Blog | Data/AI Strategy | June 2, 2026 | 3 min read

BARC x Actian Research: Scaling Data Products–Key Challenges and What’s Next

Par Actian Corporation

#IA Data Contracts gestion des données Data Products
scaling data products

Par Actian Corporation

#IA Data Contracts gestion des données Data Products

Résumé

  • Organizations still face challenges scaling data products, particularly around ownership, governance, and cross-team collaboration.
  • These challenges are gradually decreasing as enterprises gain experience and refine their data product strategies.
  • Data observability is emerging as a top priority (43%) to ensure data reliability and proactively detect issues.
  • Future focus is shifting toward building trustworthy, well-governed data foundations to support AI at scale.
Dans cet article :

Conclusions de l'étude mondiale BARC x Actian de 2026, menée auprès de plus de 300 responsables des données en entreprise

Dans tous les secteurs, les entreprises investissent massivement dans l'IA. Pourtant, de nombreuses initiatives peinent encore à dépasser le stade de l'expérimentation et à générer une valeur ajoutée durable pour l'entreprise.

Pour mieux comprendre ce qui distingue les initiatives d'IA qui se développent de celles qui stagnent, Actian s'est associé à BARC, un cabinet d'analyse mondial de premier plan spécialisé dans les données et l'analyse, pour mener une étude mondiale auprès des responsables des données d'entreprise.

S'appuyant sur les témoignages de plus de 300 personnes interrogées issues de divers secteurs et régions, cette étude examine la manière dont les organisations adoptent et mettent en œuvre data products data contracts, ainsi que l'influence de ces approches sur la réussite des initiatives en matière d'IA.

While adoption is accelerating, the research also highlights an important reality: implementing data products at scale remains a work in progress for many organizations.

Les leaders de l'IA contre tous les autresRapport mondial de recherche BARC × Actian (2026)

Scaling Data Products Still Presents Challenges

Despite the growing adoption of data products, organizations report several challenges when implementing them in practice.

challenges when implementing data products

Challenges when implementing data products – © BARC 2026

These challenges reflect the complexity of operationalizing data products across large organizations. Implementing this approach requires new practices for data ownership, governance, and collaboration between teams responsible for producing and consuming data.

As highlighted in the research, the transition toward managing data as products is still evolving, and organizations are refining how they structure and govern these initiatives.

Signs of Progress Across the Industry

Encouragingly, the research also indicates that many of these challenges are becoming less severe than in an earlier 2024 study.

As organizations gain experience with data product approaches, they are gradually learning to address operational and governance questions that arise as they scale these initiatives.

This suggests that data products are moving from an emerging concept toward a more established practice within enterprise data strategies.

Future Priorities: Strengthening Data Foundations for AI

Looking ahead, the research also examined which areas organizations plan to prioritize over the next 12 months as they continue scaling data products.

chart showing areas related to data products

Areas related to data products that organizations are prioritizing in the next 12 months – © BARC 2026

The research shows that the primary driver of data product adoption is data quality—trustworthy inputs for AI systems and decision-making. 

It is therefore no surprise that data observability is emerging as the next focus area (43%), as organizations seek greater visibility into the health and reliability of their data pipelines and the ability to detect and resolve issues before they affect production systems. 

Alongside observability tools, practices such as data contracts are increasingly used to ensure that expectations around schema, ownership, and quality are clearly defined.

Overall, these new priorities highlight a broader shift: enterprises are increasingly focusing not only on building data platforms but also on ensuring that the data powering analytics and AI is trustworthy and well-governed.

Télécharger le rapport de recherche complet

Cet article présente plusieurs conclusions clés issues de l'étude mondiale menée par BARC et Actian.

Le rapport complet, Data Products Data Contracts 2026 : les fondements du succès de l'IA, examine comment les organisations de tous les secteurs et de toutes les régions adoptent et mettent en œuvre data products data contracts, et comment ces pratiques influencent la maturité de l'IA, gouvernance et les résultats concrets.

Téléchargez le rapport complet pour découvrir les conclusions de cette étude et savoir comment les grandes entreprises déploient l'IA à grande échelle grâce à data products.

Télécharger le rapport complet