In this episode, product manager Raghu Vemuri talks about the PI Workbench application, new in the Paris release. PI Workbench helps you add machine learning (ML) to your ServiceNow workflows, and monitor and manage the results. This episode covers:
What is PI Workbench all about?
Common use cases
Pretrained ML models
Using Guided Setup to create ML models
Help with implementing ML
Performance analytics for ML
Getting started

For more information, see:
Product documentation: ITSM Predictive Intelligence Workbench
Product documentation: HR Predictive Intelligence Workbench
Predictive Intelligence Community: Predictive Intelligence  

Your feedback helps us serve you better! Did you find this podcast helpful? Please leave a comment to tell us why or why not.

Subscribe to iTunes

In this episode, product manager Raghu Vemuri talks about the PI Workbench application, new in the Paris release. PI Workbench helps you add machine learning (ML) to your ServiceNow workflows, and monitor and manage the results. This episode covers:
<ul>
<li>What is PI Workbench all about?</li>
<li>Common use cases</li>
<li>Pretrained ML models</li>
<li>Using Guided Setup to create ML models</li>
<li>Help with implementing ML</li>
<li>Performance analytics for ML</li>
<li>Getting started</li>
</ul>
For more information, see:
<ul>
<li>Product documentation: <a href="https://docs.servicenow.com/bundle/paris-it-service-management/page/product/itsm-predictive-intel-workbench/concept/itsm-piwb-landing-page.html">ITSM Predictive Intelligence Workbench</a></li>
<li>Product documentation: <a href="https://docs.servicenow.com/bundle/paris-hr-service-delivery/page/product/human-resources/concept/hr-predictive-intelligence-wb.html">HR Predictive Intelligence Workbench</a></li>
<li>Predictive Intelligence Community: <a href="https://community.servicenow.com/community?id=community_topic&amp;sys_id=05bccb30db596b00d58ea345ca9619ee">Predictive Intelligence </a>&nbsp;</li>
</ul>
Your feedback helps us serve you better! Did you find this podcast helpful? Please leave a comment to tell us why or why not.
<a href="https://itunes.apple.com/us/podcast/servicenow-techbytes/id1038560176?mt=2">Subscribe</a>&nbsp;to iTunes

ServiceNow Insights is your insider’s guide to the world of ServiceNow. Join us as we unpack the latest products, innovations, and updates with in-depth discussions led by the creators behind the platform. Hear firsthand about the challenges they've overcome, the solutions they've pioneered, and the exciting future they envision. Whether you're a seasoned admin, agent, platform owner, or just discovering the power of ServiceNow,  and offers valuable insights to help you stay informed and leverage the full potential of the platform.

ServiceNow Insights&nbsp;is your insider&rsquo;s guide to the world of ServiceNow. Join us as we unpack the latest products, innovations, and updates with in-depth discussions led by the creators behind the platform. Hear firsthand about the challenges they've overcome, the solutions they've pioneered, and the exciting future they envision. Whether you're a seasoned admin, agent, platform owner, or just discovering the power of ServiceNow,&nbsp;&nbsp;and offers valuable insights to help you stay informed and leverage the full potential of the platform.

ServiceNow TechBytes is a Podcast Program hosted …

ServiceNow Insights 

ServiceNow Podcast Program is a collection of podcast shows hosted by various ServiceNow experts and professionals covering different focus areas and a broad variety of topics. Come listen to our experts talk about what's going on at ServiceNow. Join the conversation!

Visit the Now Community forums

ServiceNow Podcast Program is a collection of podcast shows hosted by various ServiceNow experts and professionals covering different focus areas and a broad variety of topics. Come listen to our experts talk about what's going on at ServiceNow. Join the conversation!
<a href="https://community.servicenow.com/community">Visit the Now Community forums</a>

ServiceNow Podcasts

ServiceNow Insights Podcast

Episode 58: Predictive Intelligence Workbench

Why multilingual content is a business risk, a compliance question, and an AI-readiness problem - not just a translation checkbox - with ServiceNow's Lyena Solomon.

