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TransUnion Research Reveals Growing AI Confidence-Readiness Paradox Among Marketers

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TransUnion (NYSE: TRU) released research on AI adoption among 100 senior marketing and technology leaders at major U.S. brands, highlighting a “confidence-readiness paradox.” While 89% expect AI-enabled marketing investment to rise within 12–24 months and 64% feel confident about meeting AI marketing goals, only 42% rate people readiness and 36% rate data and process readiness as high. Fewer than half (48%) report sufficient visibility into platform-level AI to optimize confidently, and 65% mainly measure AI via time and cost savings rather than advanced techniques. The study identifies data fragmentation, walled-garden blind spots and cross-channel gaps as key barriers to measuring AI impact and achieving meaningful business outcomes.

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Market Context

Recent insider activity was classified as Net Selling, with 0 shares bought and 50,100 sold over 90 ...
Analysis

Recent insider activity was classified as Net Selling, with 0 shares bought and 50,100 sold over 90 days. Against this AI-readiness research, the platform record adds execution context; data transparency remains a risk to watch.

Key Figures

Survey Sample: 100 senior leaders Expected AI Investment Growth: 89% AI Goal Confidence: 64% +5 more
8 metrics
Survey Sample 100 senior leaders Senior marketing and technology leaders at major U.S. brands
Expected AI Investment Growth 89% Expect AI-enabled marketing investment to increase over the next 12 to 24 months
AI Goal Confidence 64% Confident they will achieve AI-enabled marketing goals
People Readiness 42% Rate organizational people readiness as high
Data and Process Readiness 36% Rate organizational data and process readiness as high
Platform AI Visibility 48% Say they have enough visibility to make optimization decisions confidently
Efficiency-Based Measurement 65% Measure AI success primarily through time and cost savings
Cross-Channel Blind Spots 70% Report difficulty understanding AI impact across the customer journey

Previous AI Reports

4 past events · Latest: Jun 03 (Positive)
Same Type Pattern 4 events
Date Event Sentiment 24h Move Catalyst
Jun 03 AI data expansion Positive -5.9% Expanded TruIQ data enrichment on Snowflake for prescreen credit marketing campaigns
Apr 16 AI fraud research Negative +1.1% Reported rising consumer losses and fraud exposure from increasingly sophisticated AI-enabled schemes
Mar 18 Machine learning capabilities Positive -0.8% Expanded device-security machine learning capabilities to improve fraud detection and reduce friction
Mar 05 AI analytics launch Positive +1.2% Launched AI Analytics Orchestrator Agent with Google Cloud Gemini and OneTru integration

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Pattern Detected

AI-tagged news produced 3 divergences and 1 alignment, with an average 24-hour move of -1.11%.

Key Terms

marketing mix modeling, multi touch attribution, incrementality testing, walled gardens
4 terms
marketing mix modeling technical
"advanced methodologies like marketing mix modeling, multi touch attribution and incrementality testing"
Marketing mix modeling is a data-driven method that measures how different marketing actions — like TV ads, online ads, promotions and pricing — have historically affected sales and customer behavior, while separating those effects from things like seasonality or the economy. For investors it reveals which marketing “ingredients” deliver the best return and helps predict how changes in spending or strategy are likely to affect future revenue, making budget decisions less guesswork and more evidence-based.
multi touch attribution technical
"advanced methodologies like marketing mix modeling, multi touch attribution and incrementality testing"
A method for assigning credit to the different interactions a potential customer has before a sale or conversion, rather than giving all credit to the last contact. Multi-touch attribution uses rules or statistical models to weigh advertising, email, social, search and other touchpoints so a company can estimate which channels contributed to a outcome. Investors care because these measurements affect reported marketing efficiency, customer acquisition costs, and revenue forecasting—similar to breaking down which runners in a relay helped win the race.
incrementality testing technical
"advanced methodologies like marketing mix modeling, multi touch attribution and incrementality testing"
Incrementality testing measures whether a specific action — such as an advertising campaign, promotion, or product change — actually causes additional customer behavior beyond what would have happened anyway. Think of it like watering some plants and leaving others dry to see if the water made a real difference; for investors, it shows which expenditures produce real, incremental returns versus those that just reassign or accelerate sales, helping assess true growth and the efficiency of spending.
walled gardens technical
"data blind spots within walled gardens limit their ability to evaluate AI effectiveness"
A walled garden is a closed digital ecosystem where a company controls which apps, services, data and transactions can enter or leave, limiting how easily users and partners can interact with outside platforms. For investors, that control can boost recurring revenue and customer loyalty—like a shopping mall that keeps shoppers and rents inside—but also concentrates regulatory, competitive and innovation risk if the market or rules push for more openness.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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AI investment is rising and confidence is strong, but a significant gap in people, process and data readiness remains a barrier to performance

CHICAGO, Aug. 05, 2026 (GLOBE NEWSWIRE) -- TransUnion (NYSE: TRU) today announced its research that found many organizations remain unprepared to scale AI effectively or clearly measure its business impact despite increasing investments in the capability.

