Tony Hogben is the Immersive Studio Lead at Pfizer Digital Omnichannel Services & Solutions (OSS). Pfizer Digital Omnichannel Services & Solutions (OSS) is at the forefront of transforming how Pfizer connects with patients, healthcare providers and professionals worldwide. Through innovative digital strategies, cutting-edge technology, and data-driven insights, OSS powers seamless, personalised, and impactful experiences. By integrating advanced analytics, automation, and AI-driven solutions, the team enhances engagement, optimises communication, and drives meaningful connections across all digital touchpoints.
You’ve had an extensive career in digital innovation and immersive technologies. What first sparked your interest in this field, and how did your journey lead you to your current role?
My path has been somewhat unconventional. After completing a degree in ‘New Media’ at the turn of the century—when digital was still finding its footing—I established and ran my own digital agency. Working during the emergence of Web 2.0 was truly exhilarating. We were pioneering SAAS solutions and early mobile applications in an environment where innovation wasn’t just a buzzword—it was our daily reality. Every project broke new ground, and the entrepreneurial energy was infectious.
After successfully selling my business just before the pandemic, I initially enjoyed the downtime, but quickly realised I needed a new challenge that would leverage my expertise. Joining Pfizer Digital has allowed me to combine both my creative vision and technical capabilities, drawing on nearly two decades of experience helping organisations of all sizes transform digitally.
Building the Immersive Studio from the ground up has been particularly rewarding— creating an internal innovation hub that enables teams across the company to harness immersive and interactive technologies. Currently, I’m part of a team spearheading our initiatives to integrate AI solutions across multiple departments and use cases, helping teams reimagine their workflows and capabilities.
What’s been most fulfilling about transitioning to healthcare is applying my passion for the intersection of technology and human experience in an environment where our work has tangible impact. Here, the precision, realism, and engagement we create through immersive technologies directly influences healthcare professional education and, ultimately, patient outcomes. This connection between technological innovation and human wellbeing drives me every day.
Medical training is undergoing a shift with AI-driven simulations. How do these AI- powered immersive experiences compare to traditional training methods in terms of effectiveness and accessibility?
I should start by addressing immersive experiences before exploring how AI is transforming the landscape.
Immersive training experiences fundamentally transform medical education by offering flexibility traditional methods can’t match. Learners can revisit complex scenarios from virtually anywhere, at their own pace, and as many times as needed. The evidence is compelling, knowledge retention rates for immersive learning are significant—up to 76% better than traditional training methods*
AI is now revolutionising these immersive experiences in four crucial ways:
In content creation, AI is democratising the development of high-fidelity simulations. What once required teams of specialised developers and months of work can now be completed faster and by far fewer people – this will unlock development potential and allow content to be created at scale.
For learner experience, AI enables dynamic adaptation—adjusting scenarios in real- time based on decisions and skill level, creating authentic challenges that better mirror clinical unpredictability.
On the feedback front, AI provides nuanced assessment beyond simple pass/fail metrics. It can analyse the learners’ movements, decision sequences, and compare performance against thousands of previous sessions to offer personalised coaching.
Finally, AI enables collaborative learning through natural language processing and intelligent avatars that simulate realistic patient and team interactions.
The accessibility impact is profound—AI-driven immersive experiences can be deployed widely and cost-effectively, helping address training gaps globally. This powerful combination of immersive technology and AI has the potential to democratise access to high-quality medical training, particularly in underserved regions.
*Bonde, Mads & Makransky, Guido & Wandall, Jakob & Larsen, Mette & Morsing Bagger, Mikkel & Jarmer, Hanne & Sommer, Morten. (2014). Improving biotech education through gamified laboratory simulations
Can you share insights into how AI-driven medical simulations are being developed at your company? What are some of the biggest challenges in building these high- fidelity simulations?
We’re in the early stages of integrating AI into our approaches. We have a clear vision of where we’re heading, but the heavily regulated healthcare space we work in necessitates methodical implementation and rigorous validation. This creates a tension between our desire to innovate quickly and our obligation to proceed carefully—we’d love to keep pace with the frantic innovation happening with AI.