#ServiceNow #Localization #Globalization #AI

Chapters

00:00  Cold open: "half ten" and the meaning problem
00:29  Welcome + episode topic
00:53  Meet Lyena Solomon
01:12  Why this isn't just translation
03:49  The word "order" - context matters
05:05  What is language governance?
06:04  Translating "pizza"
07:03  The regulatory reality (Quebec, EU AI Act)
09:30  Self-localization: Maori and Inuktitut
13:23  The real business risk of inconsistency
15:43  AI readiness and language risk
16:28  A support ticket in three languages
20:32  It's about trust, not just translation
21:11  Closing thought: the joy of understanding
22:17  Wrap-up + subscribe

For more about ServiceNow - https://www.youtube.com/@ServiceNowDocs
To watch these episodes on YouTube - https://www.youtube.com/watch?v=yxoHmZj5gOk&list=PLCOmiTb5WX3qvGq7Cp3o2KkCiplJyqQOK

 

Why multilingual content is a business risk, a compliance question, and an AI-readiness problem - not just a translation checkbox - with ServiceNow's Lyena Solomon.
#ServiceNow #Localization #Globalization #AI
Chapters
00:00&nbsp; Cold open: "half ten" and the meaning problem 00:29&nbsp; Welcome + episode topic 00:53&nbsp; Meet Lyena Solomon 01:12&nbsp; Why this isn't just translation 03:49&nbsp; The word "order" - context matters 05:05&nbsp; What is language governance? 06:04&nbsp; Translating "pizza" 07:03&nbsp; The regulatory reality (Quebec, EU AI Act) 09:30&nbsp; Self-localization: Maori and Inuktitut 13:23&nbsp; The real business risk of inconsistency 15:43&nbsp; AI readiness and language risk 16:28&nbsp; A support ticket in three languages 20:32&nbsp; It's about trust, not just translation 21:11&nbsp; Closing thought: the joy of understanding 22:17&nbsp; Wrap-up + subscribe For more about ServiceNow - <a href="https://www.youtube.com/@ServiceNowDocs">https://www.youtube.com/@ServiceNowDocs</a> To watch these episodes on YouTube - <a href="https://www.youtube.com/watch?v=yxoHmZj5gOk&amp;list=PLCOmiTb5WX3qvGq7Cp3o2KkCiplJyqQOK">https://www.youtube.com/watch?v=yxoHmZj5gOk&amp;list=PLCOmiTb5WX3qvGq7Cp3o2KkCiplJyqQOK</a>
&nbsp;

Why Translation Isn't the Same as Understanding | Multilingual Content at ServiceNow

Voice AI sounds simple until you try to deploy it at scale — across airports, accents, languages, and thousands of employees at once.

In this episode of ServiceNow Insights, host Bobby Brill sits down with Midam Kim, an ML engineer and linguist at ServiceNow, to unpack what it actually takes to build voice AI as an enterprise product. From the out-of-vocabulary problem (why AI still struggles with names) to why turn-taking in conversation is a linguistic skill most people never think about, Midam breaks down the human science behind the technology.

 In this episode:

- Why voice AI is replacing typing as the default way to interact with enterprise systems

 - The difference between building for employees (B2B) vs. building for their customers (B2B2C)

 - Why an airport is one of the hardest possible environments for voice AI — and what ServiceNow does about it

 - The "out-of-vocabulary" problem: why AI still struggles with names, accents, and rare expressions

 - Why ServiceNow's secret sauce is hiring linguists, not just engineers

 - The linguistic framework behind every voice interaction: sounds, words, and turn-taking

 - Why voice AI is like teaching a kid to speak for the first time

Chapters
00:00 — Welcome to ServiceNow Insights
00:22 — Meet Midam Kim, ML Engineer & Linguist
00:35 — Why voice is replacing typing
01:48 — What voice AI actually does for employees
03:40 — B2B vs. B2B2C: who's really using this?
05:11 — Desk employee vs. airport traveler: two different problems
06:42 — Building for an ever-changing environment
08:53 — Why airports are the hardest use case
09:54 — Accents, fluency, and the diversity problem
11:20 — "My Name Is. My Name Is. My Name Is." — the OOV problem
12:50 — The coffee shop name story
13:20 — How ServiceNow trains its models
14:59 — The 3 linguistic layers: sounds, words, interaction
16:38 — Midam's turn-taking story from Korea
18:33 — Why voice agents can't be "that person you avoid"
20:16 — "We can make it great"

 Subscribe for more ServiceNow Insights episodes on AI, voice technology, and enterprise innovation.

