By Patrina Pellett & Sarah Snyder 

What 53+ Medical Affairs AI programs reveal about adoption, team capability, and what leaders should do next. 

“I don’t have Copilot on my computer.”  

This was at one of our first in-person AI trainings in March 2025. The range in comfort with AI was impossible to miss. At the same time, another MSL had used Copilot to build out the entire Med Info department and was saving hours. They were already thinking several steps ahead. 

The MSLs that didn't think they had Copilot on their computer did. They just didn't know where to find it. Same company. Same training. Completely different starting points and AI comfort levels.  

In summer of 2025, we got serious about showing impact of our AI training programs and started rigorously measuring each training session and program. After delivering over 53 AI trainings to 265 Medical Affairs professionals across 10 pharma and biotech companies, we a broad range of comfort levels with AI. From power users to folks terrified to use it.  

AI use is growing fast among Medical Affairs teams, but that doesn't mean they are AI-ready. 

That is not a reason to slow down. It is a reason to get more deliberate about helping people build the right skills, apply AI to real work, and show how that work is improving. 

Medical Affairs is becoming more AI-active. The next step is turning that activity into visible impact. 

Leaders now need to turn that momentum into giving their team superpowers and more consistent strategic Medical Affairs performance. This article outlines 5 AI readiness metrics to get your team there.  

AI Adoption in Medical Affairs Is Accelerating 

There is no question that Medical Affairs is using AI more. In July of 2025, one of Sarah's LinkedIn polls on AI use showed that 55% of respondees (n=336) were using AI daily. For some teams that number is much higher, with 80-90% using it daily. One of the Medical Affairs teams we worked with had daily AI use rise from 29% before training to 67% three months later. 

The way people used AI also changed. Use for ideation increased from 41% to 83%. Use for feedback rose from 32% to 67%. That shift is more interesting than use metrics. People were moving beyond drafting emails and creating summaries to using AI to explore ideas, challenge their thinking, and improve work already in progress. 

Medical Affairs leaders no longer need to ask, “Will our people use AI?” 

The better question is: Can we turn uneven individual use into a reliable team capability that helps the team do more strategic work and have a larger impact? 

Daily AI Use Does Not Equal Medical Affairs AI Readiness 

Usage data tells leaders whether people have started. It does not tell them how well people can perform. 

Here's where AI adoption in Medical Affairs gets interesting. Our data shows that daily use doesn't mean using AI well. For example, one team had 33 people reporting daily AI use, but they ranked their confidence in it as average (2.5 out of 5), showing that frequency of AI use and capability are not the same thing. 

Someone can use Copilot every day for basic tasks like rewriting emails but not use it at all for deep strategic work or applying AI to a full workflow. Another person may use it less often but use it exceptionally well for one high-value task. 

The question becomes do we want Medical Affairs to be using AI strategically or more like a task monkey? Should it save a little bit of time on boring admin tasks or should it give people super powers? Medical Affairs leaders need a fuller picture. These 5 AI readiness measures for Medical Affairs help provide it. 

5 Measures of AI Readiness in Medical Affairs 

1. Confidence in AI Skills: Find the Skill Holding the Team Back 

“Your team feels more confident using AI” sounds good, but it does not tell a leader what support the team needs next or where they are struggling.  

Confidence in prompting is different from confidence in scientific validation, compliance, or workflow integration. A team may be strong in three areas and still be held back by the fourth. 

That's why it's important to assess those capabilities separately. The 5 skills we measure in every program are confidence in prompting, verifying accuracy, applying compliance guardrails, daily use, and integration into workflows. It allows training to meet people where they are instead of treating everyone the same 

The leadership question is: Which skill gap is stopping the team from doing more valuable work with AI? 

2. Meaningful AI Use: Look for Better Thinking 

An increase in daily use is encouraging. It’s not the end goal. 

It breaks our hearts when teams report only using AI for writing emails or creating summaries (basic content generation tasks). It shows an education gap in how to use AI. Do you want your team drafting emails or going next level in their thinking? 

One of the team's we worked work had daily AI use rise from 29% before training to 67% three months later. But the more interesting shift was how people used it. Ideation increased from 41% to 83%. Using AI for feedback rose from 32% to 67%. 

That is a different kind of adoption. The team was not merely asking AI to produce more content. People were beginning to use it to explore options, challenge their thinking, and improve work already in progress.  

The strategic move is to go from content generation to ideation and feedback. This is a sign of more mature AI use and what Medical Affairs leaders should pay attention to.  

Basic uses remove friction. More strategic uses help people prepare better questions, examine an insight from several angles, pressure-test a plan, or improve scientific communication. Both have value, but they should not be counted as if they represent the same level of capability. 

That is the shift our training is designed to create. The goal is not simply more AI output. It is better thinking around the work that matters. 

Ask: Is AI helping the team produce more or think better? 

3. AI Workflow Adoption: A Prompt Library Is Not a Workflow 

We love a good prompt library (get some free prompt packs on our resource page). But a folder full of prompts does not mean the team has changed how work gets done. 

In one cohort, seven of nine respondents used AI daily, yet everyone rated workflow integration at only 2 or 3 out of 5. AI was present in the work, but it had not become part of a reliable process. 

