Artificial intelligence has moved past the experimental phase. After months of talk about upcoming transformation, it’s now embedded in operations and business processes<\/b>. But between the initial buzz and real implementation, many organizations still struggle to turn potential into tangible value.<\/p>\n
A recent study by the Wharton School and GBK Collective<\/b> paints an interesting picture: generative AI is no longer a novelty for executives, it\u2019s becoming a performance lever<\/b>. Tools like ChatGPT, Copilot, and Midjourney are being woven into daily workflows. But a key question remains: how can we ensure these tools actually improve business performance?<\/b><\/p>\nFrom experimenting to creating real value<\/h2>\n
That\u2019s where the mindset is shifting. Businesses no longer want to \u201cdo AI\u201d just to keep up with trends. They want to measure its impact<\/b>. The FOMO (fear of missing out) is giving way to a more rational approach: getting a real return on investment, in both the short and long term.<\/p>\n
But the transformation doesn\u2019t depend solely on the tech. It relies on three key pillars: processes, data, and people<\/b>.<\/p>\nAI without visibility is like flying blind<\/h2>\n
AI needs reliable data to learn, suggest, and make decisions. But in most organizations, that data is stuck in silos or fragmented systems.<\/p>\n
That\u2019s where Process Mining<\/b> comes in.<\/p>\n
By analyzing digital footprints left in enterprise systems (ERP, CRM, ITSM, etc.), Process Mining maps how processes actually run<\/b>, not how we assume they do. This visibility allows:<\/p>\n AI without Process Mining, or vice versa, limits the full potential of transformation. But when combined, they turn data into measurable action<\/b>.<\/p>\n The most forward-thinking organizations aren\u2019t just looking to automate. They\u2019re aiming for continuous improvement<\/b>.<\/p>\n With Process Mining, AI can:<\/p>\n This is what we see in the field, especially in the mandates we support: the real gains come from combining visibility, analysis, and action in a smart way.<\/b><\/p>\n AI isn\u2019t a magic bullet. It\u2019s a lever. And like any lever, it only works if it\u2019s grounded on something solid.<\/p>\n Process mining provides that foundation. Together, they help organizations act with clarity, and turn AI into a tool for continuous improvement, not an isolated experiment.<\/p>\n Can your AI truly improve what it can\u2019t see?<\/p>\n That\u2019s the question every business should ask before moving forward.<\/p>\n","protected":false},"excerpt":{"rendered":" AI: beyond the hype Artificial intelligence has moved past the experimental phase. After months of talk about upcoming transformation, it’s now embedded in operations and business processes. But between the initial buzz and real implementation, many organizations still struggle to turn potential into tangible value. A recent study by the Wharton School and GBK Collective […]<\/p>\n","protected":false},"author":3,"featured_media":60493,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[77],"tags":[],"class_list":["post-60498","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-process-mining-en-en"],"yoast_head":"\n\n
How AI and Process Mining work together<\/h2>\n
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Bottom line: see before you act<\/h2>\n