How to Apply the LIFT/Drag™ Formula to Your AI Readiness

AI is no longer a theoretical ambition in biopharma—it’s a business mandate. Some organizations are already using AI to streamline clinical trials and automate regulatory responses. Others are still locked in endless pilot cycles and vendor evaluations. I've seen companies recycle the same pilots just swapping out vendors. The difference isn't access to technology. It’s how the organization is structured to absorb and scale it. Through my work advising across tech startups and multinational pharma companies, one theme consistently emerges: companies don't fail at AI because they lack tools—they fail because they lack readiness and real commitment.  That insight led me to create the LIFT Score™—a practical framework any organization or department can use to assess whether their AI strategy is primed for execution or destined for inertia.

The LIFT Formula

LIFT = (Leadership + Investment + FTEs + Talk) ÷ Drag

Each element is scored from 1 (low) to 5 (high): -

LEADERSHIP: Strength of executive sponsorship and AI advocacy

INVESTMENT: Actual budget committed to AI initiatives

FTEs: Internal headcount dedicated full-time to AI strategy and execution

TALK: Corporate public visibility of your organization’s AI ambition (e.g., press releases, investor presentations, conference keynotes, etc)

DRAG: Degree of organizational risk-aversion and functional friction, especially across enabling functions like Legal, Compliance, IT, and Procurement

The higher your LIFT score, the more likely your AI strategy will take off. The lower the score, the more likely it will stall—regardless of technical capability.

Three Biopharma Profiles in Flight (Hypothetical / Self Rating)

1. Company A — Large Multinational Pharma

Leadership = 3 Investment = 3 FTEs = 2 Talk = 4 Drag = 4

LIFT = (3 + 3 + 2 + 4) ÷ 4 = 12 ÷ 4 = 3.0

Verdict: Ambition is high, but structural risk-aversion is higher. Despite a visionary senior leadership and some recurring budget, execution gets bogged down in process. Legal reviews, IT security assessments, and vendor onboarding stretch timelines longer than the projects themselves. AI is present, but progress is unevenly obtained.

2. Company B — Small Biotech, Phase 3

Leadership = 5 Investment = 3 FTEs = 3 Talk = 4 Drag = 2

LIFT = (5 + 3 + 3 + 4) ÷ 2 = 15 ÷ 2 = 7.5

Verdict: Focused and aligned. This organization sees AI not as an operational necessity. Senior leadership sponsors it, and internal blockers are minimal. Despite lean resources, the alignment across Medical and Regulatory drives velocity. Execution beats aspiration. The stakes are high, but pay-off can be huge--and truly transformative.

3. Company C — Mid-Size Biopharma

Leadership = 5 Investment = 4 FTEs = 4 Talk = 4 Drag = 2

LIFT = (5 + 4 + 4 + 4) ÷ 2 = 17 ÷ 2 = 8.5

Verdict: Positioned to scale. Here, AI isn’t off to the side—it’s embedded in each function with a dedicated AI Lead that is senior and fully-allocated. Dedicated teams are in place, budget has been allocated for experimentation, and enabling functions act as partners early and upfront. Governance models keep things moving while managing risk. This is what enterprise AI readiness looks like.

Final Thought

AI readiness isn’t a technology problem—it’s a structural one. That’s why every successful digital transformation is ultimately a behavioral transformation.

You cannot lift your organization with AI if drag dominates your enterprise. The key is to align up front—make it a team effort to reduce the drag—otherwise, your AI projects will be exactly that: a drag.

If you’d like further explore your organization’s LIFT Score™ and how to improve it versus peer companies, I’m happy to help. 

Framework developed by RS Consultative, LLC™         

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