Data governance gap exposes AI confidence crisis across industries

The greatest threat to artificial intelligence adoption isn't inadequate models or insufficient computing power. It's data discipline. Publicis Sapient's 2026 Guide to Next industry trends report, released in November 2025, exposes a stark reality: organizations are failing at AI not because their algorithms are flawed, but because the data feeding them is inconsistent, fragmented, and ungoverned.

"AI won't fail for lack of models. It will fail for lack of data discipline," the report states definitively. "AI projects rarely fail because of bad models. They fail because the data feeding them is inconsistent and fragmented."

The consultancy surveyed more than 500 industry leaders and interviewed nearly 70 experts between September 2025 and publication. Research conducted by IPSOS spanned five industries—consumer products, retail, transportation and mobility, telecommunications, and media—across seven markets. The findings document a fundamental disconnect: while the majority of executives claim their AI technology and programs are scaled or enterprise ready, most organizations remain in pilot mode with inadequate data governance frameworks.

According to Publicis Sapient's Energy Report, 63 percent of energy leaders identified poor data quality as a top barrier to drawing insights. Fifty-one percent pointed to siloed or inaccessible data as a major challenge. In telecommunications research, 61 percent of executives said technical data debt delays customer experience innovation. These numbers reveal that data governance has become the defining fault line separating AI success from failure.

Guy Elliott, Consumer Products, Retail, Telco, Media and Tech Industry Lead for EMEA and APAC at Publicis Sapient, captured the crisis precisely: "Executives are mistaking generative AI experimentation, use of ChatGPT or Copilot, and/or machine learning usage for full integration. Confidence without measurement is belief, not certainty."

The report introduces "decision debt" as its central concept—scenarios where optimism moves faster than evidence and assumptions scale before systems do. Without clean, connected, and governed data, organizations cannot prove their AI systems work as intended, cannot measure whether algorithms reflect brand values rather than generic efficiency targets, and cannot scale autonomous systems reliably. Data governance has emerged not as a technical requirement but as a strategic imperative determining which organizations will succeed in the AI-driven economy.

"Every year, 'Guide to Next' is our chance to take a clear-eyed look at what's coming," according to the report's editorial team. "But this year, the stakes feel higher—the decisions heavier, the bets bigger."

The consultancy's research methodology required all 540 participants to hold C-suite positions or direct reports with recognized decision-making authority. Eligibility criteria mandated senior management roles of at least one year at organizations with revenues exceeding $1 billion and workforces of 1,000 employees or more. All participants held direct responsibility for selecting external consultants and service providers for digital transformation initiatives.

2023: The foundation year

The 2023 Guide to Next report focused primarily on post-pandemic digital transformation and customer experience priorities. The findings centered on customer engagement challenges, particularly in the transportation sector where Publicis Sapient's 2023 European Car Ownership Report discovered that 50 percent of car owners never interact with their vehicle's brand beyond the initial purchase.

Of customers who did engage, only 7 percent interacted via an official brand app. The remaining 93 percent represented customers that original equipment manufacturers weren't making efforts to engage with beyond their initial purchase. The 2023 report emphasized that brands capitalizing on engagement tools like mobile apps had opportunities to massively increase lifetime value of currently inactive customers.

Sustainability emerged as a major concern. The transportation industry produced more emissions than any other sector, with over 243 million Americans using cars as their primary transportation method. Climate change awareness drove considerable impact predictions for the transportation sector, though the report noted that electric vehicle mandates remained on the horizon rather than immediate reality.

Connectivity represented a crucial factor for improving customer lifetime value. The 2023 research emphasized leveraging connectivity of apps and in-vehicle infotainment systems to enhance the in-vehicle experience, thereby improving customer satisfaction and building brand loyalty. Data privacy concerns surfaced significantly, with Publicis Sapient's 2023 Customer Data Survey revealing that 44 percent of consumers were unwilling to share their data with any company.

The 2023 report positioned AI as an emerging technology requiring careful consideration of use cases and implementation strategies, but the technology remained largely in early adoption phases across most industries.

2024: The experimentation phase

By 2024, artificial intelligence had advanced from experimental to practical consideration. The Guide to Next 2024 documented growing confidence in AI capabilities while highlighting persistent challenges around implementation and scaling. The report emphasized customer lifetime value maximization as organizations moved away from traditional single-transaction models toward long-term customer relationships.

