Alteryx, Inc., an AI-ready data and analytics company, today released its “2026 State of Data Analysts in the Age of AI” report, revealing that while AI is becoming central to business decision-making, human oversight remains critical to ensuring AI-generated outcomes are trusted and actionable. The research found that analysts spend nearly four hours per week validating and correcting AI-generated outputs, while poor data quality and governance continue to undermine AI and analytics initiatives. The findings also show that AI works best when the people closest to the business stay involved, with 65% of analysts saying AI and agent-based systems are most productive when the logic is managed at the business level. As organizations accelerate toward more agentic AI systems, the need for trusted data, governed logic and workflows, and human oversight continues to grow.

Key Findings at a Glance: 

• 96% of data analysts are actively using AI tools in their roles 
• 47% of failed AI and analytics projects are attributed to poor data quality or governance 
• 65% of analysts say AI and agent-based systems are most productive when the logic is managed at the business level
• Data analysts spend an average of 5.7 hours per week preparing and cleaning data, and an additional 3.7 hours per week checking and correcting AI outputs
• Only 3% prefer fully autonomous AI without routine human involvement, while 46% favor a human-in-the-loop approach 

The findings point to a broader shift in how organizations are operationalizing AI. As businesses move from experimentation to deploying AI in core workflows and decision-making, trust increasingly depends on more than model performance alone. Analysts and operations teams play a critical role because they maintain business logic, governance standards, and operational context that help AI systems produce reliable and actionable outcomes.

Human Oversight Still Remains Central in the Age of Agentic AI

As AI becomes a bigger part of an analyst’s day-to-day work, the impact goes beyond simple productivity gains. Businesses are quickly adopting more advanced AI capabilities, like agentic AI, but, on the contrary, analysts are now spending more time reviewing, validating, and guiding AI-generated work. Over half (59%) expect to use AI agents to generate insights within the next year, and many are already using them to draft communications (59%) and manage workflows (54%).

Even as AI takes on a larger role in data-to-insight workflows, analysts remain closely involved because they are ultimately accountable for the quality, accuracy, and reliability of the outcomes. Nearly half (46%) prefer a human-in-the-loop approach where AI systems require human approval before taking action, while only 3% are comfortable with fully autonomous AI. The findings suggest that as AI becomes more embedded in business processes, trust, oversight, and human judgment remain essential to ensuring outputs are accurate, explainable, and aligned with business needs. 

“AI is already influencing how businesses make decisions every day, but our research highlights a reality many organizations are now confronting: trust matters just as much as speed,” said Andy MacMillan, CEO at Alteryx. “The people closest to the business play a critical role because they understand the logic, rules, and operational context behind decisions, whether that’s pricing models, compliance requirements, or operational thresholds, and that business logic is constantly evolving. AI can accelerate work, but organizations still need governed workflows and human oversight to ensure outcomes are visible, understandable, repeatable, and auditable across the organization.”

Data Challenges Continue to Limit AI Success

Behind every successful AI initiative is a strong data foundation, and many organizations are still struggling to get there. Even as AI adoption grows, ongoing issues with data quality, access, and governance continue to slow progress and limit AI effectiveness. Analysts say either poor data quality or governance is responsible for nearly half (47%) of failed AI and analytics projects, making it the biggest barrier to AI success.

Most (79%) analysts believe their data is ready for AI at scale, yet the day-to-day reality looks much different. Analysts still spend an average of nearly 6 hours each week preparing and cleaning data, plus nearly another 4 hours reviewing and correcting AI-generated outputs, checking for issues such as incorrect calculations, inconsistent metrics, or responses that don’t align with company policies and definitions. Governance concerns are also rising, with access control and data exposure (42%) ranking as the top issue, followed closely by regulatory compliance (41%). These findings show that as companies push AI deeper into business operations, the people closest to the business increasingly need to provide the context AI relies on, including not just clean data, but also the business logic, workflows, policies, and governance that shape how decisions are made and acted on.