Related episode: Voice AI Agent Evaluation — how ServiceNow measures whether voice AI meets human expectations. https://youtu.be/x7Ks932T18o

For more about voice in AI from Midam Kim - https://youtu.be/3NUf6W_FMWs?is=wGc7BfyhiDp8JlOW

 #VoiceAI #EnterpriseAI #ServiceNow #ArtificialIntelligence #Linguistics #ConversationalAI #AIProduct #Podcast

Voice AI sounds simple until you try to deploy it at scale &mdash; across&nbsp;airports, accents, languages, and thousands of employees at once.
In this episode of ServiceNow Insights, host Bobby Brill sits down with Midam Kim, an ML engineer and linguist at ServiceNow, to unpack what it actually takes to build voice AI as an enterprise product. From the out-of-vocabulary problem (why AI still struggles with names) to why turn-taking&nbsp;in&nbsp;conversation&nbsp;is&nbsp;a&nbsp;linguistic&nbsp;skill&nbsp;most&nbsp;people&nbsp;never&nbsp;think&nbsp;about,&nbsp;Midam&nbsp;breaks&nbsp;down&nbsp;the&nbsp;human&nbsp;science&nbsp;behind&nbsp;the&nbsp;technology.
&nbsp;In this episode:
- Why voice AI is replacing typing as the default way to interact with&nbsp;enterprise systems
&nbsp;- The difference between building for employees (B2B) vs. building for their&nbsp;customers&nbsp;(B2B2C)
&nbsp;- Why an airport is one of the hardest possible environments for voice&nbsp;AI&nbsp;&mdash;&nbsp;and&nbsp;what&nbsp;ServiceNow&nbsp;does&nbsp;about&nbsp;it
&nbsp;- The "out-of-vocabulary" problem: why AI still struggles with names,&nbsp;accents,&nbsp;and&nbsp;rare&nbsp;expressions
&nbsp;-&nbsp;Why&nbsp;ServiceNow's&nbsp;secret&nbsp;sauce&nbsp;is&nbsp;hiring&nbsp;linguists,&nbsp;not&nbsp;just&nbsp;engineers
&nbsp;- The linguistic framework behind every voice interaction: sounds,&nbsp;words,&nbsp;and&nbsp;turn-taking
&nbsp;- Why voice AI is like teaching a kid to speak for the first time
Chapters 00:00 &mdash; Welcome to ServiceNow Insights 00:22 &mdash; Meet Midam Kim, ML Engineer &amp; Linguist 00:35 &mdash; Why voice is replacing typing 01:48 &mdash; What voice AI actually does for employees 03:40 &mdash; B2B vs. B2B2C: who's really using this? 05:11 &mdash; Desk employee vs. airport traveler: two different problems 06:42 &mdash; Building for an ever-changing environment 08:53 &mdash; Why airports are the hardest use case 09:54 &mdash; Accents, fluency, and the diversity problem 11:20 &mdash; "My Name Is. My Name Is. My Name Is." &mdash; the OOV problem 12:50 &mdash; The coffee shop name story 13:20 &mdash; How ServiceNow trains its models 14:59 &mdash; The 3 linguistic layers: sounds, words, interaction 16:38 &mdash; Midam's turn-taking story from Korea 18:33 &mdash; Why voice agents can't be "that person you avoid" 20:16 &mdash; "We can make it great"
&nbsp;Subscribe for more ServiceNow Insights episodes on AI, voice&nbsp;technology,&nbsp;and&nbsp;enterprise&nbsp;innovation.
Related episode: Voice AI Agent Evaluation &mdash; how ServiceNow measures&nbsp;whether&nbsp;voice&nbsp;AI&nbsp;meets&nbsp;human&nbsp;expectations.&nbsp;https://youtu.be/x7Ks932T18o
For more about voice in AI from Midam Kim -&nbsp;<a href="https://youtu.be/3NUf6W_FMWs?is=wGc7BfyhiDp8JlOW">https://youtu.be/3NUf6W_FMWs?is=wGc7BfyhiDp8JlOW</a>
&nbsp;#VoiceAI #EnterpriseAI #ServiceNow #ArtificialIntelligence #Linguistics #ConversationalAI #AIProduct #Podcast

Teaching a Computer to Speak | Voice AI in the Real World 

Most organizations deploying AI agents can’t answer a basic question: is it actually working? Not whether the agent runs — whether the process actually got better.

In Episode 3 of our process mining and process intelligence series, Damian Pascale and Roz Parpia join host Bobby Brill to go deep on what it actually looks like to run process intelligence with AI in the mix — from the AI Visibility Gap, to a four-step framework for finding the right AI use cases, to what “closed loop intelligence” really means once agents are governing agents.

