How Quintrix helps companies find and train data talent for the data revolution

AI, The Future & You Someone once asked me, “What’s the future of most industries and establishments now that AI can perform so many human tasks — sometimes even better?” Here’s my honest response: AI has come to stay — for good. But the key is not to fear being replaced by it; it’s to learn how to work with it. In today’s world, those who learn how to use AI as a tool for efficiency, creativity, and problem-solving will always stay relevant. AI won’t take your job — but someone who knows how to use AI effectively just might. 💭 I’d love to hear your thoughts: How do you see AI transforming your field or industry? — EGBO Blessing C. Data Analyst | Certified Human Resource Manager |CEO, Soar Space Hub #ArtificialIntelligence #FutureOfWork #DataAnalytics #HRM #Innovation #SoarSpaceHub 📸 PS: I created this image using Google Gemini AI Studio.

Recent CompTIA data show that most organizations are using AI to cut labor rather than build real capability. That’s not technological progress — it’s an institutional failure with serious economic implications. We must stop treating efficiency as the dominant variable in innovation. True innovation expands human capacity, strengthens mobility, and distributes opportunity across the system. 🔗 Read more: https://lnkd.in/gHFnHwNZ So the question I’m wrestling with is this — what happens when innovation starts to hurt? #AI #Innovation #FutureofWork #NextEconomy

🚨 The recent commentary by RAND (October 24, 2025) , originally published by Barron’s on October 18, and authored by Jonathan Welburn and Vegard Mokleiv Nygaard, invites us to radically reconsider the way we interpret the relationship between artificial intelligence and work. The title is provocative: “AI is making jobs, not taking them”, but the content goes beyond optimism: it offers a data-driven, more cautious and realistic perspective on what is actually happening. The starting point is clear: AI is not (yet) revolutionizing employment the way Wall Street and the media suggest and the real issue lies in how slowly AI is being adopted in real business processes. 🔍 Some interesting data: * Only 2 % of companies in the logistics and transportation sector use generative AI. * In the financial and insurance sectors, the rate is around 10 %. * Even in the IT world, only 1 in 4 companies truly integrates generative AI into its products or services. But the most surprising data point is this: companies that use AI are more likely to increase employment than reduce it. Why? Because we’re confusing “exposure to AI” with “full automation.” Most AI technologies today are augmenting and redefining work, not replacing it. 💡 Another study cited in the piece (MIT Sloan Executive Education) shows that 95 % of companies are not getting returns from their AI investments because they still fail to integrate these tools into their core processes. The problem isn’t technological power, but alignment between tools, people and organizational structure. 📎 At least three reflections emerge for those working in governance and labor markets: 1. Talking about AI without considering real adoption data creates false expectations and unnecessary polarization. 2. Regulating the future of work can’t be based on rigid categories (“human” vs “artificial” labor), but on hybrid ecosystems. 3. This is the time to invest in training and adaptive capacity, not in apocalyptic predictions. 📣 The real issue isn’t “AI vs work,” but rather AI as a catalyst for new types of work and new skills. 👉 Read the full RAND commentary: https://lnkd.in/dVzV2bCb #AIGovernance #JobCreation #AIAdoption #Ethics # #AIWorkforce #DigitalTransformation

“92% of companies say data is a strategic asset — yet only 34% have mapped where it lives.” (IDC, 2025) Imagine hiring the smartest person in the world... …then locking them in a room with no context, incomplete files, and blurry links. That’s how most enterprises treat AI today. They feed it fragments, expect clarity, and blame the model when it fails. But AI doesn’t create intelligence — it amplifies visibility. At DEVOPSOLUTION, we build environments where: 🔹 Data is discoverable and contextual 🔹 Visibility is engineered, not assumed 🔹 Intelligence comes from clarity, not chance #AI #DataDiscovery #AIReadiness #Transparency #EnterpriseArchitecture #DevopSolution #DigitalLeadership

🤖 Agentic AI is reshaping how organizations harness market intelligence—streamlining data analysis and helping teams unlock insights they might otherwise miss. As AI steps into a more active analyst role, how do you see this impacting your strategy and innovation goals? 📔Get some inspiration on our blog: https://hubs.ly/Q03NXPmp0 #AIforInsights #MarketIntelligence #Innovation #KnowledgeManagement #AgenticAI #DeepSightsAgents

In modern enterprises, 𝐚𝐜𝐜𝐮𝐫𝐚𝐜𝐲 𝐢𝐬 𝐧𝐨 𝐥𝐨𝐧𝐠𝐞𝐫 𝐭𝐡𝐞 𝐟𝐢𝐧𝐢𝐬𝐡 𝐥𝐢𝐧𝐞, 𝐢𝐭’𝐬 𝐭𝐡𝐞 𝐬𝐭𝐚𝐫𝐭𝐢𝐧𝐠 𝐩𝐨𝐢𝐧𝐭. As organizations embrace automation and AI, what truly defines success today is trust in data. When leaders hesitate because two reports show different numbers, or when teams spend hours validating figures instead of acting on them, the issue isn’t just data quality. It’s a data trust gap. Forward-thinking enterprises are now making 𝐝𝐚𝐭𝐚 𝐭𝐫𝐮𝐬𝐭 𝐚 𝐦𝐞𝐚𝐬𝐮𝐫𝐚𝐛𝐥𝐞 𝐊𝐏𝐈 tracking reliability, transparency, and accountability alongside revenue and performance. 𝐎𝐮𝐫 𝐥𝐚𝐭𝐞𝐬𝐭 𝐛𝐥𝐨𝐠 𝐩𝐨𝐬𝐭 explains how to quantify trust, connect it to business outcomes, and make it visible across every analytics layer. 𝐡𝐭𝐭𝐩𝐬://𝐝𝐚𝐭𝐚𝐤𝐫𝐲𝐩𝐭𝐨𝐧.𝐚𝐢/𝐰𝐡𝐲-𝐝𝐚𝐭𝐚-𝐭𝐫𝐮𝐬𝐭-𝐢𝐬-𝐛𝐞𝐜𝐨𝐦𝐢𝐧𝐠-𝐭𝐡𝐞-𝐧𝐞𝐰-𝐤𝐩𝐢-𝐟𝐨𝐫-𝐦𝐨𝐝𝐞𝐫𝐧-𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞𝐬/ Because in the data-driven era, the companies that trust their data will move faster, decide smarter, and innovate better.   #DataTrust #DataQuality #DataGovernance #DataObservability #DigitalTransformation #AI #Analytics #BusinessIntelligence #DataDriven #EnterpriseData #ModernDataStack

