REGISTRATION & COFFEE
Let's be honest: many organizations are diving headfirst into AI, but their data culture is shaky - at best. This gap between AI ambition and data maturity is a recipe for disappointment, leading to failed projects, wasted resources, and frustration. It's a familiar story; the business demands supersonic speed, but the data infrastructure is stuck on dial-up. The biggest challenge is however not technology, but cultural resistance to change. Without buy-in from business units and senior management, even the best AI strategies stall. Real maturity starts with honest conversations about what’s not working and a willingness to address legacy processes and mindsets. The point isn’t perfection, and while speed matters, sustainable speed wins. Keep the board onside, your teams invested, and vision realistic when budgets tighten and patience thins to prepare for AI that delivers.
Onboarding a new AI solution is the start of the risk curve, not the finish. New product features land faster than legal can read existing T&Cs, creating risk and delays. The smart move is a standing rulebook, rather than a case-by-case evaluation of each vendor feature. Learn how to reduce feature approval times with reusable due-diligence packs and a standard AI addendum vendors sign once.
Your AI is only as good as the data you feed it. Rubbish in, liability out.
Governance is a team sport and only works when built on top of delivery workflows, not layered over it – when people don’t’ actually use it, operations stall. Too often, rules sit outside the frontline, so teams wait weeks for approvals, chase definitions, or re-check what should be obvious or immediately accessible. The fix is simple: ownership in business teams, clear decision rights, findable definitions, and lineage captured automatically – the result? Saved time, energy, and sanity. A central-but-open library keeps people aligned, while reusable evidence packs and event-based approvals replace 11th-hour bottlenecks and cut delays before they start.
With AI models like DeepSeek R1 and OpenAI’s o3 mastering the art of reasoning, Business Intelligence stands at the cusp of a paradigm shift. Once synonymous with dashboards - or simply “PowerPoint for Data” - BI is now rapidly evolving into a proactive system where AI actively answers our most critical business questions. As AI continues to advance, it won't merely assist - it will proactively answer thousands of insightful questions in the time it takes a human to ask one.
Conflicting definitions and fragmented metrics erode trust and slow innovation. Real impact only happens when organisations establish clear, consistent metrics, guardrails, and decision-ready products that teams adopt at scale. At Booking.com, scaling experimentation and measurement required:
Pick your challenge focused seat during lunch, and get to network with peers who are focused on similar blockers – walk away with new contacts, and solutions to what’s holding you back
Freedom and autonomy to explore and exploit data is great. Accelerated speed-to-insight, experimentation, and unburdening data teams from ad-hoc requests. The catch? Spreadsheet and tool sprawl, skewed dashboards, and unintended data leak risk. The fix isn’t increased gatekeeping; it’s better guardrails.
The modern data stack is a complex ecosystem. Choosing the right data platform is one of the biggest bets a data leader can make, with long-term consequences for cost, agility, and innovation. Integrated suite or focused tools? Buy, build, or a little of both? With margins tight, the wrong call drags year-round. With hyperscaler alliances shaping who you can do business with for years to come, platform decisions need to align with long term business strategy, not just immediate technical or budgetary concerns - you don’t want to be boxed in roadmaps you can’t influence. Done right however, platform strategy unlocks efficiency without trading freedom for convenience.
Think Tank | Data Commercialization Lab - From Hypothesis to Pilot
Keeping legacy data feels safe, but it slows innovation, buries insights, and swells bills. Legal retention collides with messy, unstructured sprawl - emails, SharePoint duplicates, local copies. Hoarding becomes a comfortable habit, not strategy; all while most value still only sits in a small slice of data. Your technology is not to blame – it’s culture that makes data bloat stick around. Tackle the perception that all data matters equally, and embed a data cleansing culture that saves time, energy, and patience. The win? Accelerated time-to-insight, cheaper legacy modernisation, and a database your team can actually work with.