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New research report

State of Pharma Intelligence 2026

How 130 pharma leaders are using AI and why only a quarter report high trust in it.

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Cover of the State of Pharma Intelligence 2026 report, The Confidence to Act
92%
say AI changed a recent decision
26%
report high trust in its output

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Key findings

Where trust, visibility, and speed fall short

Pharma teams are already using AI to make real decisions. What holds them back is trust in the output, visibility into China, and the time it takes to screen a partner.

How far do pharma teams trust AI?

84%

use expert or analyst review to check AI output before it informs a decision.

Use expert or analyst review84%
Cross-check with a second source or tool69%
In the full reportWhy teams using three or more validation methods are three times as likely to report high trust

Why is China hard for pharma teams to read?

45%

see China as the biggest opportunity for external innovation over the next five years.

See China as the top opportunity45%
Feel confident in their visibility into China22%
In the full reportHow US and European views of China split

Why does partner screening take so long?

77%

need three weeks or more to produce initial screening intelligence on a potential partner. Only 23% do it within two weeks.

Need 3+ weeks to screen a partner77%
Say internal alignment slows them most48%
In the full reportWhy teams with dedicated AI/ML staff are three times as likely to have advanced automation

Inside the report

What’s in the full report

  1. 01

    How trust in AI changes with each stage of adoption, and the validation practices linked to higher trust

  2. 02

    The leading barrier to a clear view of China, and how confidence in that view changes what teams do

  3. 03

    How a shared evidence base and data quality relate to partner screening timelines

  4. 04

    The automation plateau: where company size stops mattering, and what dedicated AI/ML staff change

  5. 05

    Four priorities for trusted intelligence, with the data behind each

A look inside

Preview the report

Report page showing trust in AI output and trust by AI adoption stageIn the full report
How trust in AI rises with adoption. Trust in AI output climbs as teams move from early to advanced adoption.
Report page comparing US and European views of the biggest innovation opportunityIn the full report
Where US and European leaders see the biggest opportunity. 59% of European leaders and 28% of US leaders rank China first.
Report page showing partner screening timelines and constraintsIn the full report
How long initial partner screening takes. 77% need three weeks or more, and 23% finish within two weeks.
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In their words

AI needs to prove it is safer, more consistent, and more accountable than the current manual process.
Senior R&D strategy leader, US CDMO

31%

of respondents name trust in AI output as the biggest barrier to getting more value from AI.

About the research

Why we ran this survey

Pharma teams make high-stakes R&D, pipeline, and deal decisions against fast-moving scientific, clinical, patent, and commercial evidence. We set out to understand how AI is influencing those decisions, what builds confidence in its output, and where intelligence workflows still fall short.

The report is written for the leaders who turn that evidence into decisions.

Fielded in August 2026 with NewtonX, the survey reached 130 respondents at director level and above. Published November 2026.

Who took part

By function

R&D strategy
40%Business development
27%Data sciences
15%Competitive intelligence
12%Other
6%

By organization

Drug developers
66%CDMOs and CMOs
18%Consulting
6%CROs
5%Other
5%

By country

United States
46%United Kingdom
18%Germany
17%Switzerland
11%France
8%

See what 130 pharma leaders told us and how your team compares.

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