Sustainability became more urgent. Wildfires across the United States and record temperatures in mainland Europe and China pushed climate considerations to the forefront. The 2024 report noted that as electric vehicle mandates edged closer to reality, sustainability looked set to dominate headlines and corporate agendas. One of the most discussed technical advancements became artificial intelligence, with established original equipment manufacturers giving AI and connected data considerable attention.

Retail media networks began serious expansion. The 2024 report predicted that retailers would find profitability from expanding their advertising capabilities and creating networks in new non-U.S. markets. Retail media was rapidly evolving from a U.S.-centric grocery phenomenon to a global competitive landscape. The report noted that retailers needed to contribute data to marketplaces and create bigger clean rooms where everyone participates in data sharing.

Generative AI began transforming specific use cases. The 2024 research documented early successes in supply chain optimization, predictive maintenance, and customer service automation. However, most implementations remained pilots rather than enterprise-wide deployments. Retail executives identified cost reduction as the number two generative AI transformation goal, behind increasing productivity, reflecting economic pressures facing the industry.

The 2024 report emphasized data strategy maturity as a critical differentiator. Transportation industry research found that only 3 percent of surveyed C-suite executives claimed to have a mature enterprise data strategy that had been fully integrated and leveraged in their business. Twenty-seven percent had only some strategies, while 37 percent described a "well-defined strategy" in place.

Privacy and personalization tensions increased. The 2024 findings noted that 51 percent of consumers wanted clear explanations of how data is used, 53 percent wanted opportunity to opt out at any time, and 46 percent wanted companies to comply with privacy laws and regulations. These concerns created challenges for organizations attempting to leverage connectivity for personalized services.

2025: The acceleration year

The 2025 Guide to Next characterized the year as AI's "playground year," with organizations exploring applications across operations. Economic instability and widening income inequality dominated the landscape, forcing creative cost-cutting measures and growth strategies. Inflation remained significant—hovering around 3 percent throughout 2024 in the United States and not expected to drop to 2 percent until 2025 or later.

Generative AI turned shoppers into co-creators. Rather than using customer demographics and historic purchasing data to tailor shopping experiences, generative AI enabled customers to organically reveal shopping intent in real time and personalize journeys as they progressed. Retailers no longer guessed based on customer data—they conversed with customers in real time. According to Publicis Sapient research, 63 percent of retail executives believed personalization or hyper-personalization would be "very or extremely important" to their organization's application of generative AI in the next three years.

Retail media monetization became imperative. The 2025 report emphasized that retailers who hadn't yet launched retail media networks needed to explore data co-ops and other data-sharing opportunities. Retail media networks were rapidly evolving, with industry analysis showing that global advertising spend reached $29 billion, excluding Amazon's contribution.

Transportation platforms emerged. The 2025 research documented the shift toward software-defined vehicles that evolved with regular updates, like smartphones. Rajeev Singh, Transportation & Mobility Industry Leader for EMEA & APAC, stated that "after six months or a year, the same vehicle gives the driver a new experience because the manufacturer introduced a feature over the air."

However, organizational maturity lagged behind technology readiness. Only 34 percent of original equipment manufacturers considered themselves mature in executing over-the-air updates, while the majority—58 percent—remained in scaling phases. This gap between capability and execution foreshadowed the larger confidence-capability divide that would define 2026.

Energy sector AI adoption accelerated. The 2025 report predicted AI would be worth $4.6 billion by 2032 for the renewables market alone. Use cases emphasized AI's power in driving data-driven decisions and supporting customers through chatbots, with 2025 expected to see more proofs of concept transitioning into full-scale implementations.

Electric vehicle adoption hit complications. After periods of hype and aggressive launch timelines, many auto manufacturers walked back or delayed commitments. EV purchases hit a plateau despite industry giants' efforts. Cost and convenience continued playing factors—EVs remained more expensive than gas-powered cars, charging infrastructure remained inadequate, and total ownership costs exceeded what many drivers could justify.

2026: The reckoning

The 2026 Guide to Next, released in November 2025, marks a stark departure from previous years' optimism. The report introduces "decision debt" as its central concept—scenarios where optimism moves faster than evidence and assumptions scale before systems do. This phenomenon has become the defining fault line in enterprise AI adoption.

The research reveals that across Publicis Sapient's industry surveys, the majority of executives say their AI technology and programs are scaled or enterprise ready. Yet the data, and the experts interviewed, reveal a different story: most organizations are still in pilot mode. Confidence is outpacing capability, creating what the report calls "the new fault line in enterprise AI."

