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AI Readiness Lags Ambitions: Survey Highlights Key Gaps Threatening Generative AI Success

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Qlik

Qlik recently announced findings from an IDC survey exploring the challenges and opportunities in adopting advanced AI technologies. The study highlights a significant gap between ambition and execution: while 89% of organizations have revamped data strategies to embrace Generative AI, only 26% have deployed solutions at scale. These results underscore the urgent need for improved data governance, scalable infrastructure, and analytics readiness to fully unlock AI’s transformative potential.

The findings, published in an IDC InfoBrief sponsored by Qlik, arrive as businesses worldwide race to embed AI into workflows, with AI projected to contribute $19.9 trillion to the global economy by 2030. Yet, readiness gaps threaten to derail progress. Organizations are shifting their focus from AI models to building the foundational data ecosystems necessary for long-term success.

Stewart Bond, Research VP for Data Integration and Intelligence at IDC, emphasized:
“Generative AI has sparked widespread excitement, but our findings reveal a significant readiness gap. Businesses must address core challenges like data accuracy and governance to ensure AI workflows deliver sustainable, scalable value.”

Without addressing these foundational issues, businesses risk falling into an “AI scramble,” where ambition outpaces the ability to execute effectively, leaving potential value unrealized.

“AI’s potential hinges on how effectively organizations manage and integrate their AI value chain,” said James Fisher, Chief Strategy Officer at Qlik. “This research highlights a sharp divide between ambition and execution. Businesses that fail to build systems for delivering trusted, actionable insights will quickly fall behind competitors moving to scalable AI-driven innovation.”

The IDC survey uncovered several critical statistics illustrating the promise and challenges of AI adoption:

  • Agentic AI Adoption vs. Readiness: 80% of organizations are investing in Agentic AI workflows, yet only 12% feel confident their infrastructure can support autonomous decision-making.
  • “Data as a Product” Momentum: Organizations proficient in treating data as a product are 7x more likely to deploy Generative AI solutions at scale, emphasizing the transformative potential of curated and accountable data ecosystems.
  • Embedded Analytics on the Rise: 94% of organizations are embedding or planning to embed analytics into enterprise applications, yet only 23% have achieved integration into most of their enterprise applications.
  • Generative AI’s Strategic Influence: 89% of organizations have revamped their data strategies in response to Generative AI, demonstrating its transformative impact.
  • AI Readiness Bottleneck: Despite 73% of organizations integrating Generative AI into analytics solutions, only 29% have fully deployed these capabilities.

These findings stress the urgency for companies to bridge the gap between ambition and execution, with a clear focus on governance, infrastructure, and leveraging data as a strategic asset.

The IDC survey findings highlight an urgent need for businesses to move beyond experimentation and address the foundational gaps in AI readiness. By focusing on governance, infrastructure, and data integration, organizations can realize the full potential of AI technologies and drive long-term success.

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Qlik Named a Leader in the 2025 Gartner Magic Quadrant for Augmented Data Quality Solutions

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Qlik

Qlik recently announced its recognition as a Leader in the 2025 Gartner Magic Quadrant for Augmented Data Quality Solutions, marking its sixth time receiving this recognition. Qlik sees this recognition as a validation of its commitment to helping businesses ensure the data quality and governance needed to drive AI confidently at scale.

“With AI models increasingly commoditized, the true differentiator is data quality,” said Mike Capone, CEO, Qlik. “Companies that invest in governance and integrity will extract the most value. This recognition from Gartner validates what we see—AI success depends on trusted data.”

AI models require consistent, complete, and trusted data to generate accurate insights, yet many organizations struggle with gaps, inconsistencies, and unstructured inputs that undermine AI’s effectiveness. Poor data results in unreliable models, biased predictions, and heightened operational risk.

“Organizations need more than standalone data quality tools—they need a complete data strategy that ensures integrity at every stage,” said Drew Clarke, GM & EVP, Data Business Unit, Qlik. “Qlik Talend Cloud enables enterprises to embed trust into their data, analytics, and AI workflows, turning fragmented data into a reliable asset.”

By enabling proactive, governed data pipelines, Qlik ensures AI systems operate with high-trust data from the start, allowing businesses to scale AI with confidence.

AI is driving demand for next-generation data quality solutions that go beyond basic cleansing. With innovations like the Qlik Trust Score for AI, retrieval-augmented generation (RAG) support, and automated data remediation, businesses can move from reactive fixes to continuous, AI-powered data optimization.