Currently, we’re focusing our AI efforts in three key areas:
- Content Creation Acceleration: We’re using AI to enhance our content development pipeline, helping our medical and instructional design teams scale production of evidence-based scenarios, clinical variations, and patient models. This allows us to maintain quality while significantly expanding our library of simulations.
- Technical Development Acceleration: We’re leveraging AI to streamline our technical development processes, enabling faster prototyping, testing, and deployment of new simulation features and capabilities. This is helping us overcome resource constraints and accelerate our innovation cycle.
- Learner-Adaptive Experiences: In parallel, we’re developing ways to incorporate AI directly into our simulations to create more dynamic, responsive learning environments. This includes personalised feedback systems and adaptive difficulty based on learner performance patterns.
While progress requires patience in this domain, we’re excited about how these AI innovations will ultimately transform medical training and patient outcomes.
Your 360 degree experience, virtual laboratory, is an innovative approach to training healthcare professionals. How does it work, and what kind of feedback have you received from users so far?
The 360-degree virtual laboratory gives healthcare professionals the experience of walking through a real lab environment, interacting with medical equipment, practicing procedures, and solving real-world challenges in a fully immersive digital space.
The virtual lab was designed to complement in-person tours of working laboratories that demonstrate best practices. We recognised that physical lab visits involve complicated logistics and scheduling limitations, so we created a digital alternative accessible 24/7 from anywhere in the world.
Healthcare professionals navigate through detailed, interactive simulations that test their knowledge and enhance their understanding of laboratory procedures. The platform is designed for multiple devices, ensuring flexibility in how and where learning takes place. We’ve expanded our offering to include virtual labs for numerous medical conditions and have translated these experiences into many languages to support global education needs.
The feedback has been overwhelmingly positive. Users consistently praise three aspects:
- Realism: The high-fidelity environment creates an authentic sense of presence in a working laboratory
- Engagement: Interactive elements maintain interest and focus throughout the learning experience
- Flexibility: The ability to access training at their convenience and pace
Most importantly, healthcare professionals report feeling more confident in their skills and retaining information better than with traditional training methods. This improved knowledge retention translates directly to better patient care in real-world settings.
AI and immersive tech can make training more accessible, but do you see any barriers—such as regulatory concerns, adoption hesitancy, or technical limitations—that need to be overcome?
When it comes to implementing new technologies in healthcare training, the barriers differ significantly between immersive experiences and AI applications.
The primary challenges with immersive technology include:
- Development Costs: Traditionally, creating high-quality immersive experiences has been expensive. However, AI is actually helping us address this by accelerating content creation and reducing production time.
- Accessibility: We ensure our immersive training remains accessible by developing for multiple platforms, as demonstrated with our Virtual Lab which works across various devices. This approach allows learners to engage regardless of their technical setup.
- Adoption Hesitancy: This is perhaps our most persistent challenge, particularly among experienced healthcare professionals. Our strategy is incremental exposure—starting with familiar formats like our Virtual Lab that introduce spatial learning concepts without requiring a steep learning curve. This builds comfort with immersive concepts before advancing to more complex technologies.
For AI integration, we face different obstacles:
- Technical Limitations: We’re actively working through these by building robust platforms and approaches that will serve as foundations for future developments.
- Regulatory Concerns: This represents our most significant challenge. Regulatory bodies have valid questions about the accuracy and validity of AI- generated content in healthcare education. Our approach is to develop internal use cases first, creating concrete examples we can use to engage regulatory teams constructively. We recognise we need to support their understanding while collaboratively developing appropriate guardrails.
By addressing these barriers systematically and recognising their distinct characteristics, we’re creating pathways for responsible innovation that maintains the high standards required in healthcare education.
With AI accelerating at an unprecedented pace, do you foresee a point where AI could take on a more active role in real-time patient care, rather than just being a support tool?
