Pharma
99 documented deployments, 2.5% of the record. What they do, what they report and how they are built.
Data updated
The read
Written 19 Jun 2026 from 40 representative deployments. The figures on this page are live.
Pharma AI adoption is concentrated in two repeatable patterns: drug discovery and preclinical acceleration, and document-heavy workflow automation. The first targets slow, high-failure, high-cost R&D by using computational modeling, data unification, and agentic orchestration to improve target discovery, candidate evaluation, and simulation workflows; the second tackles fragmented manual lab, regulatory, and scientific writing processes through assistants, document processing, compliance automation, and data extraction. Clinical-trial optimization, pharmacovigilance, manufacturing quality, and track-and-trace appear, but are less prominent. Overall, adoption looks most mature where AI augments existing workflows; more autonomous agentic orchestration is emerging but still experimental.
What is distinctive about Pharma
Drug discovery is 47.6× more common here than across the whole record.
Lift compares a pattern’s share of deployments here with its share everywhere. 1× means no difference.
- Drug discovery18 here of 21 in total47.6×
- Life sciences innovation9 here of 12 in total41.6×
- Compliance automation5 here of 76 in total3.6×
- Patient engagement5 here of 81 in total3.4×
The most common patterns
Drug discovery leads with 18 deployments from 14 organizations.
- Drug discovery14 organizations · 7 in the last 6 months18
- Life sciences innovation9 organizations · 2 in the last 6 months9
- Compliance automation5 organizations · 0 in the last 6 months5
- Patient engagement3 organizations · 0 in the last 6 months5
- Therapeutics research3 organizations · 0 in the last 6 months4
- Risk assessment3 organizations · 0 in the last 6 months3
- Clinical documentation copilot2 organizations · 1 in the last 6 months2
- Cloud migration agent2 organizations · 2 in the last 6 months2
Across business functions
Operations accounts for the most deployments here: 74.
A deployment can serve several functions.
- Operations75% of this dossier74
- Research & Development74% of this dossier73
- Legal & Compliance51% of this dossier50
- Human Resources47% of this dossier47
- Supply Chain26% of this dossier26
- Marketing17% of this dossier17
- Finance16% of this dossier16
- Customer Service6% of this dossier6
What deployments here report
33 Pharma deployments publish a quantified result.
Time & speed
29 metrics
Reduction · median and middle half−50%fewMedian reduction −50%, middle half −50% to −61%, from 4 metricsIncrease · median+71%2 metrics · fewCost savings
8 metrics
Reduction · median and middle half−53%Median reduction −53%, middle half −40% to −66%, from 6 metricsProductivity & throughput
5 metrics
No reductions reportedIncrease · median+105%4 metrics · few
Grey figures rest on fewer than 5 published metrics. Read them as examples, not as a typical result.
How it is built
Microsoft appears in 57% of these deployments.
- Custom-built79% · 58
- Low-code10% · 7
- Bought5% · 4
- Mixed5% · 4
The build approach is known for 73 of 99 deployments (74%). The rest are left out.
Cloud providers named
Compare providers across all industries- Microsoft56 deployments57%
- AWS32 deployments32%
- GCP11 deployments11%
The highest-ranked deployments
Ranked by innovativeness adjusted for age. Every figure above is computed from records like these.
Only records with high or medium evidence strength are ranked.
No records to show yet.