TransUnion commissioned United Talent Agency’s (UTA) brand advisory division to survey 100 senior marketing and technology leaders at major U.S. brands. The findings reveal a confidence-readiness paradox. Marketers are increasingly confident AI will transform marketing, yet many lack the people, data and process foundations required to realize its full value, beyond efficiency improvements.

Defining the confidence-readiness paradox:

  • AI investment is accelerating: 89% of marketers expect investment in AI-enabled marketing initiatives to increase over the next 12 to 24 months.
  • Confidence outpaces readiness: 64% are confident they will achieve their AI-enabled marketing goals. However, only 42% rate their organization’s people readiness as high, while just 36% rate their data and process readiness as high.
  • Transparency is lacking: Fewer than half (48%) say they have enough visibility into platform-level AI to make optimization decisions with confidence.
  • Marketers are mostly focused on efficiency: 65% of marketers measure AI success primarily through time and cost savings, but less than half use more advanced methodologies like marketing mix modeling, multi touch attribution and incrementality testing.

"Marketers are increasingly confident in AI's ability to drive business results, but many are still working to build the foundations needed to scale it effectively," said Matt Spiegel, EVP, TruAudience Growth Strategy, TransUnion. "However, AI isn't a shortcut around data challenges. It's a force multiplier. Organizations that build strong foundations of trusted data, identity and measurement will be best positioned to close the gap between AI ambition and AI outcomes."

The Barriers to AI Readiness
The study found that data fragmentation remains one of the industry's biggest obstacles to AI readiness. The limitations inhibit marketers’ ability to evaluate AI’s effectiveness and achieve meaningful business outcomes.

Top concerns related to data fragmentation

  • 42% reported incomplete or missing data
  • 69% said data blind spots within walled gardens limit their ability to evaluate AI effectiveness
  • 70% said cross-channel blind spots make it difficult to understand AI's impact across the customer journey

As AI becomes more deeply embedded in marketing workflows, the findings suggest that transparency, independent measurement and connected data will become increasingly important competitive advantages.

"What this research makes clear is that AI success is no longer defined by access to the technology itself," said Michael Burke, principal at UTA Advisory. "The real differentiator is whether organizations can connect their data, measure outcomes and operationalize AI at scale."

Click here to read the full report exploring the AI confidence-readiness paradox and how marketers can leverage TransUnion’s robust data and connected identity to achieve meaningful ROI.

About TransUnion (NYSE: TRU)
TransUnion is a global information and insights company with over 13,000 associates operating in more than 30 countries. We make trust possible by ensuring each person is reliably represented in the marketplace. We do this with a Tru™ picture of each person: an actionable view of consumers, stewarded with care. Through our acquisitions and technology investments we have developed innovative solutions that extend beyond our strong foundation in core credit into areas such as marketing, fraud, risk and advanced analytics. As a result, consumers and businesses can transact with confidence and achieve great things. We call this Information for Good® — and it leads to economic opportunity, great experiences and personal empowerment for millions of people around the world. http://www.transunion.com/business

ContactDave Blumberg
 TransUnion
E-maildavid.blumberg@transunion.com
Telephone312-972-6646

FAQ

What is the AI confidence-readiness paradox highlighted by TransUnion (TRU) in August 2026?

The AI confidence-readiness paradox describes marketers’ high confidence in AI alongside low organizational readiness. According to TransUnion, 64% feel confident about AI goals, yet only 42% rate people readiness and 36% rate data and process readiness as high.

How much are marketers planning to increase AI marketing investment according to TransUnion (TRU)?

According to TransUnion, 89% of surveyed marketers expect AI-enabled marketing investment to increase over the next 12 to 24 months. This indicates rising AI spending even though many organizations still rate their readiness in people, data and processes as relatively low.

How are marketers currently measuring AI success in the TransUnion (TRU) 2026 study?

TransUnion reports that 65% of marketers primarily measure AI success through time and cost savings. Fewer than half use advanced methods like marketing mix modeling, multi-touch attribution or incrementality testing, limiting their ability to evaluate AI’s full business impact across channels.

Why does TransUnion (TRU) emphasize data and measurement foundations for AI in marketing?

TransUnion emphasizes that AI is a force multiplier, not a shortcut around data problems. The company says organizations with trusted data, connected identity and robust measurement will be better positioned to translate AI investments into measurable marketing outcomes and meaningful return on investment.

What role does AI transparency play in marketing performance according to TransUnion (TRU)?

According to TransUnion, fewer than half (48%) of marketers have enough visibility into platform-level AI to optimize confidently. The research suggests that transparency, independent measurement and connected data will increasingly differentiate marketing performance as AI becomes embedded in workflows.