Merit Data & Technology

30 minutes. Three practitioners. On 10 June, we are running a focused live session to help AI-accountable leaders:  - Understand what meaningful AI value measurement actually looks like in practice  - Identify the hidden costs and accountability gaps most programmes are carrying  - Build frameworks that work across strategy, operations, and delivery  - Develop a shared language that holds up in board-level conversations Sowmya Vivek, Kumaran Ponnambalam, and Tharun Mathew will share what they have seen, built, and applied across enterprise AI programmes, and what the evidence says about where most organisations are falling short. Just real frameworks and what they mean for your AI investment. Join us on 10 June | 4 PM BST | 8 AM PDT Register now. Link in comments.  

Your organisation is investing in AI. But can you prove it is working? Not in theory. Not in pilot metrics. In real, board-level terms. That is the question most AI programmes cannot answer cleanly. Not because the work is not happening, but because the frameworks to measure it, account for it, and communicate it simply are not in place. In this webinar, three practitioners break down the gaps that matter most: what to measure, what is being missed, and how to build accountability structures that hold at every level. If you are responsible for AI strategy, delivery, or outcomes, this session will change how you think about your programme. Register here: https://lnkd.in/gSygN43C 

The EU AI Act enters full enforcement soon. Most enterprises already know they need to act. What they underestimate is the root cause: it is not a compliance gap. It is an architectural one. 33% of organisations have no evidence-quality audit trails for their AI systems at all. A further 61% have fragmented logs spread across systems that cannot be reconciled into a defensible evidentiary record. The regulation does not ask whether you understand your data lineage. It asks whether that lineage lives in infrastructure that can produce structured, verifiable evidence on demand. For most legacy estates, the answer is no. Not because the systems are broken. Because they were built for a different purpose: operational debugging, not evidentiary defence. Buying a compliance platform does not fix this. If the data layer cannot produce evidence-grade lineage, no GRC tool sitting on top of it will conjure the evidence into existence. The good news: the foundational evidence capability can be built in 120 days for a defined high-risk scope, if the work is sequenced as a modernisation programme, not a compliance project. We have published the engineering blueprint. It covers what the Act actually requires article by article, why most legacy architecture can not satisfy it, and a phased 120-day roadmap that works in production environments. Download the whitepaper. Link in comments. #EUAIAct #LegacyModernisation #AIGovernance #DORA #EnterpriseAI #CIO #CTO 

Most AI programmes have a proof problem.  Not a technology problem. Not a talent problem. Not a budget problem. Boards are walking into conversations and asking harder questions than ever.  Most AI teams are walking in with activity metrics, not evidence. Deployment counts. Model accuracy scores. Throughput improvements.  Numbers that describe what the system is doing. Not what the business is gaining.  That gap is what this session is built to close. 10 June 2026 | 4:00 PM BST | 8:00 AM PDT  Three practitioners across GenAI strategy, ML engineering, and data and AI architecture who have built and led AI programmes at enterprise scale are running a 30-minute session on exactly this. Live session + Q&A Reserve your spot. Link in Comments. #AIStrategy #EnterpriseAI #GenerativeAI #AIAccountability #DigitalTransformation #CXO #TechLeadership #DataDriven #AILeadership #B2BWebinar

In 2026, ICP precision is not about who fits a description.  It is about who is showing the behaviour that predicts a purchase.  Four things are silently killing most B2B ICPs right now:  → The Title Trap: title-based targeting catches ~50% of buyers. The rest hold the same role under a different name.   → The Committee Blindspot: targeting one title in an 11-person deal means you're reaching 9% of the people who actually decide.   → The Static Snapshot: a persona defined in January is targeting a different group by June.   → Fit without intent: matching your ICP perfectly is not the same as being in market.  Signal velocity is the new metric. Not database size. Not persona precision. We've put together a full guide on this - including a five-step process to rebuild your ICP from your own won-deal data, and the three signals that consistently precede B2B purchases before most teams even notice.  The 2026 ICP Reset. Link in the first comment. #B2BMarketing #DemandGeneration #ICP #RevOps #MarketingStrategy