This episode’s answer to the recurring question: don’t automate the chaos. Find it, understand it, improve it — then, and only then, streamline it.

 

CHAPTERS

0:00  Introduction — Damian Pascale & Roz Parpia

0:56  “Don’t automate the chaos” — where the phrase comes from

2:25  Process mining vs. process intelligence — what actually changed

4:21  The linchpin: where AI fits across all three layers

5:36  The AI Visibility Gap — what most organizations are missing

6:56  A real example: when agent metrics look great, but quality doesn’t

8:13  The four-step framework: Find, Understand, Improve, Streamline

11:27  Where AI comes into streamlining — sizing the right use cases

13:19  Does the order of the four steps actually matter?

14:04  Task Mining — the human side process mining can’t see

15:19  A concrete example: the procurement approval bottleneck

16:31  The closed loop — six steps to continuous improvement

17:30  Why you can never skip the ‘detect’ step

18:05  Measuring real impact with the compare feature

19:25  Governance and AI Control Tower, explained simply

20:46  Mining the agents themselves — a third layer of visibility

21:36  Closed loop intelligence — the three layers, confirmed

22:48  Day one: what to do after deploying your first agent

23:38  Closing thoughts from both guests

24:26  Wrap-up

 

IN THIS EPISODE

• Why an AI agent doesn’t fix a broken process — it just runs the broken process faster

• The real difference between process mining and process intelligence: three layers in one

• The AI Visibility Gap: why almost every customer has deployed an agent, but few can prove it’s working

• A real customer example — an agent that improved response time but quietly increased the reopen rate

• The four-step framework for AI-ready process improvement: Find, Understand, Improve, Streamline

• The 2–15 minute rule (and the 3–9 minute sweet spot) for sizing the right AI agent use cases

• Why skipping straight to automation is exactly how you end up automating the chaos

• Task Mining and the procurement approval example — 45 minutes across four systems, invisible to process mining alone

• The six steps of the closed loop, and why the ‘detect’ step is the one everyone skips

• Using the compare feature to measure whether an AI agent actually helped — or just moved the problem

• AI Control Tower, explained simply — and how it becomes a third layer of process intelligence

• Closed loop intelligence: the agent, the governance, and the agent’s own behavior — all observable, all improving

 

GET STARTED

If you’re a ServiceNow customer, you already have access to free evaluation projects — no license needed.

https://www.servicenow.com/au/products/process-mining/get-started.html

https://www.servicenow.com/docs/r/now-intelligence/process-mining/process-mining.html

https://www.youtube.com/watch?v=TVrU0TQ7ldM

https://www.youtube.com/watch?v=GLKROYqnc10

 

#ServiceNow #ProcessMining #ProcessIntelligence #AIAgents #AgenticAI #TaskMining #AIGovernance #AIControlTower #WorkflowAutomation #DigitalTransformation #ContinuousImprovement #ClosedLoopIntelligence #ServiceNowPodcast #EnterpriseAI #DontAutomateTheChaos