Guy Elliott, Consumer Products, Retail, Telco, Media and Tech Industry Lead for EMEA and APAC at Publicis Sapient, stated that "executives are mistaking generative AI experimentation, use of ChatGPT or Copilot, and/or machine learning usage for full integration. Confidence without measurement is belief, not certainty."

Industry-specific data exposes the extent of this confidence-capability mismatch. Media leaders report that consent-first user experience design boosts trust, yet over half cite privacy as AI's top barrier. Among consumer products executives, a significant percentage audit how AI assistants describe their brands each month. Transportation executives indicate readiness to monetize in-car AI capabilities, but only one-third have achieved scale. Retail leaders claim preparedness for agent-to-agent commerce despite the technology remaining largely theoretical.

The 2026 report identifies four critical tensions. Originality versus sameness threatens organizations relying on off-the-shelf AI, creating what the report calls "a race to the bottom" where efficiency without distinctiveness makes competitors indistinguishable. Breakthrough versus bottleneck requires organizations to deploy agents to shorten delivery cycles and reimagine design, then scale with intent using clean, connected, and governed data.

Decisions versus deferrals addresses accumulated technical debt. Years of old systems, deferred decisions, and fragile fixes cannot be covered by agentic AI—instead, such systems expose these structural weaknesses. Routine versus reinvention demands organizations redefine roles, placing humans in decision loops for judgment, ethics, and context while building systems reflecting brand identity rather than cost optimization alone.

Data governance emerges as the critical factor. "AI won't fail for lack of models. It will fail for lack of data discipline," the report states. "AI projects rarely fail because of bad models. They fail because the data feeding them is inconsistent and fragmented."

According to Publicis Sapient's Energy Report, 63 percent of energy leaders identified poor data quality as a top barrier to drawing insights. Fifty-one percent pointed to siloed or inaccessible data as a major challenge. In telecommunications research, 61 percent of executives said technical data debt delays customer experience innovation.

Expected impacts and strategic imperatives

The 2026 findings carry immediate implications for marketing professionals as platform consolidation accelerates and major advertising technology providers integrate AI capabilities across their ecosystems. The gap between stated readiness and actual governance represents the primary challenge facing marketing organizations.

Investment patterns reflect industry momentum despite implementation challenges. Artificial intelligence attracted $124.3 billion in equity investment during 2024, representing the highest funding levels among 13 analyzed trends in McKinsey's research. Digital trust and cybersecurity technologies received $77.8 billion, while cloud and edge computing secured $80.8 billion.

McKinsey's Technology Trends Outlook 2025, published in July 2025, identified agentic AI as the most significant emerging trend for marketing organizations. Job postings related to agentic AI increased 985 percent from 2023 to 2024. Equity investment in agentic AI reached $1.1 billion during 2024.

The marketing technology ecosystem responds rapidly. Amazon launched agentic capabilities across its advertising platform on November 11, 2025, transforming tools from question-answering systems into autonomous agents that monitor accounts, optimize inventory, and manage campaigns. The system processes natural language instructions to execute complex workflows including campaign creation, audience targeting, and analytics query generation.

IAB Tech Lab released the Agentic RTB Framework version 1.0 for public comment on November 12, 2025, establishing standardized specifications for deploying containerized agents within real-time bidding infrastructure. Six companies launched the Ad Context Protocol on October 15, betting that open-source technical standards could enable AI agents to communicate across platforms and execute advertising tasks autonomously.

Google's advertising leadership maintained that ads are not disappearing despite AI transformation. Robby Stein, VP of Product for Google Search, stated on October 30, 2025, that he doesn't see Google Ads going away. The executive leads teams responsible for search ranking mechanisms affecting billions of daily queries and over one million active advertisers globally.

Platform automation faces scrutiny. Meta's AI advertising strategy draws criticism as Advantage+ becomes the default campaign setup for sales, leads, and app campaigns. As of 2025, Advantage+ creative enhancements activate by default, with detailed targeting expansion mandatory for link clicks and landing page views as of January 2024. The company removed detailed targeting exclusions entirely in January 2024, citing 22 percent better performance without them.

Retail media networks continue expansion despite AI uncertainty. IAB Europe analysis published on November 6, 2025, documented convergence between retail media and connected television. Retail media advertising spend on connected television is projected to grow three times faster than retail media search. The sector is projected to capture 20 percent of global advertising revenue by 2030, representing approximately $300 billion in spending.

Measurement infrastructure transforms. LiveRamp announced expanded capabilities on October 23, 2025, allowing retail media networks to analyze Meta advertising through its Clean Room platform. The functionality enables retailers to connect Meta campaign results with their own sales information in privacy-safe environments.

