agility, described collectively as “being able to do more within the system, rather than outside it,” said Rajaram.  

The ecosystem necessarily extends beyond the enterprise. “The ecosystem has to extend forward as well as down into the CDMOs,” Rajaram said. 

Rajaram’s observation closes the loop across every function: “It is one thing for us to provide the tools and the connection between the applications. But really, what we need is top-down organizational change, a move away from continuing to operate in silos. And that starts with cross-functional leaders working together.”

Customer Perspective: Smith+Nephew’s Enterprise QMS Transition

I sat down with Joshua Cohen, Director of Global Quality Systems at Smith+Nephew for an in-depth discussion on the company’s QMS transition. Cohen described Smith+Nephew’s move from a fragmented multi-system QMS to a single harmonized platform, following a structured evaluation of more than 30 vendors. By the end of that process, Smith+Nephew selected Veeva as its enterprise QMS platform, with phase one deployment now underway. “By the end, it became clear that Veeva was the right long-term partner, not only to support what we have today, but also to enable future phases of digitization.” At scale — approximately 21,000 active employees and contractors, more than 60,000 reportable complaints annually, and approximately 1.5 million active training assignments — Cohen framed the decision as “comparable in scale, cost, commitment, and compliance impact to systems like MES, ERP, and PLM.”

Smith+Nephew took a phased approach to implementation, with phase one covering document control and training scheduled for August 2026, followed by complaints and validation in December. A purpose-built platform reduces configuration burden: “We’re implementing very close to standard, and that should make it much easier to stay current with the three-release cycle each year,” said Cohen.

On AI, Cohen remarked, “I wouldn’t describe us as an early adopter, but we are actively and cautiously evaluating AI because of the regulatory environment we operate in. AI should enhance people by improving efficiency, quality, accuracy, or speed, but it should not replace human judgment, especially at this stage.” 

Cohen offered advice to peers, saying, “Align early, align broadly, and connect the transformation directly to enterprise objectives. Without that, it can look as though you’re simply pushing for a new system, which makes adoption much harder.”

AI Across The MedTech Continuum

The closing panel featured Dr. Aarathi Cholkeri-Singh, Executive Director and Chief Medical Officer at Karl Storz, and Elizabeth Platt, Senior Vice President of Global Quality, Regulatory, and Clinical Affairs at Bio-Rad Laboratories. 

Platt characterized this AI moment as unlike any prior technology wave: “This is very different because we’ve not ever seen waves that are fully horizontal across the organization and transformational, so it’s not just a single technology in one function. It is a capability that can really touch every process.” Her governance framing, “How do we govern, validate appropriately, and redesign work to get value out of it without outsourcing accountability.”

Dr. Cholkeri-Singh observed that “AI’s not just changing how we work. It’s actually starting to influence how we’re making decisions.” Drawing on surgical robotics adoption, she argued trust built through demonstrated outcomes sets AI’s pace: “AI will move at the speed of trust.” 

Both panelists were unambiguous on accountability. “You can’t outsource accountability in regulated work — the human has to stay in the loop,” Platt stated, citing an FDA warning letter issued to a company that skipped validation requirements based on an AI agent’s recommendation. 

Dr. Cholkeri-Singh added that AI “doesn’t lower the bar for clinical validation — if anything, it actually raises the bar for how clearly we need to understand and explain what’s happening behind the output.” 

Across the discussion, AI governance, human oversight, and structured data foundations emerged as non-negotiable prerequisites for responsible AI adoption in regulated MedTech environments. Platt’s prerequisite: “AI on top of chaos doesn’t work.”

In Brief

The MedTech Summit affirmed Veeva MedTech’s deep industry commitment across its platform, quality, and PLM. The MAAP architecture and Falcon initiative reflect a deliberate, trust-based approach to AI. 

Smith+Nephew’s enterprise QMS migration underscores the momentum behind purpose-built life sciences platforms. 

The consensus across every session: governance, structured data, and human accountability are non-negotiable prerequisites for AI adoption. Moving with intention matters more than moving with speed.

We will continue to provide updates on Veeva MedTech as they become available.

To discuss how this initiative impacts your organization, click on this link to schedule an Analyst Inquiry on this topic.

The opinions and analysis expressed in this post reflect the judgment of Axendia at the time of publication and are subject to change without notice. Information contained in this post is current as of publication date. Information cited is not warranted by Axendia but has been obtained through a valid research methodology. This post is not intended to endorse any company or product and should not be attributed as such.