AI Becomes Core to Business Decision-Making

AI is quickly becoming part of everyday business decision-making. Nearly all analysts surveyed (96%) say they use AI tools in their work every day, and organizations are already seeing the impact. Among IT leaders, 85% report noticeable gains in employee productivity, while 79% say AI is helping teams make decisions faster.

As AI adoption grows, AI-generated insights are carrying more weight across the business. Half (50%) of analysts and 62% of IT leaders say that most or almost all business-critical decisions are now influenced by AI insights.

But generating insights faster doesn’t always make decisions easier. The biggest challenge organizations face is helping business leaders understand and trust AI-generated outputs, with 43% saying interpreting and explaining AI insights remains a key barrier. At the same time, companies continue embedding AI into core technologies like cloud data warehouses (40%) and business intelligence tools (39%), making AI an increasingly central part of how businesses operate.

The Evolving Role of the Data Analyst

Analysts increasingly see AI as a collaborator that changes how work gets done, not a replacement for human expertise. In fact, 82% say automation is making them more effective by helping them work faster and focus on higher-value tasks.

As AI becomes more embedded in everyday operations, the role of the analyst is evolving from producing insights to guiding how AI systems operate. Over the next five years, 40% believe changing skill requirements will have the biggest impact on their responsibilities, while 36% point to the growing importance of real-time analytics. The findings suggest that analysts and operational teams will play an increasingly important role in defining, validating, and evolving the business logic AI systems rely on to deliver trusted, repeatable outcomes. This includes the rules, calculations, and operational processes that determine how the business actually runs, whether it’s updating tax rules in different countries, changing sales commission structures, adjusting supply chain thresholds, or applying compliance and pricing policies as conditions evolve.

Ahmad Shakora, Group Vice President- META, Cloudera

We are now in an era where digital connectivity underpins many areas such as commerce, security, governance, and social life.

In the Middle East, with ever-changing external factors, access to data has transitioned into a critical asset, with organisations and nations increasingly focused on protecting a vast array of information.

 For businesses operating in this region, traditional efficiency-focused IT strategies are no longer sufficient. Robust business continuity and disaster recovery must take center stage.

The expanding risk matrix

The current operating environment highlights several areas of vulnerability for global digital infrastructure, demonstrating that risks can be either planned or entirely unexpected:

• Government interventions can result in significant, sudden internet restrictions. Additionally, physical data center infrastructure is susceptible to multiple external factors. Severe and unpredictable environmental events, including extreme heat and unexpected flooding, can place a strain on the physical and cooling infrastructure of centralized data centers, forcing facilities offline
• Unexpected impact on physical infrastructure can arise, causing noticeable latency
• Total reliance on centralized third-party platforms amplifies operational risks. These can stem from planned events, such as routine maintenance and vendor migrations, or unplanned events, such as global software updates that inadvertently lead to widespread, cascading outages

In response to these varied and potentially compounding threats, the Gulf Cooperation Council is shifting from efficiency-first cloud adoption to resilience-first planning. Nations are accelerating investments in localized data centers, sovereign cloud environments, and multi-channel data access architectures that can withstand both cyberattacks and physical military threats.

In the UAE, the sovereign cloud market is projected to grow at a compound annual rate of 23% through 2033, signalling a sustained commitment to securing critical data and reducing exposure to fragile global dependencies.

When resilience becomes the backbone of survival

These external forces elevate Business Continuity and Disaster Recovery from a regulatory checkbox to a fundamental requirement for corporate survival. For CIOs and CTOs operating in the Middle East, ensuring operational resilience requires highly specific architectural choices.

Tech leaders who view infrastructure through a purely technical lens may be vulnerable. Data infrastructure must function as a strategic fortress. Resilience must supersede efficiency as the primary design goal. To continue operating amidst disruptions, tech leaders should look for the following differentiators when building their enterprise data infrastructure:

1. Cloud power, local control: do not put all the eggs in the public cloud basket. Organizations need a setup that works the same way whether it is in a giant data center or a small server at a remote branch. By running mini-clouds locally, enterprises keep the speed and control without being at the mercy of a service provider’s outage. Infrastructure must allow organizations to run data and AI workloads anywhere, converging the best of public cloud with on-premises deployments, including secure air-gapped environments.