The healthcare sector's AI challenges center on access rather than diagnosis. Healthcare organizations must address invisible systems delaying care rather than focusing solely on AI-powered diagnostic capabilities. Financial services face a $124 trillion wealth transfer, with more than $100 trillion coming from Baby Boomers and older generations flowing to millennials and Gen Z—the first truly digital-native wealth holders.

Energy sector findings emphasize that companies winning in 2026 will be those deciding fastest and best, not necessarily those with the most assets. The report notes that what people are realizing is that optimizing functional silos isn't enough—organizations need to optimize the system as a whole and break down those silos.

Where focus shifted from and where it stands

The four-year progression from 2023 through 2026 reveals a fundamental transformation in organizational priorities and market realities.

In 2023, focus centered on post-pandemic recovery and customer engagement challenges. Organizations grappled with basic connectivity issues—getting customers to use apps, establishing digital touchpoints, understanding why engagement remained low. Sustainability concerns were building but remained largely aspirational. AI existed as an emerging technology requiring exploration but lacked clear use cases or implementation paths.

By 2024, focus shifted to experimentation and pilot programs. Organizations moved from questioning whether to adopt AI to determining how to implement it. Customer lifetime value replaced single-transaction thinking. Retail media networks began serious expansion beyond U.S. grocery. Data strategy maturity emerged as a differentiator, though most organizations admitted having only partial strategies. The tension between personalization benefits and privacy concerns intensified.

The 2025 focus accelerated toward practical applications. AI transitioned from experimental to operational across specific use cases. Generative AI turned shoppers into co-creators. Retail media monetization became imperative rather than optional. Software-defined vehicles emerged as platforms for ongoing engagement. However, organizational maturity consistently lagged behind technology readiness. The gap between what technology could do and what organizations could operationalize became visible.

In 2026, focus has moved decisively toward governance, measurement, and structural transformation. The report identifies this as a reckoning year where optimism meets reality. Organizations must prove that confidence translates to measurable capability through robust governance frameworks, clean data infrastructure, and cultural change extending beyond technology implementation.

The shift represents movement from "can we do this?" in 2023, to "how do we do this?" in 2024, to "we're doing this" in 2025, to "are we actually doing this right?" in 2026. The 2026 report characterizes this as the difference between belief and certainty—between assuming AI readiness and proving it through measurement.

The consultancy positions the 2026 findings as both map and mirror—a look at where markets are headed and a reflection of how ready leaders truly are. "Across every sector we studied, ambition is high, but alignment still lags," the editorial team wrote. "Winning now means closing that distance."

The answer depends on whether confidence translates to capability through governance, measurement, and leadership extending beyond technology implementation to structural transformation. The report's central question remains whether organizational systems fight for companies or against them.

"Don't play it safe. Dare to prove your optimism right," the report concludes. "Your systems are already shaping your future. The only question is: are they fighting for you or against you?"

For marketing professionals, these findings carry immediate implications. Organizations face pressure to demonstrate return on investment for AI initiatives while simultaneously building foundational infrastructure enabling autonomous systems to operate reliably at scale. The gap between stated readiness and actual governance capability represents the primary challenge as marketing technology spending continues accelerating.

The movement toward agentic commerce creates uncertainty for traditional advertising models. Amazon intensified its campaign to block AI companies from accessing its e-commerce platform on August 21, 2025, adding restrictions against Meta, Google, and Huawei crawlers. The company reported 22 percent growth in advertising revenue to $15.7 billion in Q2 2025.

Microsoft's occupational impact study, published July 22, 2025, examined 200,000 anonymized conversations between users and Bing Copilot. Customer service representatives, employing 2.86 million people nationwide, ranked among the top occupations for AI applicability alongside sales representatives, who represent over 1.14 million workers.

The Publicis Sapient report arrives as industry debate around automation protocols highlights ongoing tension between technical capability and business model viability. Ad tech veteran Ari Paparo published detailed analysis on November 3, 2025, expressing support for certain automation capabilities while raising significant concerns about media buying applications.