This steps slightly outside my area of expertise, but I think we can see that AI is already moving beyond support roles in healthcare, with examples like AI-assisted diagnostics and real-time surgery guidance. In the next five years, I expect AI to take on a much more active role in patient care, but it won’t fully replace humans. Instead, AI will work alongside healthcare professionals in a “human-in-the-loop” framework, offering assistance without taking complete control. This shift raises ethical concerns around trust and accountability—while AI might suggest diagnoses or treatment plans, the final decision will still be made by humans to ensure patient safety. AI will enhance decision- making, but human judgment will remain essential.
In a world where AI-generated medical insights could one day outperform human professionals in certain tasks, how should the healthcare industry prepare for this shift?
With every technological transformation, we see task displacement rather than people replacement. The healthcare industry needs to reframe AI not as a replacement for professionals but as a collaborator. It’s a simple equation, Human + AI is greater than Human or AI alone.
This shift will be gradual and task-specific—likely beginning in areas like image-based diagnostics, pathology screening, and predictive analytics for patient deterioration. These are areas where pattern recognition at scale gives AI a natural advantage, while more complex clinical reasoning will remain human-led for the foreseeable future.
We need to start with small, targeted tasks that deliver immediate value rather than the usual all-or-nothing approach of monolithic solutions. This iterative approach allows clinicians and patients to build trust in AI capabilities over time.
Rather than resisting change, the healthcare industry should proactively shape how AI is embedded into the healthcare ecosystem, ensuring it enhances rather than diminishes the human elements that remain central to healing.
Ultimately, the first step any organisation should take is democratising AI exposure. Give your staff personal challenges to open their eyes to the possibilities—have them create an image, write an email, or build a presentation using AI tools. Once they experience the power firsthand, they’ll bring that excitement back to identify meaningful applications in their daily work. Bottom-up innovation often produces the most practical and impactful solutions.
Many companies struggle with scaling AI solutions beyond pilot projects. What strategies have you used to successfully implement AI at scale?
For me, successfully AI scaling any technology project involves addressing two critical challenges: technology infrastructure, and user adoption.
In healthcare’s heavily regulated environment, establishing robust technical foundations is essential before scaling any AI initiative. We need secure, compliant infrastructure that balances innovation with patient safety requirements.
With new technology, adoption often becomes the greatest barrier to scale. We’ve found that making AI as invisible as possible is crucial to widespread adoption. For example, being faced with a blank screen and needing to write an effective prompt creates significant friction for most users. Instead, we’re designing solutions where users can simply click pre-configured buttons or use familiar workflows that leverage AI behind the scenes.
Our approach prioritises starting small but building with scale in mind from day one. Rather than creating one-off solutions, we design modular components that can be extended and repurposed across multiple use cases. This allows successful pilots to become templates for broader implementation.
You believe AI is set to transform healthcare in ways that were once considered science fiction. What specific advancements do you think will have the most profound impact over the next five years?
As a child of the 80s, I remember the Six Million Dollar Man and Bionic Woman TV shows from the 1970s. Those shows featured characters physically augmented by technology, the real revolution with AI, however, will be cognitive augmentation. This excites me the most.
Over the next five years, I believe several other specific advancements will fundamentally transform healthcare:
- Administrative Automation: The bureaucratic burden that currently consumes so much of our healthcare professional’s time will be dramatically reduced. This isn’t just about efficiency—it’s about putting the care back into healthcare by redirecting human attention to patient interactions.
- Drug Discovery Acceleration: The timeline from identifying therapeutic targets to developing effective treatments will compress from decades to years or even months. AlphaFold, created and open sourced by Google’s DeepMind, has already revolutionised our understanding of protein structures—solving in days what previously took years of laboratory work.
- Precision Diagnostics at Scale: AI systems will dramatically improve early detection of conditions like cancer, cardiovascular disease, and neurological disorders through pattern recognition across vast datasets.
- Personalised Treatment: Treatment plans will be continuously refined based on individual patient data, adjusting in real-time to maximise effectiveness and patients’ engagement in their own care.
The pace of these changes will be startling. AI development is like dog years—but with exponential acceleration. We’re going to see what might have taken 50 years of conventional research and implementation.
These aren’t distant science fiction scenarios—they’re already emerging in early forms, it’s not the future, it’s now.