The hardest part of any AI programme is not building it. It is answering for it. On 10 June, practitioners from Cisco and Merit Data and Technology are spending 30 minutes on exactly that: how to measure AI value beyond cost savings, which costs most programmes are missing, and how to build accountability structures that hold up when leadership asks the hard questions. No pitch. No theory. Just what actually works in practice. Tharun Mathew, Sowmya Vivek, Kumaran Ponnambalam 10 June 2026 | 4:00 PM BST | 8:00 AM PDT | Live + Q&A Can't make it live? Register anyway. We will send the replay. Link to register in comments. #AI #EnterpriseAI #AIStrategy #AIAccountability #Webinar 

53% of retailers saw this shift coming back in 2020. In 2026, Location Intelligence is no longer a trend - it is a $32.8 billion market reshaping retail strategy. Today, success in retail is not just about where you are. It is about understanding why customers are there, how they move, and what influences their buying decisions in real time. Retailers that are not leveraging spatial data are leaving revenue opportunities open for competitors. Our latest deep dive explores 6 ways retailers are using Location Intelligence to drive smarter decisions and stronger margins: Site Selection: Move beyond static demographics with real-time traffic insights and competitor footfall analysis.  Store Layout Optimisation: Use geospatial heat maps to identify high-conversion zones and reduce customer bottlenecks.  Smarter Staffing Models: Align staffing schedules with live customer demand and walk-in trends.  Hyper-local Marketing: Deliver personalised offers based on in-store movement and customer intent. The equation is simple: Static Mapping = Missed Footfall.  Location Intelligence = Competitive Advantage  Explore all 6 strategies here: https://lnkd.in/ghGMGNeD

It is Saturday. Nobody wants to talk about marketing data.     Except the person who just opened their campaign results.     They bought a list in March. 40,000 contacts. The vendor called it premium. The vendor called it verified. The vendor did not mention that premium and verified both refer to when it was last checked, which was not recently.     The open rates are low. The bounces are not. The domain reputation is having a difficult morning.     This is not a rare story.      The problem was never the size of the list. It was the assumption that data sitting in a database stays accurate while the world keeps moving. People change jobs. Companies restructure. Inboxes close. Nobody updates the spreadsheet.     Merit has no database to go stale. Every list is built from scratch, researched live, for the exact audience you need, at the moment you need it. What arrives with you is current, compliant, and has not been sold to the three agencies operating in your space.     Most marketing problems that show up in the results started much earlier, in the data.     https://lnkd.in/geAp4QBM     #ZeroDatabase #MarketingData #B2BMarketing #EmailMarketing #DataQuality 

The ICP framework is not the problem. The data underneath it is. The filters look right. The industry fits. The headcount applies. The job titles check out. What they cannot tell you is whether that company has budget available right now. Or whether a new leader just joined and is about to run a vendor review. Or whether they are six weeks into a migration that makes them an immediate prospect. Firmographics describe a company as it was. Not as it is. The shift in 2026 is from profile-based targeting to signal-based targeting. Leadership changes. Funding rounds. Technology migrations. Rapid hiring in a specific function. These are not background details. They are the signals that a company is in motion, and motion is where buying decisions happen. The teams outperforming their categories are not working from bigger lists. They are working from better signals, stacked together to identify accounts with an active buying window, before competitors even know to look. We have published a full breakdown of how this works in practice. Link in the comments. #ICPStrategy #B2BMarketing #DemandGeneration #SignalBasedSelling #MarketingData 

The demos went well. Six months later, leadership wants to know what it returned. Most AI teams are not ready for that question. Not because the work was not done. Because the accountability structures were never built alongside it. That is not a technology problem. That is a structural one. And it is the conversation most organisations are quietly avoiding. On 10 June, we are having it out loud. Three practitioners who have built these systems in the real world, sharing what actually works. Sowmya Vivek, AI Solutioning Consultant and GenAI Strategist, Merit Data and Technology, Kumaran Ponnambalam, Principal ML Engineer, Cisco & Tharun Mathew, Head of Data and AI Solutions, Merit Data & Technology. 30 minutes. No pitch. No theory. Just the blueprint for making AI investment answerable. 10 June 2026 | 4:00 PM BST | 8:00 AM PDT | Live + Q&A Can't make it live? Register anyway. We will share the recording. Link to register in comments. #AI #EnterpriseAI #AIStrategy #DigitalTransformation #Webinar