\ud83c\udf0d “The world no longer changes in 2 years… but in 2 months.”<\/h2>\n
Between new AI models, protocols like MCP, LLM integrations and constant acceleration, the technological environment is evolving at an impressive speed.<\/p>\n
But beyond the “wow” effect, an interesting observation was shared:<\/p>\n
\ud83d\udcc8 AI adoption explodes.<\/p>\n
\ud83d\udcc9 The abandonment rate of AI projects too.<\/p>\n
Many companies have tried. Fewer have actually transformed these initiatives into measurable business impact. <\/p>\n
\ud83e\udd16 AI in analytics: two major gaps<\/h2>\n1\ufe0f\u20e3 The context gap<\/h3>\n
AI doesn’t need more data. It needs better context<\/strong>. <\/p>\n Counting actions is not enough. We need to understand the environment in which they occur. <\/p>\n A simple example: a drop in video consumption on a website. A problem? Not necessarily, if usage shifts to replay or podcast. <\/p>\n \ud83d\udc49 Without context, numbers can be misleading.<\/p>\n Analytics tools need to deliver more than just dashboards. They must produce concrete results<\/strong>. <\/p>\n SaaS is not “dead”, but it is being challenged: customers expect value that is more integrated, more activatable, more directly linked to business issues.<\/p>\n Two pillars structure the roadmap:<\/p>\n Structuring models, standardizing approaches, facilitating implementation.<\/p>\n Featuring :<\/p>\n The aim: to transform weeks of framing into a few clicks, and give AI a clean, coherent framework.<\/p>\n Circulate data throughout the company.<\/p>\n Some key developments:<\/p>\n \ud83d\udcca Workspace: <\/strong>ready-to-use workspaces based on activated data sources (and gradually the end of Explorer). A more dynamic logic, adapted to each organization. <\/p>\n \ud83d\udce9 Scheduled exports with IA summary: <\/strong>to move from a passive to a proactive logic.<\/p>\n Another major project:<\/p>\n A clear desire to give teams greater autonomy without making use more complex.<\/p>\n With MCP, you can :<\/p>\n But with a controlled approach: \u2714\ufe0f No cross-customer analysis \u2714\ufe0f Siloed data \u2714\ufe0f Possibility of AI opt-out according to internal constraints.<\/p>\n In today’s fast-paced environment, the temptation is great to “put AI everywhere”.<\/p>\n The vision shared here is more pragmatic:<\/p>\n An approach that echoes many of our current discussions with customers.<\/p>\n Perhaps the real question is no longer “how do we add AI?”. But rather: how do we make our data ecosystems truly exploitable and activatable?<\/strong> <\/p>\n As at the beginning of each year, Piano gathered its partners at its offices on rue Taitbout. An invaluable opportunity to move beyond operational projects and reflect on the evolution of our business. Many thanks to Samia ABARA (VP Partnerships) for her warm welcome, and to C\u00e9dric FERREIRA (Chief Product Officer) for a presentation that […]<\/p>\n","protected":false},"author":7,"featured_media":14109,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[42],"tags":[],"class_list":["post-14111","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-new-things"],"yoast_head":"\n2\ufe0f\u20e3 The outcomes gap<\/h3>\n
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\ud83e\udde9 The Piano answer: Data Excellence & Data Empowerment<\/h2>\n
\ud83d\udd39 Data Excellence<\/h3>\n
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\ud83d\udd39 Data Empowerment<\/h3>\n
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\ud83d\udd0e Data Query redesigned<\/h3>\n
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\ud83d\udd17 MCP: connecting LLMs to real data<\/h3>\n
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\ud83d\udca1 What we learned from it<\/h3>\n
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