The 2026 Pharma CI USA Conference in New Jersey brought together competitive intelligence, market research, and insights leaders from across the life sciences industry. AI was part of nearly every conversation. But the more important story was what those conversations signal about the role of CI itself.
Getting information to leadership quickly is now expected. What sets a CI team apart is its ability to interpret that information and point to what matters most.
Leadership expectations are rising, information is more accessible than ever, and AI is absorbing much of the routine work. The discussions in New Jersey made one thing clear: CI’s value is increasingly measured by the quality of the decisions it shapes, not the volume or speed of what it delivers.
Sedulo Group had the opportunity to present findings from the 2026 Life Sciences Competitive Intelligence Survey Report, and several of those findings resurfaced in panel discussions throughout the event.
What’s Changed: Key Takeaways
Several clear shifts emerged throughout the conference:
- AI adoption is broad, but trust and governance determine whether it scales
- Automation is absorbing monitoring work, raising the value of primary intelligence
- Leadership expects a strategic partner, not an information provider
- Narrative has become a core CI competency
- CI is engaging earlier in the asset lifecycle and covering more ground
- CI structures and skill sets are still evolving
AI Is Everywhere, but Trust Decides Whether It Scales
Nearly every CI team in attendance is using AI to automate some part of the workflow, and a growing number have built proprietary tools of their own. Enthusiasm was real, but so was caution.
A recurring point was that the model itself is rarely the bottleneck. Trust is. Industry data shared at the event showed that 60% of AI projects are abandoned after proof of concept and 95% of enterprise generative AI pilots never reach production. Source traceability, properly licensed content, and verification are what separate tools that scale from pilots that stall.
The room reflected that tension. In one audience poll, 54% of attendees reported only medium confidence in their LLM, while 23% said they were highly confident. One leader shared that rolling out an AI-assisted CI newsletter took roughly eight months of trial and error, and that current tools still cannot independently produce validated implications for senior leadership.
points the same way. Applied or Developing AI usage rose to 53.9%, nearly double last year’s 29%, yet adoption and trust are still maturing together.
Automation Is Raising the Value of Primary Intelligence
Most of the AI applications discussed were focused on monitoring: filtering press releases, news, trial updates, and alerts, then drafting summaries. That is where automation is landing fastest.
As AI takes on more secondary work, the balance of effort shifts toward primary intelligence. Pharma leaders were clear that strong internal AI tools do not replace primary research. AI tends to skew toward a dominant perspective, overlook outliers, and miss when information is wrong or out of date. Human sources, expert conversations, and on-the-ground insight fill those gaps.
Leaders also noted that stakeholders lose trust quickly when deliverables read like unedited AI output.
From Information Provider to Strategic Partner
CI has evolved from a library and retrieval function into a strategic, integrated partner. As information has become widely accessible, expectations have risen. The value now lies in delivering the right insight to the right person, at the right level, at the right time.
Speakers described what separates strategic partners from information providers:
- Being proactive, flagging developments before being asked, with implications and not just facts
- Earning trust over time by consistently having leadership’s back
- Being willing to deliver unwelcome news when the evidence supports it
One memorable benchmark came from a chief of staff who would take a 40 to 60 page report and reduce it to the three things a senior leader actually needed to know. Several leaders described curated executive briefings built on that same principle.
That shift is showing up in the data. In Sedulo Group’s 2026 Life Sciences CI Survey Report, 46.1% of CI leaders said CI plays a critical and consistent role in strategic planning, up from 41% in 2025.
Narrative as a Core Competency
Speed of information still matters, but it was repeatedly treated as the baseline rather than the differentiator. What leaders want is a partner who understands the story and can explain why a new piece of intelligence matters to the broader landscape.
Data informs, but stories motivate action. One session made the point by presenting the same research finding twice, first as a statistic and then as the story of a single patient. The difference in impact was immediate.
The practical guidance was consistent: lead with the key takeaways, keep one clear throughline, cut anything that does not support it, and interpret findings for cross-functional audiences rather than simply translating them. This matters even more as insights move from management teams to the C-suite.
Earlier Engagement and a Broader Remit
CI is being pulled into decisions earlier than ever, including early investment and go/no-go calls, sometimes on preclinical data. Panelists referenced a finding from Sedulo Group’s survey presentation: CI is now engaging roughly 30% earlier in the asset lifecycle than two years ago, which they confirmed matched their own experience.
Earlier involvement brings its own discipline. Teams described avoiding overreaction to a crowded early landscape by focusing on the two or three competitors most likely to reach market, and using structured threat rankings that weigh revenue potential, M&A activity, and signals such as analyst questions on earnings calls.
The remit is also widening. CI teams are increasingly expected to cover policy and regulatory intelligence, including IRA-driven shifts in launch sequencing, and to bring a macro industry view alongside brand-specific work. Discussions on global CI reinforced the need for on-the-ground sources, citing a case in China where a competitor entered trials later but reached market first by accelerating enrollment.
Structure and Skills Are Still Evolving
Many organizations are still working out where CI sits and how it connects to adjacent functions. The ideal described at the event is a continuous insights cycle in which CI, market research, forecasting, and analytics inform each other, rather than passing work along in a linear handoff.
Hiring is shifting as well. Rather than recruiting a single CI profile, leaders are filling specific gaps: life sciences knowledge, consulting-style stakeholder skills, comfort with structured data, and in some cases, dedicated roles focused on AI for CI.
What This Means for Life Sciences Organizations
The themes from Pharma CI USA 2026 raise practical questions for CI leaders across the industry:
- Is AI being used to sharpen judgment, or simply to process more information faster?
- As monitoring becomes automated, is primary intelligence getting the investment it now deserves?
- Are insights reaching leadership as a clear story with a “so what,” or as a stack of findings?
- Is CI engaged early enough in the asset lifecycle to shape decisions, rather than react to them?
The risk of standing still is real. Teams that remain reactive information providers will find it harder to earn a seat at the table as expectations rise.
The opportunity is just as clear. Teams that pair governed AI with strong primary intelligence and compelling narrative will be better positioned to anticipate change and influence the decisions that matter most.
Looking Ahead
The conversations in New Jersey reinforced a message we also heard at 2026 Pharma CI Europe earlier this year in Frankfurt. The future of competitive intelligence is not purely technological or purely human. It is a hybrid model, and the value lies in how well the two work together.
CI is moving earlier, reaching higher, and being measured by the quality of decisions it influences. The organizations that adapt now will be best positioned to lead in an increasingly complex market.