Human Element in Digital Transformation: Pharma Talks with Paul Tunnah 

Success in digital transformation is not guaranteed, no matter how advanced the tech stack is or how much money is invested. McKinsey reports that across industries, 70% of digital transformation initiatives fail to meet their stated objectives. The path to digital adoption in pharma is even bumpier due to the industry’s regulated nature.

The good news is that many of these failures are preventable with the people-first digital strategy and change management. In a recent episode of Pharma Talks, Paul Tunnah, founder of Pharmaphorum, healthcare communications expert, and co-founder of View AI, shared a more balanced and forward-looking perspective on how organizations should approach digital transformation.

Early in the conversation, Tunnah offered a perspective that reframes the topic:

I feel a bit allergic to the word digital. People get obsessed with technology, channels, and all that, but transformation is broader. It’s about people and how companies operate.

Transformation Always Revolves Around People

Why do so many organizations adopt innovation, yet so few manage to sustain or scale it? A lot of time goes into selecting and implementing a technology ecosystem, while the people component often becomes an afterthought.

In the phrase “digital transformation”, the first word points to technology. Yet, the second points to people. Transformation happens in how people change their ways of working, their mindset, and their skills.

Teams resist change when they do not see the value, do not understand the context, or lack proper support. When global and local teams are not aligned, organizational change in pharma begins to feel like a top-down whim that makes work just different and not necessarily easier.

Life sciences’ digital transformation discussions often begin with technology. This is a classic case of shiny tool syndrome, where attention shifts to selecting platforms instead of defining the problem that needs to be solved.

It is essential to first understand what kind of change is required to address that problem, and only then define how technology can support it. There is little value in talking about models, copilots, and automation without a clear vision of how these tools will help teams work better.

Playing Safe Is No Longer Safe

Organizations raise valid concerns around AI security and compliance. Ignoring these risks would be irresponsible. But focusing on them exclusively can lead to a self-fulfilling prophecy, where fear creates a state of inaction that ultimately causes the very risks organizations are trying to avoid.

As Paul put it:

There’s risk when adopting any new technology, but there’s also a reward. If AI helps solve a problem in collaboration with people, the upside is huge.

He also offered a reminder that conservative pharma companies may be tempted to disregard: “If your competitors are adopting new technologies and you’re not, that’s a risk too.”

The challenge is how to use AI responsibly, deliberately, and with cross-functional ownership. According to Paul, decisions about what to share with AI models and what to protect should never sit with one function alone.

It’s about understanding what’s unique to your company versus what’s generic. These decisions should involve IT and business leaders together, because they understand both security and downstream application.

Evolution, Not Revolution

AI headlines often come with familiar imagery: blue screens, robotic hands, and a strong sense of futuristic disruption. This visual language reinforces the idea that innovation is revolutionary, leading many to believe that AI can be adopted overnight.

When asked whether AI in CRM and customer engagement represents a revolution or an evolution, he didn’t hesitate: “I’d say evolution. Technology moves fast, but data, workflows, and people take time. Systemic change is gradual.”

Expecting people to quickly change entrenched habits and beliefs is like waiting for snow in May. The probability is not zero, but it is highly unlikely. What matters far more is continuous change management in pharma that embeds technology into real workflows and gives teams clear reasons and value to adopt it.

Paul described this state as a perpetual beta. Tools evolve, processes adapt, and organizations learn continuously.

Big companies shouldn’t try to build bespoke systems. It’s better to partner with experts who are constantly improving the tools.

Hyperpersonalizing Customer Interactions

Paul also tried to predict what pharma engagement might look like in 2026.

People are bombarded with information. Companies often add more channels, but the focus should be on quality, relevance, and trust. Engagement should be easy and cut through the noise.

Many organizations assume that a lack of data is the main barrier to personalization. But the challenge is often an abundance of it. Customer feedback, social listening, real-world evidence, and years of engagement history are already available.

When you gather all this data and plan for personalization, reality hits you with a cold shower.

Paul explained:

Personas aren’t static. Start with segments, optimize dynamically, and make sure field reps have the right materials to engage effectively.

Just as a doctor interprets complex clinical data to guide an individual patient, field teams need structured guidance to adapt content to each real-world interaction.

Engagement Requires Homework

Effective engagement often looks effortless from the outside, but it rarely is. Nataliya mentioned how even something that appears simple, like Elon Musk riding a one-wheeled bike, requires immense preparation behind the scenes.

Paul immediately connected that idea to pharma ecosystems.

Our ecosystems must provide feedback. Learn and adapt. Dashboards alone aren’t enough. And don’t get lost in big data. Maintain the human connection.

A human element in digital transformation might be the most important leadership challenge ahead.

Hot or Not: Signals for the Future

To close the episode, Nataliya and Paul played a quick “Hot or Not” game. The answers revealed a lot about where the industry may be heading.

• Generative AI producing 70 percent of pharma content? “Not yet. People factor still matters.”
• Commercial and medical teams building content together? “Hot. It’s happening.”
• Hyperpersonalization versus strong segmentation? “Hot. Fix segments first before chasing n equals one personalization.”
• Replacing channel mix thinking with story architecture? “Hot. Focus on story, not just channels.”

Pharma brands will move the needle by delivering value to HCPs, payers, and patients rather than focusing solely on technological advances.

Final Reflection

Digital transformation is about changing how teams think, work, and learn. AI is only a tool that supports that journey. As this technology evolves, it will become more capable and more invisible, working quietly in the background like an interpreter who enables the conversation without drawing attention to themselves.

As Paul reminded us throughout the discussion, transformation only sticks when it makes sense to the people doing the work and the people we are trying to serve.

If this conversation resonated with you, we highly recommend listening to the full episode playlist of Pharma Talks.

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