As part of the 7th Annual Insight Jam LIVE event, the Solutions Review editors have compiled a list of predictions for 2026 from some of the most experienced professionals across the Artificial Intelligence (AI) and broader enterprise technology marketplaces.
As part of Solutions Review’s annual Insight Jam LIVE event, we called for the industry’s best and brightest to share their enterprise technology predictions for 2026 and beyond. The experts featured represent some of the top solution providers, consultants, and thought-leaders with experience in these marketplaces. Each projection has been vetted for relevance and its ability to add business value.
Enterprise Technology Predictions for 2026 and Beyond
Alex Merced, Head of DevRel at Dremio
AI-Native Lakehouses Will Become the Standard Architecture.
“By 2026, the lakehouse will no longer be an emerging pattern; it will be the default. Organizations will demand platforms that natively support AI and analytics at scale. These modern lakehouses will integrate open table formats, vector search, and retrieval capabilities as core features, allowing them to handle both structured and unstructured data within a single system. It will also enable real-time, AI-driven use cases like retrieval-augmented generation (RAG) and intelligent applications without the need for duplicated infrastructure.
Generative AI Will Redefine Self-Service Analytics.
“Generative AI will transform how business users interact with data. Natural-language querying, voice interfaces, and intelligent discovery will allow non-technical users to access insights on demand, without needing SQL or data engineering support. In 2026, semantic layers and intelligent data catalogs will play a pivotal role in interpreting intent and ensuring that users access trusted, governed data. This shift will empower business teams to make faster decisions, while freeing data teams to focus on higher-value innovation.”
DataOps Will Be Automated by AI, from Pipeline to Governance.
“AI will revolutionize DataOps by automating everything from pipeline creation to metadata enrichment. Generative tools will produce ETL logic, detect anomalies, and recommend fixes in real-time, significantly reducing the manual overhead of data engineering. Simultaneously, AI-powered governance and FinOps tools will proactively optimize performance, cost, and compliance. As a result, in 2026, data teams will spend less time firefighting and more time driving strategic value across the business.”
Read the full article, via Solutions Review.