Take KOL research. Asking Copilot to summarize a publication is an AI-assisted task. Building a repeatable pre-call planning process that combines stakeholder priorities, publications, previous interactions, insights questions, validation, and a clear engagement objective starts crossing into an AI-enabled workflow. 

Our programs put AI inside real Medical Affairs work because people need to practice the whole process, not just the prompt. The aim is not identical output from every person. It is a reliable standard for how good work gets done. This matters even more as teams explore agents. An agent can repeat a process at scale, but it cannot fix a process the team has never clearly designed. 

Ask: Have we designed and validated the workflow we want the agent to repeat? 

4. Team Consistency: AI’s Most Underrated Return 

Most AI business cases lead with speed. Our program data points to another source of value: reducing avoidable variation across the team. 

Before our KOL access training teams took anywhere from 61 to 137 minutes to research a KOL. After our AI-enabled workflow, this went down to 24 - 34 minutes per KOL. MSLs got faster researching KOLs. But more importantly, the team moved toward a more consistent way of preparing. 

Power users can help create that consistency and can create a disproportionate amount of value. They discover strong use cases, test new approaches, and make AI feel practical for less confident colleagues. But “ask Billy Bob, he’s good at Copilot” is not a sustainable plan. Without support, power users become the team’s unpaid AI help desk and burn out quickly. 

A structured Medical Affairs AI Champion Program gives them the tools, time, and boundaries to share what works. It also helps turn individual shortcuts into practices the whole team can use. 

Ask: Is AI helping a few people excel or lifting the performance of the whole team? 

5. Capacity Created: Decide What the Time Is For 

Time saved is useful. But what happens with that time savings becomes the impact story. Senior leadership loves seeing time savings, but after 6 months, they want to see more: "Ok, your time savings is cute, so what?" 

In one Insights Pro program, time to research the KOL before an upcoming meeting fell by 23 minutes while participants spent 11 more minutes planning stronger insights questions. AI did not just make the process faster. It moved effort toward being more strategic. 

We have seen this play out beyond a single exercise. In a 7-month program with a team of Medical Directors, meaningful AI use took 4-5 months and multiple training sessions. Then the Senior Director noticed a clear change: the team’s work had become more strategic. 

That is what real adoption often looks like. Not one exciting workshop. Practice, reinforcement, and enough time for new habits to show up in the work. 

For another team, we built an agent based on the team lead’s approach to coaching insights and trained the MSLs to use it. The manager now spends less meeting time covering the basics in one-on-ones. The conversation can move faster to strategy, stronger insights, and how she can help MSLs in the field. 

The impact is not simply minutes saved. It is better use of the manager’s expertise and more valuable coaching for the team. 

Recovered time does not automatically turn into value. If leaders do not decide where that capacity should go, it will disappear into inboxes and meetings. A team needs an explicit reinvestment choice: stronger KOL preparation, better insight interpretation, more coaching, deeper strategic planning, or another priority the organization can see and value. 

Ask: What better Medical Affairs work is AI creating room for and who can see the difference? 

What Medical Affairs Leaders Should Do Next to Build AI Ready Teams 

One AI session will not move an entire team from first login to strategic workflow design. The capability spread is too wide, and real integration into daily work and complex Medical Affairs workflows takes practice. 

Medical Affairs leaders should focus on: 

• Role-specific training tied to real Medical Affairs work (to supplement enterprise training) 

• Multiple touchpoints that help new habits stick (try adding some AI into your next meeting with this prompt) 

• A support program for AI champions to avoid burning them out and increase strategic use on the team 

• Shared workflows that power users help test and improve 

• Measures that connect AI use to stronger thinking, consistent execution, and visible impact 

The teams that stand out will not be the ones with the best adoption metrics. They will be the ones that can show how AI improved the work: better planning, deeper questions, more consistent preparation, stronger coaching, and more strategic conversations. 

The next competitive advantage in AI for Medical Affairs will not come from access to AI. It will come from making good performance repeatable. 

Build AI Readiness Across Your Medical Affairs Team 

MSL Mastery helps Medical Affairs teams turn scattered AI use into practical, role-specific capability. Our AI training and AI-enabled AI Champion Program help teams build the skills, workflows, and reinforcement needed to make adoption stick and show the impact. 

Set up some time to explore AI training for Medical Affairs teams. 

FAQ: AI in Medical Affairs 

What does AI readiness mean in Medical Affairs? 

AI readiness is a team’s ability to use approved AI tools effectively, validate outputs, apply compliance guardrails, integrate AI into real workflows, and turn the resulting capacity into better Medical Affairs work. 

How should Medical Affairs leaders measure AI adoption? 

Look beyond adoption metrics. Measure confidence in AI skills, meaningful AI use, workflow adoption, team consistency, and the capacity created for more strategic work. 

What is a Medical Affairs AI Champion Program? 

It equips selected influential team members to model effective practices, support peers, test use cases, and help improve shared workflows. Champions need clear responsibilities, protected time, and ongoing support. It's one of the best ways to create consistent and strategic AI use on your team.  

Is daily AI use a sign that a Medical Affairs team is AI-ready? 

Not by itself. In our baseline data, daily users still showed wide differences in prompting, validation, compliance, and workflow-integration confidence. Frequency of use should be evaluated alongside capability and the quality of the work.