Fintech and cloud budgets may grab the headlines, but 2026 looks set to be a defining year for how enterprises use, govern and protect data. Across TechInformed’s 2026 submissions, contributors point to a common theme: organizations will get less mileage from labels and more from data quality, lineage, access and control.
That shows up in everything from the pushback against “agentic” positioning, to the rise of conversational interfaces, to a sharper focus on sovereignty, repatriation and vendor lock-in.
Another major shift is how people interact with data, how enterprises prepare data for AI, and how organizations keep control of data across platforms and jurisdictions.
Taken together, the forecasts suggest data leaders will spend 2026 strengthening foundations, quality, governance, portability, and trust, while simplifying access for the wider business.
Dashboards give way to conversation
James Smith, SVP EMEA, ThoughtSpot
“Agentic washing needs to go: It’s overhyped, overpriced and underwhelming.”
“Self-service will become a given rather than a selling point. Data products will continue to evolve. Often a data product is simply a dashboard, and dashboards will not be a primary method of analysis by the end of 2026.
“The term ‘data products’ as a term will fade. We’ll also see a rally against ‘agentic’. It’s been severely overused. Too many companies are slapping ‘agent’ labels on basic automation and charging five times the price. We’ll see a trough of disillusionment around ‘agentic’, moving from the initial hype to eventual productivity, but first there will be pushback against the overused term.
“Natural language interfaces will fundamentally transform how we interact with data in 2026. Today, the vast majority of data interaction happens through dashboards. I expect it to drop to less than 20% by the end of 2026. We’re quickly moving towards a conversational data experience that makes insights accessible to everyone, not just data specialists. This will become the expectation.”
AI outcomes depend on data quality
Andy Whitehurst, Chief Technology Officer, Sopra Steria UK
“Data will be the super unleaded fuel for businesses.”
“2026 will show that the biggest barrier to effective enterprise AI will be the persistent myth that AI is ‘magic’. The reality is far more grounded because AI’s value remains inseparable from the quality of the data it consumes.
“Organizations that treat data management as an afterthought will find their AI initiatives falter, while those who invest in high-quality, well-curated and accessible data will unlock superior outcomes and competitive advantage.
“Think of data as the ‘super unleaded’ fuel for AI, better quality enables more complex, higher-performing solutions, whereas lower quality fuel will only restrict progress. The year ahead will see a growing recognition that successful AI isn’t solely about clever algorithms, but about disciplined data stewardship.”
Rytis Ulys, Head of Data & AI, Oxylabs
“In 2026, the search for data will focus less on quantity and more on quality. Recent Anthropic research showed that even small amounts of low-quality data can ruin the entire dataset. Additionally, it showed that beyond a certain point, adding more low-quality data yields minimal gain – or even degrades performance – compared to using a targeted, relevant subset.
“As such, data fundamentals will remain more important than ever. Robust tables and catalogs, quality and lineage, and low-latency query engines have become prerequisites for agents, retrieval, not afterthoughts. Graph and vector-augmented retrieval is moving from blog post to pattern, observability now spans prompts, tools, and cost, and compliance sits alongside performance in the same plane. Data isn’t fading; it’s been promoted to AI’s control surface.”
Sovereignty drives architecture choices
Edwin Weijdema, Field CTO EMEA & Cybersecurity Lead, Veeam
“Data Sovereignty will turn regulatory demands into a business advantage.”
“For the last decade, or at least since the GDPR came into force, organizations have been pushed to pay more attention to their data. Despite this, most have barely scratched the surface of what their data can deliver, instead focusing on meeting compliance and resilience.
“But next year, this is going to start to change. I see more organizations embedding data sovereignty into their operations, and along the way, the more mature ones will finally transform data from a regulatory demand into a strategic advantage. Where previously, data strategy has been all about defense, we will see this shift into proactive data use, turning it into a driver of innovation.
“2026 will be key for this. It will be no small task to establish the control and understanding of data needed to unlock it. But I expect that those organizations that use the year ahead to evolve their data maturity will see accelerated product development, business growth, and will be able to offer unique customer experiences – crucially differentiating them from those that remain focused solely on ticking the compliance box. After all, compliance should be the baseline of what you do, not the finishing line.”
Chris Dyke, Sales Director UK and Ireland, Allied Telesis
“Regulatory and geopolitical pressures will drive significant investment in localised enterprise databases. Organisations will increasingly maintain critical data on-premises or within regional infrastructure, creating an integrated enterprise network architecture optimised for these local data centres.
“Networking solutions must ensure secure, high-performance connectivity across sites, supporting compliance and efficient data access. This trend is expected to accelerate through 2026 as privacy and regulatory requirements tighten.”
Portability and trust define the data layer
Efrain Ruh, Regional CTO, Digitate
“Vendor Data Lock-In Becomes the Hidden Threat to AIOps.”
“One of the least visible, but most impactful trends will be the increasing control that large software vendors exert over operational data. As observability and telemetry become more integral to AI systems, some vendors will restrict direct access to logs, metrics and configuration data, pushing enterprises toward their own proprietary AI tools.
“This shift changes the competitive landscape entirely. Data access becomes crucial for building vendor-agnostic AI solutions. Without control over their operational data, organisations risk being locked into narrow ecosystems that limit choice, innovation and interoperability.
“Chief Information Officers (CIOs) will need to negotiate differently in this era. Data portability, API openness and cross-platform observability must be written explicitly into contracts. The organisations that protect their neutral data layer will maintain the freedom to adopt best-of-breed AI and avoid being trapped by single-vendor ecosystems.”
James Evans, Senior Director, Head of AI, Amplitude
“Data-first AI will redefine the ethics of innovation. Next year, responsible AI will start not with ambition but with accountability. The most forward-thinking organisations will design AI initiatives around the data they can legally and ethically use, rather than building systems first and scrambling for training data later.
“Consent-based value exchanges will become a cornerstone of innovation, where users knowingly trade information for tangible benefit. As legal and public scrutiny intensify, businesses will realise that transparent data lineage and user choice are competitive differentiators, not compliance chores.
“At the same time, new economic models will emerge to reward creators whose content underpins the next generation of AI models, helping to correct the imbalance between human contribution and machine advantage. Trust, not scale, will become the true measure of AI maturity.”