2. Maintain internal control over enterprise AI: if there are disruptions to internet access or travel is restricted, AI shouldn’t stop working. Sovereign Private AI, by design, brings the thinking power to where the data actually sits. This keeps sensitive data secure and ensures automated systems stay online even if the rest of the world goes offline.

3. Diversify technology partners: tech leaders should implement an Open Data Lakehouse architecture that unifies 100% of the organization’s data to avoid vendor lock-in and catastrophic single points of failure. A critical design principle to look for is the strict separation of compute and storage. By utilizing highly scalable, S3-compatible object storage independently from computing power, enterprises can leverage robust data replication and erasure coding to ensure high durability, guaranteeing that all backup data remains safely within sovereign boundaries.

4. One view, no silos: managing fragmented data across a region during a crisis can be chaotic. CIOs need a Unified Data Fabric that breaks down silos and provides a single view of all organizational data with centralized, end-to-end security and governance across complex hybrid environments. Coupled with this, infrastructure must support Data in Motion: the ability to seamlessly move and process real-time data from any source to any destination. If a subsea cable is damaged or a data center goes offline, this capability ensures business-critical decisions can still be made seamlessly as traffic reroutes.

5. Visibility & isolation: Operational survival requires extreme visibility. A resilient infrastructure must feature granular observability across the full IT stack for proactive health monitoring, incident response, and data-flow policy enforcement. By using containers to isolate different tasks, enterprises can ensure that if one part of the business encounters technical issues, the risk is contained, protecting critical operations.

The future of business in the Middle East belongs to leaders who treat their infrastructure as a sovereign fortress.

True resilience requires moving past simple cloud adoption to build localized, hyper-resilient architectures that remain fully functional when global networks fail. CIOs and CTOs must now prioritize digital autonomy by anchoring their most critical operations in hardened, local environments that can withstand physical and international uncertainties. By designing for total isolation, leaders can ensure their organization remains operational and secure regardless of regional instability. The ultimate competitive advantage is the ability to maintain power and connectivity.

Holcim UAE officially launched ECOCycle® at the Make It In The Emirates event at ADNEC Centre, Abu Dhabi, marking a landmark moment in the country’s journey toward smarter, more sustainable construction. ECOCycle uses Holcim’s advanced circular technology to accelerate change, building cities from cities and closing the loop in construction.

The UAE generates enormous volumes of construction demolition materials every year, accounting for an estimated 70% to 75% of the nation’s total solid waste. ECOCycle directly addresses this challenge by transforming this into new, high-quality building materials, giving discarded resources a second life rather than sending them to landfill. ECOCycle, Holcim’s circularity technology platform, guarantees a minimum of 10% up to 100% recycled construction demolition materials in every labeled product, with no compromise on quality or performance.

Speaking at the launch, Ali Said, CEO of Holcim UAE and Oman, said: “With ECOCycle, we’re building cities from cities, closing the loop in construction and helping our customers achieve their ambitious circularity goals – by providing building materials and solutions that carry this label, with no compromise on quality and performance. At the same time, we’re reducing the use of primary materials, conserving natural resources, and minimizing the volume of materials sent to landfill.”

The concept is simple but powerful. Instead of extracting new raw materials for every construction project, ECOCycle recovers and reprocesses materials from old structures, feeding them back into the construction cycle. The result is a genuinely closed-loop system that reduces waste, conserves natural resources, and supports the UAE’s ambition to divert 75% of waste from landfill.

This is not an untested idea. Holcim has already used this technology across multiple markets worldwide, including in France where – in a world first – an entire residential building was constructed using 100% recycled concrete. The UAE launch brings that proven track record to this region for the first time.

ECOCycleproducts can contribute to internationally recognized green building certifications, giving developers, architects, and contractors confidence that they are building responsibly. From foundations to facades, ECOCycle is how Holcim turns the cities of today into the building materials of tomorrow, building cities from cities.