Data Driven Crash  Most executives believe that data is pure and objective, and that by adopting a data driven strategy, they are creating a culture of rationality devoid of politics and bias. Sorry; but going to burst that bubble. Data is the atomic identifiable artifact resulting from the combination of many decisions. Data is not objective. As the artifact of decisions, data encodes all the biases, politics and misconceptions that influenced the decisions in the first place. Without fully understanding how the decision making process actually works, a data driven strategy is very likely to lead to strategic missteps.   This is why we created CLAIS (C-Level Artificial Intelligent Strategy), AI for the executive suite. CLAIS informs the executive how decisions are actually made, how processes actually work, what biases and misunderstandings are moving the company into precarious positions and how the built-up inertia of the organization puts the company at risk to business model innovation.   To learn more, please follow us at https://lnkd.in/dRXJUinC    #AI #artificialintelligence #strategy #busienssmodelinnovation 

When Data Meets AI: The New Role 🧠 Data used to answer questions. Now, with AI, it asks them. We’re entering a new era in analytics one where AI doesn’t just accelerate work… it changes the kind of work analysts do. Here’s the shift no one is talking about 👇 🔹 Old role: “Give me the numbers.” “Build the dashboard.” “Explain what happened.” 🔹 New role (2025): “Tell me what we’re missing.” “Challenge the assumptions.” “Guide the decision.” “Teach AI how to think with our data.” AI gives us speed. But analysts bring context, judgment, and strategy the things algorithms can’t replicate. The analysts who thrive now aren’t just chart builders. They’re strategic translators: connecting data, business logic, and human insight into one narrative that leaders can actually act on. 💡 The future of analytics belongs to people who can think beyond the dashboard. Not the ones who fear AI but the ones who know how to direct it. What part of your workflow has changed the most with AI this year? #DataAnalytics #AI #PowerBI #DecisionIntelligence #Leadership #DataCulture #FutureOfWork

You don’t want to panic when AI shifts the market as a Data Analyst. Do you? Because truth is, it’s already happening. AI is getting faster, dashboards smarter, and the industry noisier. But here’s the catch: AI isn’t replacing data analysts. It’s replacing analysts who refuse to evolve. The real skill now? → Turning data into direction. → Numbers into narratives. → Insights into impact. AI can process information, but it can’t feel context. It can’t replace your curiosity, intuition, or your ability to tell the story behind the numbers. So don’t panic. Learn the tools. Stay curious. Adapt fast. Because when the market shifts, those who evolve don’t lose, they lead it. Share your thoughts 💭 on this in the comment section. Cheers 🥂 to the new week. #DataAnalytics #AI

The state of #AI in 2025: #Agents, #innovation & #transformation- Key Takeaways from McKinsey & Company report ✅ Most organisations are still in the experimentation or piloting phase: Nearly two-thirds of respondents say their organisations have not yet begun scaling AI across the enterprise. ✅ High curiosity in AI agents: Sixty-two per cent of survey respondents say their organisations are at least experimenting with AI agents. ✅ Positive leading indicators on impact of AI: Respondents report use-case-level cost and revenue benefits, and 64 percent say that AI is enabling their innovation. However, just 39 percent report EBIT impact at the enterprise level. ✅ High performers use AI to drive growth, #innovation, and #cost: Eighty percent of respondents say their companies set efficiency as an objective of their AI initiatives, but the companies seeing the most value from AI often set growth or innovation as additional objectives. ✅ Redesigning workflows is a key success factor: Half of those AI high performers intend to use AI to transform their businesses, and most are redesigning workflows. ✅ Differing perspectives on employment impact: Respondents vary in their expectations of AI’s impact on the overall workforce size of their organizations in the coming year: 32 percent expect decreases, 43 percent no change, and 13 percent increases. #Bigdata #Artificialintelligence #AIAgent #Digitaltransformation #Technology #GenerativeAI #FinTech #Finserv #Regulation #RegTech Mike Flache Tony Moroney Francesco Burelli Panagiotis Kriaris Dr. Martha Boeckenfeld Prof. Dr. Ingrid Vasiliu-Feltes ®© Spiros Margaris Alex Jimenez Nicolas Babin Nicolas Pinto Amitav Bhattacharjee Sam Boboev Enrico Molinari Dr. Khulood Almani🇸🇦 د.خلود المانع Imtiaz Adam Eveline Ruehlin Peter Slattery, PhD Efi Pylarinou Victor Yaromin Digital Growth Collective Sharad Agarwal Helen Yu Dr. Debashis Dutta https://lnkd.in/gt95G4ws