Most&nbsp;organizations&nbsp;deploying&nbsp;AI&nbsp;agents&nbsp;can&rsquo;t&nbsp;answer&nbsp;a&nbsp;basic&nbsp;question:&nbsp;is&nbsp;it&nbsp;actually&nbsp;working?&nbsp;Not&nbsp;whether&nbsp;the&nbsp;agent&nbsp;runs&nbsp;&mdash;&nbsp;whether&nbsp;the&nbsp;process&nbsp;actually&nbsp;got&nbsp;better.
In Episode 3 of our process mining and process intelligence series, Damian Pascale and Roz Parpia join host Bobby Brill to go deep on what it actually looks like to run process intelligence with AI in the mix &mdash; from the AI Visibility Gap, to a four-step framework for finding the right AI use cases, to what &ldquo;closed loop intelligence&rdquo; really means once agents are governing agents.
This episode&rsquo;s answer to the recurring question: don&rsquo;t automate the chaos. Find it, understand it, improve it &mdash; then, and only then, streamline it.
&nbsp;
CHAPTERS
0:00&nbsp;&nbsp;Introduction&nbsp;&mdash;&nbsp;Damian&nbsp;Pascale&nbsp;&amp;&nbsp;Roz&nbsp;Parpia
0:56&nbsp;&nbsp;&ldquo;Don&rsquo;t&nbsp;automate&nbsp;the&nbsp;chaos&rdquo;&nbsp;&mdash;&nbsp;where&nbsp;the&nbsp;phrase&nbsp;comes&nbsp;from
2:25&nbsp;&nbsp;Process&nbsp;mining&nbsp;vs.&nbsp;process&nbsp;intelligence&nbsp;&mdash;&nbsp;what&nbsp;actually&nbsp;changed
4:21&nbsp;&nbsp;The&nbsp;linchpin:&nbsp;where&nbsp;AI&nbsp;fits&nbsp;across&nbsp;all&nbsp;three&nbsp;layers
5:36&nbsp;&nbsp;The&nbsp;AI&nbsp;Visibility&nbsp;Gap&nbsp;&mdash;&nbsp;what&nbsp;most&nbsp;organizations&nbsp;are&nbsp;missing
6:56&nbsp;&nbsp;A&nbsp;real&nbsp;example:&nbsp;when&nbsp;agent&nbsp;metrics&nbsp;look&nbsp;great,&nbsp;but&nbsp;quality&nbsp;doesn&rsquo;t
8:13&nbsp;&nbsp;The&nbsp;four-step&nbsp;framework:&nbsp;Find,&nbsp;Understand,&nbsp;Improve,&nbsp;Streamline
11:27&nbsp;&nbsp;Where&nbsp;AI&nbsp;comes&nbsp;into&nbsp;streamlining&nbsp;&mdash;&nbsp;sizing&nbsp;the&nbsp;right&nbsp;use&nbsp;cases
13:19&nbsp;&nbsp;Does&nbsp;the&nbsp;order&nbsp;of&nbsp;the&nbsp;four&nbsp;steps&nbsp;actually&nbsp;matter?
14:04&nbsp;&nbsp;Task&nbsp;Mining&nbsp;&mdash;&nbsp;the&nbsp;human&nbsp;side&nbsp;process&nbsp;mining&nbsp;can&rsquo;t&nbsp;see
15:19&nbsp;&nbsp;A&nbsp;concrete&nbsp;example:&nbsp;the&nbsp;procurement&nbsp;approval&nbsp;bottleneck
16:31&nbsp;&nbsp;The&nbsp;closed&nbsp;loop&nbsp;&mdash;&nbsp;six&nbsp;steps&nbsp;to&nbsp;continuous&nbsp;improvement
17:30&nbsp;&nbsp;Why&nbsp;you&nbsp;can&nbsp;never&nbsp;skip&nbsp;the&nbsp;&lsquo;detect&rsquo;&nbsp;step
18:05&nbsp;&nbsp;Measuring&nbsp;real&nbsp;impact&nbsp;with&nbsp;the&nbsp;compare&nbsp;feature
19:25&nbsp;&nbsp;Governance&nbsp;and&nbsp;AI&nbsp;Control&nbsp;Tower,&nbsp;explained&nbsp;simply
20:46&nbsp;&nbsp;Mining&nbsp;the&nbsp;agents&nbsp;themselves&nbsp;&mdash;&nbsp;a&nbsp;third&nbsp;layer&nbsp;of&nbsp;visibility
21:36&nbsp;&nbsp;Closed&nbsp;loop&nbsp;intelligence&nbsp;&mdash;&nbsp;the&nbsp;three&nbsp;layers,&nbsp;confirmed
22:48&nbsp;&nbsp;Day&nbsp;one:&nbsp;what&nbsp;to&nbsp;do&nbsp;after&nbsp;deploying&nbsp;your&nbsp;first&nbsp;agent
23:38&nbsp;&nbsp;Closing&nbsp;thoughts&nbsp;from&nbsp;both&nbsp;guests
24:26&nbsp;&nbsp;Wrap-up
&nbsp;
IN&nbsp;THIS&nbsp;EPISODE