Key Capabilities of Qlik:

  • Qlik Trust Score for AI: Assesses data readiness for AI applications, ensuring reliable and explainable outputs.
  • Hybrid and Multi-Cloud Deployment: Ensures consistent quality across diverse environments.
  • Unstructured Data Processing: Converts raw, unstructured content into actionable insights, ensuring seamless connectivity.
  • Automated Remediation: Machine learning refines quality rules over time, reducing manual effort.
  • Data Products: Ensuring that curated data assets are easily accessible to data consumers to accelerate their use-cases, including AI projects.

“Trusted data is critical to our operations, from regulatory reporting to daily decision-making,” said Tomohisa Nakajima, Senior Manager, ICT Strategy Department, at NEC Personal Computer Corporation. “As we explore AI, ensuring data quality and governance allows us to do so responsibly and with confidence. Qlik Talend Cloud will help us automate data quality, reduce inconsistencies, and build a foundation of trust that supports both our current needs and future AI initiatives.”

“We’re seeing an increasing demand from businesses that recognize AI’s potential but struggle with data reliability,” added Clarke. “Qlik’s ability to deliver converged data management—from ingestion to AI-powered insights—sets us apart and ensures organizations can scale AI initiatives with confidence.”

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With NVIDIA Cosmos Curator, Milestone announces a platform to enable access to data and train AI Models

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Milestone NVIDIA

Leveraging the NVIDIA platform, Milestone Systems’ Project Hafnia is aiming to be a leading service for data generators, to share and utilize their data, and for developers, to access traceable and regulatory-compliant annotated video data.

Milestone’s goal is to put the latest advances in Vision Language Models (VLM) and supporting data curation capabilities in the hands of as many developers as possible.  One of the first service offerings is a VLM, fine-tuned using NVIDIA fine-tuning microservices on a large volume of compliant transportation data, curated using NVIDIA Cosmos Curator.

The VLM’s accuracy and performance optimizations are tuned for running on NVIDIA GPUs and in NVIDIA’s video search and summarization (VSS) AI blueprint. 

“By leveraging the NVIDIA platform, Milestone Systems is helping accelerate this next wave of powerful visual services,” says Deepu Talla NVIDIA Vice President and General Manager — Embedded and Edge Computing. “The next phase in development and adoption of visually perceptive Agentic AI services will be unlocked by recipes like NVIDIA VSS blueprint combined with widely available and accessible fine-tuned VLM models,” he says.

Access to data
Milestone Systems is aggregating compliant data through its global network of partners and customers in video data management. These organizations seek to leverage their own data to develop smarter analytics and will be able to benefit from the platform, which can be utilized to train AI models on sufficient, compliant data.

Artificial intelligence is our generation’s biggest game-changer. A major challenge for the ongoing development is having access to enough high-quality data for training AI models. The Project Hafnia platform will collect and curate data with the aspiration to be the world’s smartest, fastest and responsible platform for video data and training of AI models,” says Thomas Jensen, CEO of Milestone Systems.

Additionally, Project Hafnia will remove major friction points and provide smooth and seamless access to data. Driven by NVIDIA Cosmos Curator data curation, the service will speed up developing AI and analytics – up to 30 times faster than today’s standards.

Accuracy and speed
Milestone Systems will offer two services:

  •  A cutting-edge service for AI model training with high-quality video data through Training as a Service, where software developers can access quality data to train AI-models
  • A new Visual Language Model as a Service for smart city transportation and Intelligent Traffic Service use-cases that will be industry leading in performance.  


With new high-quality data and improved annotation, future analytic software for applications such as traffic management, manufacturing, airports, law enforcement, and business could achieve accuracy high enough to enable large-scale automation of operations and surveillance like never before.

Traffic Management VLM
By leveraging the NVIDIA platform, Milestone Systems has taken the first step in developing a market leading traffic and transportation Visual Language Model (VLM). The model supports a range of use cases, including general traffic assessments, driving condition evaluations, alert validation, and incident reporting.  

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UiPath to Unveil Latest Agentic Automation Solutions at Agentic AI Summit

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AI Summit

UiPath recently announced its annual UiPath Agentic AI Summit will take place online on March 25, offering attendees deeper insight into the latest UiPath agentic automation innovations and strategies for implementing agentic AI and automation to deliver consistent, reliable, and transformative business outcomes.

Agentic automation integrates AI agents, robots, and people to streamline operations, automate complex end-to-end business processes with multiple workflows and contextual decision-making, improve scalability, and unlock new levels of productivity. It enables AI software agents powered by machine learning, advanced AI, natural language processing, and computer vision to take autonomous action and deliver consistent, reliable, and transformative outcomes.

