BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Chicago BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0600 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:CDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20251102T010000 TZOFFSETFROM:-0500 TZOFFSETTO:-0600 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:CST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260220T224623Z UID:39EA62B9-0DC7-4AFD-B9C0-B0D7499CC216 DTSTART;TZID=America/Chicago:20260219T183000 DTEND;TZID=America/Chicago:20260219T200000 DESCRIPTION:AI is increasingly being embedded in enterprise systems used to determine how technology products are launched\, adopted\, and scaled. Pr edictive models and automated workflows have started to influence decision s traditionally made by humans\, such as customer prioritization\, activat ion sequencing\, and intervention timing. While these systems improve effi ciency\, many organizations struggle to achieve reliable scale in producti on. Metrics apapear healthy\, automation is in place\, yet outcomes remain inconsistent. The underlying issue is often not model performance or data availability\, but activation - the point at which users reliably reach v alue.\n\nThis webinar reframes activation as a systems level bottleneck in AI enabled go-to-market (GTM) environments. Rather than treating activati on as a binary milestone\, it is considered as a probabilistic\, signal dr iven process that directly affects scalability. When activation signals ar e weak\, delayed\, or poorly governed\, automation amplifies variance and prevents systems from scaling predictably.\n\nThe session introduces a pra ctical systems framework that integrates predictive activation signals\, d ecision boundaries\, privacy regulations and governance mechanisms to supp ort reliable scaling. Emphasis is placed on engineering principles\, measu rement integrity and human oversight rather than business tactics or tool selection. The webinar is relevant to engineers and technical leaders desi gning AI systems that operate at scale under real-world constraints\, wher e reliability\, accountability\, and interpretability matter as much as pe rformance.\n\nSpeaker(s): Jagbir Kaur\n\nAgenda: \n6:25 to 6:35 PM - Open for participants to enter and network.\n6:35 to 6:40 PM - IEEE LM and CTCN Business meeting and to introduce speaker.\n6:40 to 7:55PM - Formal Progr am and Q&A.\n\nVirtual: https://events.vtools.ieee.org/m/538139 LOCATION:Virtual: https://events.vtools.ieee.org/m/538139 ORGANIZER:bill.martino@ieee.org SEQUENCE:103 SUMMARY:IEEE CTS CTCN/LMAG Zoom Meeting\, 2-19-2026\, "Scaling Bottleneck o f Activation in AI Enabled Go-To-Market Systems" URL;VALUE=URI:https://events.vtools.ieee.org/m/538139 X-ALT-DESC:Description: <br /><p class="MsoNormal"><span lang="EN" style="f ont-size: 14pt\;">AI is increasingly being embedded in enterprise systems used to determine how technology products are launched\, adopted\, and sca led. Predictive models and automated workflows have started to influence d ecisions traditionally made by humans\, such as customer prioritization\, activation sequencing\, and intervention timing. While these systems impro ve efficiency\, many organizations struggle to achieve reliable scale in p roduction. Metrics apapear healthy\, automation is in place\, yet outcomes remain inconsistent. The underlying issue is often not model performance or data availability\, but activation - the point at which users reliably reach value.</span></p>\n<p class="MsoNormal"><span lang="EN" style="font- size: 14pt\;">This webinar reframes activation as a systems level bottlene ck in AI enabled go-to-market (GTM) environments. Rather than treating act ivation as a binary milestone\, it is considered as a probabilistic\, sign al driven process that directly affects scalability. When activation signa ls are weak\, delayed\, or poorly governed\, automation amplifies variance and prevents systems from scaling predictably.</span></p>\n<p class="MsoN ormal"><span lang="EN" style="font-size: 14pt\;">The session introduces a practical systems framework that integrates predictive activation signals\ , decision boundaries\, privacy regulations and governance mechanisms to s upport reliable scaling. Emphasis is placed on engineering principles\, me asurement integrity and human oversight rather than business tactics or to ol selection. The webinar is relevant to engineers and technical leaders d esigning AI systems that operate at scale under real-world constraints\, w here reliability\, accountability\, and interpretability matter as much as performance.</span></p><br /><br />Agenda: <br /><div dir="ltr" data-setd ir="false">6:25 to 6:35 PM - Open for participants to enter and network.&n bsp\;</div>\n<div dir="ltr" data-setdir="false">6:35 to 6:40 PM - IEEE LM and CTCN Business meeting and to introduce speaker.</div>\n<div dir="ltr" data-setdir="false">6:40 to 7:55PM - Formal Program and Q&amp\;A.&nbsp\;</ div> END:VEVENT END:VCALENDAR