AI’s potential to transform life sciences is undeniable—it’s already accelerating drug discovery and enhancing operations. But technology alone won’t drive transformation.
To truly harness AI’s power, organizations must rethink how they work, prioritizing change management, breaking down silos, and building the digital foundation needed to keep up with innovation. Without these steps, AI’s potential will remain untapped.
I recently had the opportunity to explore this topic with industry leaders at the Lab of the Future event in Boston. The conversation reinforced that while the excitement around AI is high, there is work to be done to implement and integrate it successfully.
Digital Transformation Is a Journey—Not a Project
Too often, companies treat digital transformation like a one-and-done project. But real transformation is an ongoing process of learning, iteration, and adoption.
Technology alone doesn’t change a business—people do. And people don’t change overnight. Some employees embrace new ways of working, while others resist. Multiply this challenge across teams of scientists, engineers, and executives, and it’s clear why digital transformation requires a shift in mindset as much as technology.
Adoption, optimization, and true business impact take time. A new tool or system changes how teams work, which in turn uncovers new ways to refine, optimize, and rethink processes. The cycle continues, creating a feedback loop where the organization and technology evolve together.
To be successful, companies must embrace the long game. That means investing in ongoing training and change management. It means understanding that transformation isn’t about flipping a switch—it’s about continuously modifying how work gets done.
Change Management Is Crucial to Transformation
When organizations embark on a digital transformation journey, they tend to focus on the technology itself—selecting the right software, securing the right infrastructure, and ensuring cybersecurity and system administration standards are met. The assumption? If the technology is useful and provides clear benefits, people will automatically adopt it.
But that’s not how transformation works.
Technology reshapes business processes, workflows, and responsibilities—yet too often, companies don’t plan ahead for those shifts. They budget for software implementation but fail to allocate resources for business process mapping, training, and adoption strategies. Without these efforts, even the most powerful tools aren’t meaningfully integrated into how people actually work.
Take a simple example: a CRM system. A company might invest in one, expecting it to boost sales by improving customer tracking, pipeline visibility, and forecasting. But without clear guidance, incentives, and workflow adjustments, adoption often stalls. Leadership finds themselves constantly reminding teams to log interactions, while incomplete records limit the system’s effectiveness. The tool never reaches its full potential.
Now scale that challenge up to enterprise-wide AI adoption—a transformation that impacts people and processes across the organization. Without the right change management, AI is more likely to disrupt workflows than enhance them, pushing organizations into the dreaded trough of disillusionment.
Successful digital transformation demands large-scale organizational design thinking. That means asking:
- What will change in our business processes?
- How will our people work differently?
- What does successful adoption look like, and how will we measure it?
Breaking Down Silos to Keep Up with Innovation
In life sciences, it’s common for each stage of drug development—research, process development, clinical trials, and commercial manufacturing—to function almost like a separate company with its own tools, systems, and budgets. Data becomes more fragmented at every handoff, forcing teams to re-enter information and rebuild insights instead of working from a shared foundation.
AI is revolutionizing asset discovery, identifying hundreds of promising molecules in the time it once took to find a handful. But unless that data moves seamlessly from research into development, clinical trials, and manufacturing, the acceleration AI provides at the front end is lost in bottlenecks further down the pipeline.
Embracing digital transformation means reimagining how data flows. Historically, each phase of drug development optimized its own processes, but real progress happens when companies optimize the entire journey. Digital tools now make it possible to connect data across the full development lifecycle, reducing redundancy and creating a continuous path forward.
By shifting from siloed thinking to system thinking, organizations can align data, processes, and budgeting decisions, enabling the entire ecosystem to keep up with the speed of asset discovery.
The Risk of Falling Behind
When the pandemic hit, businesses were forced to adapt overnight. Remote work, virtual collaboration, and cloud-based tools became essential. Organizations that were already digitally enabled made the shift seamlessly while others scrambled to catch up. I felt fortunate that our team was ahead of the curve—we had transitioned to Microsoft Teams just a few months prior, which made the pivot to remote work far smoother than it could have been.
As AI reshapes life sciences, the same urgency exists. The difference is that this time, there’s no external forcing function. Organizations need to create their own momentum, or they risk falling behind. And in life sciences, falling behind isn’t just a competitive setback—it delays getting life-saving therapies to patients who need them now.
Finding the right drug candidate isn’t enough. Every extra step, every inefficient handoff, every disconnected system adds time that patients don’t have. Companies must be able to move quickly from discovery to development to commercialization. Without a strong digital foundation, they’ll be outpaced.
A digitally enabled enterprise is more efficient, agile, adaptable, and capable of delivering breakthrough therapies faster. Life sciences companies that embrace digital transformation will be positioned to move quickly, reduce costs, and save more patients’ lives.
