18-19 VEEVA SYSTEMS - Serious gAIns

It is an incredibly exciting time to be working at the intersection of life sciences and technology. If you had asked me a few years ago where we stood with AI, I would have told you we were deep in the hype cycle.

We’ve all seen the flashy pilots and the bold promises that didn’t quite land. But today, the atmosphere has shifted. The genie is out of the bottle, and as we move beyond mere experimentation, we are entering a phase of real, scalable utility.

At Veeva, we are seeing the emergence of Agentic AI – purpose-built, life sciences-specific intelligence that doesn’t just sit on top of a system but is natively embedded into the daily workflows of field teams.

However, as we bridge the gap between hype and value, the industry faces a critical question – how do we scale these use cases to ensure we realise their absolute, undeniable potential?

The path to successful AI in customer engagement is paved with two fundamental requirements: high-quality data and human trust.

In the world of retail or consumer goods, AI has it easy. There is a clear, linear outcome: a customer clicks a link; they buy a product; and the loop closes at the checkout. In pharma – particularly outside the US – the landscape is far more complex. We deal with aggregated sales data, disparate engagement touchpoints and strict regulatory boundaries.

We often say ‘garbage in, garbage out’ and in AI, that’s an absolute law. To turbocharge AI engines, biopharma companies must invest in a common data architecture.

This means getting rigorous about how content is tagged, how data is organised and how it is accessed via direct APIs. Without a foundation of rich, clean data, even the most sophisticated AI will fail to provide the personalised engagement HCPs now expect.

Then, there is the human element: trust. If our teams don’t believe in the suggestions the AI is making, they simply won’t use them. I believe trust is built on three things:

Transparency: Can we explain why the AI recommended a specific action?
Integrity: Is the underlying data accurate and reliable?
Ethics: Are we following evolving compliance and regulatory guidelines?

The upside of getting this right is too great to ignore. We must embrace AI safely and securely, because it is the only way to deliver the speed and depth of information that modern medicine demands

Transitioning to an AI-driven ‘Connected Engagement’ model isn’t a flip of the switch moment. In my experience, there are six drivers that determine whether an organisation is actually ready to make the leap:

Quality data availability: Do you have the right inputs, especially outcome-based data?
Ease of collection: Is your infrastructure set up to gather data without friction?
Data completeness: Are there blind spots in your customer view?
User interface and experience: How do people interact with the tech? We are moving towards voice-controlled, natively embedded AI in CRM that transforms call planning from a chore into a strategy
Scalability mindset: Are your pilots designed to be stress-tested for global rollouts, or are they just expensive science experiments?
Political will: Does the leadership have the mindset to drive a new way of working?

To trigger meaningful change, we have to look at the Connected Engagement model as a holistic ecosystem. At Veeva, we break this down into four essential elements that feed and reinforce one another.

1. Connected software
Gone are the days of best of breed solutions being strung together with digital duct tape. To reduce friction, companies need an integrated platform strategy. When AI is natively embedded – as we are doing with Veeva AI for CRM – it becomes a seamless assistant. For example, Voice Agent enables voice input into CRM, so field teams can capture information and follow-up actions quickly and easily, while Free Text Agent detects and flags potential issues in call notes to ensure accuracy and compliance. With more in-depth call reporting, companies gain the advantage of richer, higher quality customer insights.

2. Connected data
This is about achieving a true 360-degree view of the HCP. By using advanced analytics on a unified data set, we can close the marketing loop, understanding exactly what resonates and what doesn’t. This allows for faster, more agile engagement planning.

3. Connected processes
This is where many organisations stumble. It is all too easy to focus on the shiny software and forget that old processes will stifle new tech. We need to be more adaptive. Instead of one ‘e-detail’ used for every customer, AI allows us to adapt the proposition in real time based on the last conversation or the specific needs of that HCP.

4. Connected Teams
Finally, we must address the people. AI-driven engagement requires new skills, new mindsets, and even new ways of measuring performance. It’s a cultural shift toward ‘testing, learning and failing fast’.

Why are we doing all of this? Ultimately, it is about supporting HCP education and improving prescribing confidence. HCPs are under more pressure than ever; they need timely, evidence-based scientific information to make the best decisions for their patients.

Purpose-built AI helps bridge this gap. For instance, Veeva AI for PromoMats uses a Quick Check Agent to scan content against brand and compliance guidelines before it even hits the MLR (medical, legal, regulatory) review. This reduces errors and delays, meaning life-saving scientific information reaches the HCP, and the patient, much faster.

Furthermore, AI agents can now capture and structure insights from HCP interactions in real time via natural language processing. This allows field teams to stop worrying about data entry and start focusing on high-value, science-driven conversations.

We are at a tipping point. What worked in the past – the traditional, linear sales model – will not work in the future. This is perhaps the most radical period of change in the history of the life sciences industry.

For companies looking to navigate this new ecosystem, my advice is to start with a clear vision – what do your customers actually need? Don’t just buy software for the sake of it. Assess your current capabilities across the four connected pillars, identify the gaps and build a roadmap.

This transformation won’t happen overnight, but by focusing on ‘win-win’ value propositions – where the HCP gets better information and the company gets better insights – we can create a future-proof model that truly delivers for patients.

Make no mistake, the future of customer engagement is no longer a mystery; it is connected, it is intelligent and, above all, it is here.