Curbside Consults by RISE | Edition 09 | October 12, 2026 *
The Signal
AI adoption is becoming one of the most important organizational challenges facing life sciences leaders.
The technology is advancing. Investment is increasing. Employees are experimenting. And yet, many organizations are still struggling to translate that activity into sustainable enterprise value.
When adoption slows, a familiar explanation often emerges:
Our people aren't ready.
They need more training. More communication. More encouragement to embrace change. Sometimes that's true.
But what if the bigger problem isn't employee readiness?
What if the organization itself isn't designed to support the behaviors it's asking employees to adopt?
Why It Matters
Consider what happens when an organization introduces a new AI capability.
Leadership communicates the opportunity. Teams attend training. Early adopters begin experimenting.
Then the questions start.
Who approves the use case?
Can the output be incorporated into an existing workflow?
Who is accountable for its accuracy?
What happens when AI recommendations conflict with established processes?
How will success be measured? When these questions lack clear answers, adoption becomes dependent on individual initiative rather than organizational capability.
And that's a fragile foundation for enterprise transformation.
In pharma and biotech, the challenge is amplified by complex governance requirements, established commercial processes, and the need for coordination across functions.
An employee can be enthusiastic about AI and still be unable to use it effectively within the organization's operating model. Enthusiasm doesn't overcome structural friction.
The Curbside View
Here's a distinction worth making:
AI adoption is not simply a change management challenge. It's an operating model challenge.
Training people to use new tools is important.
But sustainable adoption requires organizations to rethink how decisions are made, how work gets done, and how accountability is established.
That means moving beyond asking:
How do we get employees to use AI?
And beginning to ask:
What needs to change in our organization so employees can use AI effectively, responsibly, and consistently?
Those are fundamentally different leadership questions. And they produce fundamentally different strategies.
The Move
For leaders trying to accelerate enterprise AI adoption, I'd start with four practical questions.
1. Where does AI fit into the actual workflow?
If AI remains an optional activity outside established processes, adoption will depend on individual enthusiasm. Identify where it can meaningfully improve existing work.
2. Are decision rights clear?
Employees need to understand what they can do independently, what requires approval, and who owns the outcome.
3. Are managers equipped to reinforce adoption?
Managers translate enterprise strategy into everyday execution. If they don't understand how AI changes expectations, employees will receive inconsistent signals.
3. Are we measuring outcomes or activity?
The number of licenses, training completions, or prompts submitted may indicate engagement. They don't necessarily demonstrate business value. Measure improvements in productivity, decision quality, execution, and other outcomes that matter to the business.
These questions won't solve every adoption challenge.
But they'll reveal whether the organization is creating the conditions for AI to succeed.
One Question to Take With You
If every employee in your organization became proficient with AI tomorrow, would your operating model allow them to use it effectively?
If the answer is uncertain, the next investment may need to be in organizational readiness—not another technology platform.
That's one of the challenges we're exploring through the RISE Index™ 2027, our research initiative examining enterprise AI adoption across life sciences. We invite leaders across pharma, biotech, and the broader life sciences ecosystem to contribute their perspectives.
Participate in the research:
https://therisegroup.ai/research/enterprise-ai-adoption-2027
Curbside Consults by RISE
Practical perspectives on AI, commercial strategy, and the challenges of turning ambition into execution.
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