Timeline

• 2023: Publicis Sapient releases Guide to Next 2023 focusing on post-pandemic digital transformation, customer engagement challenges, and sustainability concerns; European Car Ownership Report finds 50% of car owners never interact with vehicle brands beyond initial purchase
• 2024: Guide to Next 2024 predicts retail media expansion to non-U.S. markets and documents growing AI experimentation; emphasizes customer lifetime value and sustainability urgency; finds only 3% of transportation executives have mature data strategies
• July 2025: McKinsey publishes Technology Trends Outlook 2025 identifying AI as leading trend with $124.3 billion in 2024 investment; agentic AI job postings increase 985% from 2023 to 2024
• July 22, 2025: Microsoft study analyzes 200,000 conversations revealing AI impacts 75% of major marketing occupations
• August 21, 2025: Amazon blocks AI bots from major tech companies including Meta, Google, and Huawei amid commerce battle
• September 2025: IPSOS conducts Publicis Sapient survey of 540 senior decision-makers across seven markets and five industries documenting confidence-capability gap
• September 10, 2025: Google unveils comprehensive AI advertising suite at Think Week 2025 in New York City
• October 15, 2025: Six companies launch Ad Context Protocol for advertising automation, sparking industry debate
• October 23, 2025: LiveRamp enables retail media networks to measure Meta campaign performance through Clean Room platform
• October 30, 2025: Google VP Robby Stein declares ads "not going away" despite AI transformation during Silicon Valley Girl interview
• November 6, 2025: IAB Europe publishes analysis on retail media and CTV convergence as shopping shifts to streaming
• November 11, 2025: Amazon launches agentic capabilities transforming advertising platform into autonomous campaign management system
• November 12, 2025: IAB Tech Lab releases Agentic RTB Framework v1.0 for public comment establishing containerized agent standards
• November 2025: Publicis Sapient releases Guide to Next 2026 documenting "optimistic uncertainty" and introducing concept of "decision debt" where confidence outpaces capability

Summary

Who: Publicis Sapient, a digital business transformation consultancy, surveyed 540 senior decision-makers and interviewed nearly 70 strategy, product, engineering, customer experience, data, and AI experts. Research partner IPSOS conducted the quantitative survey. Participants held C-suite positions or direct reports with recognized expertise and decision-making authority at organizations with revenues exceeding $1 billion and workforces of 1,000 employees or more across consumer products, retail, transportation and mobility, telecommunications, and media industries.

What: The 2026 Guide to Next industry trends report exposes a critical divide between executive confidence and organizational capability in AI deployment, introducing "decision debt" where optimism moves faster than evidence and assumptions scale before systems do. The research documents a four-year progression from 2023's post-pandemic recovery focus through 2024's experimentation phase and 2025's acceleration year to 2026's reckoning, identifying four critical tensions: originality versus sameness, breakthrough versus bottleneck, decisions versus deferrals, and routine versus reinvention. The report emphasizes that AI projects fail not from bad models but from inconsistent and fragmented data, with data governance emerging as the determining factor for success. Guy Elliott stated that executives are mistaking generative AI experimentation for full integration, noting that "confidence without measurement is belief, not certainty."

When: IPSOS conducted the survey in September 2025. Publicis Sapient published the report in November 2025, marking the fourth annual Guide to Next release. The findings document conditions at a critical inflection point representing a fundamental shift from previous years—2023 focused on customer engagement and connectivity challenges, 2024 emphasized experimentation and pilot programs with customer lifetime value, 2025 characterized as AI's "playground year" with practical applications, and 2026 revealing the confidence-capability gap where organizations must prove their optimism translates to measurable results.

Where: The research spanned seven markets selected for leadership in shaping global industry standards and innovation: United States, United Kingdom, Germany, France, China, Australia, and Italy. Fieldwork occurred via secure, self-completed online surveys in local languages adhering to market research guidelines, confidentiality, and data protection standards. The geographic scope enables comparison of AI adoption patterns across major economies, with findings suggesting that confidence exceeds capability consistently across all regions rather than representing a localized phenomenon.

Why: The report matters because it documents the gap between stated AI readiness and actual governance capability across major industries at a moment when marketing technology spending continues accelerating. Organizations face pressure to demonstrate return on investment for AI initiatives while simultaneously building foundational infrastructure enabling autonomous systems to operate reliably. The findings carry immediate implications for marketing professionals as platform consolidation continues, with Amazon launching agentic capabilities in November 2025, IAB Tech Lab releasing standardized frameworks, and retail media networks projected to capture 20% of global advertising revenue by 2030. The four-year progression reveals that focus has shifted decisively from "can we do this?" to "are we actually doing this right?"—from experimentation to proving capability through measurement, governance, and structural transformation rather than purely technological solutions. The consultancy warns that agentic AI represents "the next tech debt crisis" where decision-making systems and organizational structures remain unprepared for autonomous AI operation, requiring bold moves that will be structural, cultural, and human rather than just technological.