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02 · Insights— The analysis

Pharma

99 documented deployments, 2.5% of the record. What they do, what they report and how they are built.

Data updated

99
deployments
on record
19%
use AI agents
19 deployments
3.2
average innovativeness, 1 to 5
Differentiated
published in the last 6 months
8 in the 6 months before
§ 1

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.

§ 2

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.

  1. Drug discovery18 here of 21 in total
    47.6×
  2. Life sciences innovation9 here of 12 in total
    41.6×
  3. Compliance automation5 here of 76 in total
    3.6×
  4. Patient engagement5 here of 81 in total
    3.4×
§ 3

The most common patterns

Drug discovery leads with 18 deployments from 14 organizations.

  1. Drug discovery14 organizations · 7 in the last 6 months
    18
  2. Life sciences innovation9 organizations · 2 in the last 6 months
    9
  3. Compliance automation5 organizations · 0 in the last 6 months
    5
  4. Patient engagement3 organizations · 0 in the last 6 months
    5
  5. Therapeutics research3 organizations · 0 in the last 6 months
    4
  6. Risk assessment3 organizations · 0 in the last 6 months
    3
  7. Clinical documentation copilot2 organizations · 1 in the last 6 months
    2
  8. Cloud migration agent2 organizations · 2 in the last 6 months
    2
8 of 20 patterns
§ 4

Across business functions

Operations accounts for the most deployments here: 74.

A deployment can serve several functions.

  1. Operations75% of this dossier
    74
  2. Research & Development74% of this dossier
    73
  3. Legal & Compliance51% of this dossier
    50
  4. Human Resources47% of this dossier
    47
  5. Supply Chain26% of this dossier
    26
  6. Marketing17% of this dossier
    17
  7. Finance16% of this dossier
    16
  8. Customer Service6% of this dossier
    6
§ 5

What deployments here report

33 Pharma deployments publish a quantified result.

  1. Time & speed

    29 metrics

    Reduction · median and middle half
    −50%fewMedian reduction −50%, middle half −50% to −61%, from 4 metrics
    Increase · median+71%2 metrics · few
  2. Cost savings

    8 metrics

    Reduction · median and middle half
    −53%Median reduction −53%, middle half −40% to −66%, from 6 metrics
  3. Productivity & throughput

    5 metrics

    No reductions reported
    Increase · median+105%4 metrics · few

Grey figures rest on fewer than 5 published metrics. Read them as examples, not as a typical result.

§ 6

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.

  1. Microsoft56 deployments
    57%
  2. AWS32 deployments
    32%
  3. GCP11 deployments
    11%
§ 7

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.