&bull; Why an AI agent doesn&rsquo;t fix a broken process &mdash; it just runs the broken process faster
&bull;&nbsp;The&nbsp;real&nbsp;difference&nbsp;between&nbsp;process&nbsp;mining&nbsp;and&nbsp;process&nbsp;intelligence:&nbsp;three&nbsp;layers&nbsp;in&nbsp;one
&bull;&nbsp;The&nbsp;AI&nbsp;Visibility&nbsp;Gap:&nbsp;why&nbsp;almost&nbsp;every&nbsp;customer&nbsp;has&nbsp;deployed&nbsp;an&nbsp;agent,&nbsp;but&nbsp;few&nbsp;can&nbsp;prove&nbsp;it&rsquo;s&nbsp;working
&bull;&nbsp;A&nbsp;real&nbsp;customer&nbsp;example&nbsp;&mdash;&nbsp;an&nbsp;agent&nbsp;that&nbsp;improved&nbsp;response&nbsp;time&nbsp;but&nbsp;quietly&nbsp;increased&nbsp;the&nbsp;reopen&nbsp;rate
&bull;&nbsp;The&nbsp;four-step&nbsp;framework&nbsp;for&nbsp;AI-ready&nbsp;process&nbsp;improvement:&nbsp;Find,&nbsp;Understand,&nbsp;Improve,&nbsp;Streamline
&bull;&nbsp;The&nbsp;2&ndash;15&nbsp;minute&nbsp;rule&nbsp;(and&nbsp;the&nbsp;3&ndash;9&nbsp;minute&nbsp;sweet&nbsp;spot)&nbsp;for&nbsp;sizing&nbsp;the&nbsp;right&nbsp;AI&nbsp;agent&nbsp;use&nbsp;cases
&bull;&nbsp;Why&nbsp;skipping&nbsp;straight&nbsp;to&nbsp;automation&nbsp;is&nbsp;exactly&nbsp;how&nbsp;you&nbsp;end&nbsp;up&nbsp;automating&nbsp;the&nbsp;chaos
&bull;&nbsp;Task&nbsp;Mining&nbsp;and&nbsp;the&nbsp;procurement&nbsp;approval&nbsp;example&nbsp;&mdash;&nbsp;45&nbsp;minutes&nbsp;across&nbsp;four&nbsp;systems,&nbsp;invisible&nbsp;to&nbsp;process&nbsp;mining&nbsp;alone
&bull;&nbsp;The&nbsp;six&nbsp;steps&nbsp;of&nbsp;the&nbsp;closed&nbsp;loop,&nbsp;and&nbsp;why&nbsp;the&nbsp;&lsquo;detect&rsquo;&nbsp;step&nbsp;is&nbsp;the&nbsp;one&nbsp;everyone&nbsp;skips
&bull;&nbsp;Using&nbsp;the&nbsp;compare&nbsp;feature&nbsp;to&nbsp;measure&nbsp;whether&nbsp;an&nbsp;AI&nbsp;agent&nbsp;actually&nbsp;helped&nbsp;&mdash;&nbsp;or&nbsp;just&nbsp;moved&nbsp;the&nbsp;problem
&bull;&nbsp;AI&nbsp;Control&nbsp;Tower,&nbsp;explained&nbsp;simply&nbsp;&mdash;&nbsp;and&nbsp;how&nbsp;it&nbsp;becomes&nbsp;a&nbsp;third&nbsp;layer&nbsp;of&nbsp;process&nbsp;intelligence
&bull;&nbsp;Closed&nbsp;loop&nbsp;intelligence:&nbsp;the&nbsp;agent,&nbsp;the&nbsp;governance,&nbsp;and&nbsp;the&nbsp;agent&rsquo;s&nbsp;own&nbsp;behavior&nbsp;&mdash;&nbsp;all&nbsp;observable,&nbsp;all&nbsp;improving
&nbsp;
GET&nbsp;STARTED
If&nbsp;you&rsquo;re&nbsp;a&nbsp;ServiceNow&nbsp;customer,&nbsp;you&nbsp;already&nbsp;have&nbsp;access&nbsp;to&nbsp;free&nbsp;evaluation&nbsp;projects&nbsp;&mdash;&nbsp;no&nbsp;license&nbsp;needed.
https://www.servicenow.com/au/products/process-mining/get-started.html
https://www.servicenow.com/docs/r/now-intelligence/process-mining/process-mining.html
https://www.youtube.com/watch?v=TVrU0TQ7ldM
https://www.youtube.com/watch?v=GLKROYqnc10
&nbsp;
#ServiceNow&nbsp;#ProcessMining&nbsp;#ProcessIntelligence&nbsp;#AIAgents&nbsp;#AgenticAI&nbsp;#TaskMining&nbsp;#AIGovernance&nbsp;#AIControlTower&nbsp;#WorkflowAutomation&nbsp;#DigitalTransformation&nbsp;#ContinuousImprovement&nbsp;#ClosedLoopIntelligence&nbsp;#ServiceNowPodcast&nbsp;#EnterpriseAI&nbsp;#DontAutomateTheChaos

Episode 58: Predictive Intelligence Workbench

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