Corporate teams use research to decide where to grow and how to respond to competitors. Consultants turn that evidence into client recommendations, while investor relations teams use it to prepare leadership and shape the company’s investor narrative. But their shared reliance on information doesn’t translate into a completely shared approach to AI.
Our 2026 State of AI for Business and Finance report shows how AI is changing research across corporate strategy and competitive intelligence (CI), consulting, and investor relations, with different reported benefits and adoption barriers in each group. Of the three segments, consulting uses AI less frequently, trusts it less, and discovers fewer novel insights through it. Respondents in corporate strategy and CI report that AI helps them reach decisions faster, while their organizations are the most likely to actively encourage its use. Investor relations uses AI the most and has the highest rate of negative consequences due to inaccurate AI, despite running the tightest tool governance of the three.
(Findings below draw on 349 respondents across three role-based segments: corporate strategy & competitive intelligence (200), consulting (111), and investor relations (38). Investor relations' smaller sample means its findings should be read as directional rather than conclusive.)
Usage, Trust, Verification, and Harm
Of the three segments, investor relations uses AI the most, verifies AI's output the least often, and has the greatest exposure to negative consequences from inaccurate or misleading AI output. Consulting trusts AI the least of the three (72%) and also uses it the least (53% use it at least once daily).
- Usage:
- Investor relations uses AI the most often; 74% use it at least once daily, compared with 65% overall.
- Among consulting respondents, 53% use AI at least once daily, the lowest of the three segments.
- Verifying AI output:
- All three segments verify AI output always or often less frequently than the 79% overall rate.
- Investor relations is lowest at 71% verifying always or often.
- Investor relations also has the most respondents who rarely verify AI output: 10%, double the 5% overall rate.
- Trust:
- Consulting trusts AI tools the least. 59% trust consumer-grade AI tools, compared with 68% overall, while 72% trust enterprise-grade AI tools, compared with 78% overall.
- Negative consequences from inaccurate or misleading AI output:
- Investor relations has the highest rate of experiencing negative consequences due to inaccurate or misleading AI output at 79% (vs. 62% overall). 45% say inaccurate or misleading AI output caused them to mislead or misinform a customer or colleague, much higher than the overall rate of 18%.
- Corporate strategy and CI have the lowest rate of the three at 60%, slightly below the 62% overall rate.
Decision-Making Confidence and Insight Discovery
Investor relations reports the strongest gains in decision confidence and decisions later appreciated. Corporate strategy and CI decide fastest. Consulting is least likely to discover information through AI that it would not have found otherwise.
- Investor relations: 61% say AI increases their confidence in the decisions they make, compared with 55% overall. 63% say it led to decisions they later appreciated, compared with 47%.
- Corporate strategy and CI: 67% say AI helps them arrive at decisions more quickly, higher than consulting (61%) and investor relations (63%), and higher than the overall rate (64%).
- Consulting: 12% rarely or never discover novel insights through AI, the highest share of the three segments. And only 30% use AI to find a novel insight at least once daily, compared with 40% overall.
Approved Tools and Formal AI Policies
Investor relations respondents are most likely of the three segments to report using only approved AI tools. They also report the highest rate of formal AI mandates. Corporate strategy and CI, meanwhile, report the highest rate of organizations actively encouraging AI use.
Run no unapproved AI tools:
- Investor relations leads at running no unapproved AI tools: 58%, compared with 49% overall.
Formal AI mandate:
- Investor relations also has the highest rate of a formal AI mandate at 24%, compared with the 14% overall average.
- Consulting is lowest at 7%.
Active encouragement:
- Corporate strategy and CI lead here, with 37% saying AI use is actively encouraged in their organization, above consulting (28%), investor relations (26%), and the 33% overall rate.
Sharing Research and Improving Consistency
Investor relations leads when it comes to AI making it easier to share research and findings internally and improving consistency of outputs across team members.
- Improved consistency across team members:
- Investor relations leads at 58%, compared with 47% overall.
- Corporate strategy and CI are lowest at 40%.
- Easier to share research:
- Investor relations leads again at 58%, compared with 50% overall.
- Consulting is lowest at 45%.