“Agentic automation is transforming businesses by integrating advanced process automation, business data and real-time intelligence to support scalable decision-making, and we’re seeing strong interest from customers eager to pilot this technology,” said Graham Sheldon, Chief Product Officer at UiPath. “UiPath agentic automation delivers value by driving efficiency, consistency, and scalability while empowering teams, enhancing user experiences, and ensuring strong governance. Simply put, the UiPath Platform is one of the best places to build, test, and deploy enterprise-grade agents.”

At the Summit, viewers will learn how to unlock and accelerate agentic automation initiatives with AI agents that are equipped with enterprise-grade tools and capabilities, orchestrated in complex, end-to-end workflows with robots and human-in-the-loop.

The Summit features experts from UiPath and customers such as WEX, State Street, and Adobe discussing a range of in-demand topics that can help automation professionals, business leaders, and knowledge workers understand the benefits of agentic automation. WEX, a provider of payment processing and information management services, will discuss how it is using the UiPath Platform to build, test, and deploy enterprise-grade agents to transform business processes, in part to enhance sales team preparation and document processing.

“Agentic automation enables us to make informed decisions and quickly adapt to business changes for rapid scaling. Its integration in call centers consolidates automations, streamlines processes, and empowers agents to use natural language,” said Emily Krohne, Enterprise Automation Principal at WEX. “This solution recognizes requests, triggers appropriate automations, and lightens the load on our workforce.”

Ashraf El Zarka, Vice President and Managing Director, Middle East and Africa at UiPath, said: “Businesses in the Middle East are moving beyond basic automation and actively investing in AI-driven solutions that solve real challenges. With AI expected to contribute $320 billion to the region’s economy by 2030, we see strong demand for technologies that simplify operations and deliver real value. Agentic Automation makes this possible by combining AI agents, robots, and people to improve decision-making and efficiency at scale. The Agentic AI Summit is a chance for businesses to see how they can use AI agents to work smarter, reduce complexity, and drive meaningful results.”

The summit will describe building trustworthy, governed enterprise agents within the UiPath Platform with specific sessions on Agentic Orchestration, Agentic Testing, and Agent Builder. The Agentic AI Summit will close with the session, “From inception to execution: The path to an orchestrated enterprise,” that will discuss the future of the orchestrated enterprise and will explore the latest AI research and agentic innovations that will profoundly transform organizations, empower the people who work in them, and change the nature of work itself.

Use case sessions will include:

  • Industry deep-dive: putting agentic automation to work in banking, financial services, healthcare, and manufacturing
  • Department deep-dive: how agentic automation is transforming finance, legal, and human resources
  • Application testing deep-dive: transforming SAP and SAP S/4HANA migration testing with AI
  • Process intelligence: leverage AI-powered insights for data-driven decisions on impactful transformation opportunities

UiPath Agentic Automation offerings

UiPath offers customers a single platform to understand and construct agentic solutions with a thorough understanding of key foundational components and the interplay between them. Its agentic offerings include:

  • Agentic Orchestration: now in public preview, UiPath Agentic Orchestration serves as the nerve center to meticulously coordinate processes involving UiPath-built or third-party agents, robots, people and harmonizes all elements within an automation ecosystem. It functions as the conductor in the grand symphony of business processes, orchestrating the roles of robots, agents, and people in end-to-end implementations. The average large company operates over 175 enterprise applications, each with its own data, processes, and decision-making frameworks. Without a structured, orchestrated approach, AI agents become just another layer of complexity that leads to more inefficiency, siloed decisions, and operational risk. Agentic Orchestration makes it possible for enterprises to take control of their agentic processes by assigning tasks, managing interactions across systems, and maintaining governance over AI-powered decisions.
  • Agent Builder: The company also recently announced UiPath Agent Builder, which offers a guided experience for building, testing, and launching ecosystem-agnostic, data-grounded AI agents. These agents handle complex workflows, provide autonomous decision-making, and integrate various enterprise tools and applications at scale. Agent Builder features include from-scratch agent creation, pre-built templates, testing tools, API deployment, and seamless workflow integration.

At the summit, UiPath will also announce the launch of UiPath Test Cloud, a revolutionary new approach to software testing that uses advanced AI to amplify tester productivity across the entire testing lifecycle to help customers achieve greater efficiency and cost savings. Through Test Cloud, agentic testing for software testing teams becomes a reality, equipping professionals with agents such as UiPath Autopilot and testing agents built with Agent Builder to act as collaborative partners throughout the entire testing lifecycle. By augmenting testers with AI, businesses can test more software, reduce costs, and improve accuracy to accelerate time-to-value and deliver high-quality software to customers.

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