Security Is a Shared Concern
All three segments rank security among their top barriers to AI adoption in their organization. Security concerns hold back broader AI adoption for 45% of consulting respondents, 43% of investor relations respondents, and 37% of corporate strategy and CI respondents, similar to the 43% overall rate. Where they genuinely diverge is on other obstacles.
- Corporate strategy and CI: High implementation costs (32%) and lack of skilled personnel (30%) are the highest rates of the three. Resistance to change is comparatively low here: 23%, below the 29% overall rate, and the lowest of the three.
- Investor relations: Hallucinations and incorrect outputs (49%), resistance to change (43%), and regulatory compliance issues (35%) are all the highest of the three, with hallucinations standing out well above the 22% overall rate.
- Consulting: Regulatory compliance issues (31%) are its next-largest barrier to AI adoption, above the overall 28%, though lower than investor relations’ rate.
Feature Priorities: Accuracy Wins
Similar to the overall rankings, accuracy is the top feature when choosing an AI tool. However, investor relations stands out with its higher ranking for cost and data privacy and security.
- Accuracy: Accuracy is the most common first-ranked feature in all three segments: consulting and corporate strategy and CI are both at 25%, while investor relations is at 21%, compared with 24% overall.
- Investor relations: Cost and data privacy & security are each ranked first by 19%, compared with overall rates of 9% and 13%, respectively.
- Consulting: Only 4% rank cost first, the lowest share of the three segments.
AI Investment Expectations and Measures of Value
While still high, consulting trails relative to the other segments when it comes to the beliefs that AI budget will grow over the next twelve months and that non-adopters of enterprise-grade AI for research will underperform.
Expect AI budget to grow in the next 12 months:
- Consulting is lowest at 68%, below the 80% overall average.
Believe non-adopters of enterprise-grade AI for research will underperform:
- Consulting is lowest at 50% (vs. 60% overall).
- Investor relations is highest at 70%.
Measuring AI's value:
- Investor relations stands out with measuring AI through revenue growth or new revenue attributed to AI at 57%, well above the 38% overall rate and corporate strategy and CI (36%) and consulting (35%). It also leads in measuring risk reduction or compliance improvements, at 43%, compared with 33% overall.
- Corporate strategy and CI lead on employee productivity or time savings (49%) and cost savings or avoidance (44%). Those gains could free teams to assess more opportunities and examine competitive changes more closely.
What This Means
These three segments may depend on similar analytical and communication skills, but their AI profiles point to different sources of value and risk.
- Consulting: lower trust, lighter AI usage. Expects its AI budget to grow the least of the three and is also the least convinced that skipping enterprise-grade AI for research carries real competitive risk. Consulting also uses AI less frequently, trusts it less, and shows the weakest insight discovery of the three when using AI.
- Corporate strategy and CI: most encouraged, fastest decisions. Organizations here are more likely to actively encourage AI use. They also report the strongest decision-speed benefit and place the greatest emphasis on productivity and cost savings when measuring AI’s value. In addition, they have the lowest exposure to inaccurate or misleading output of the three but the highest concern about access to skilled personnel.
- Investor Relations: heaviest use, least caution, tightest governance. Combines the heaviest use, strongest decision confidence, and the highest rate of decisions later appreciated. It also has the strongest belief that firms that don’t adopt enterprise-grade AI for research will underperform. Yet it verifies least often, reports the most negative consequences from inaccurate AI, and voices the most concern about hallucinations — despite having the tightest tool governance of the three.
Each segment's path forward reflects its own mix of usage, trust, barriers, and governance. Corporate strategy and CI teams could assess AI in recurring research workflows, such as maintaining a competitive landscape, while tracking whether time savings translate into broader or deeper analysis. Consulting firms could test AI across a defined engagement workflow, from initial research to a well-sourced client recommendation, while measuring how often it surfaces something they wouldn't have found otherwise. For investor relations, the findings reinforce the importance of verification when preparing leadership materials.
Across all three, progress depends on closing the specific gap between how AI is being used today and what each segment needs to capture more value from it.
Methodology note: Findings are based on respondents identifying their primary role or department: Corporate strategy and competitive intelligence (200), consulting (111), and investor relations (38). Investor relations' smaller sample means its findings should be read as directional rather than conclusive.
For full findings, see The 2026 State of AI for Business and Finance.
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