I create content about deep learning | The DevRel and Deep Learning Dude

I don’t wanna hop on call to learn about or see a demo of what you’re building. Too busy hacking on VLMs, curating multimodal datasets, and contributing to the open source community. 

Harpreet Sahota 🥑

It was great to be back in Boston last week and host another awesome meetup!

Thank you for everyone who showed up, our awesome lineup of speakers for taking time out of their schedules for delivering such informative talks: Anku Rani Hanhui Wang Sage Simhon Sharut G. 

And for Voxel51 for sponsoring!

If you missed the event, checkout the comments for where you can find the recordings of the talks

🤖 Hacker-in-Residence @ Voxel51| 👨🏽‍💻 AI/ML Engineer | 👷🏽‍♀️ Technical Developer Advocate | Learn. Do. Write. Teach. Repeat.

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i built a ComfyUI-inspired visual, node-based workflow editor for FiftyOne

now you can build dataset curation, analysis, and model evaluation pipelines by connecting nodes on a canvas, without writing code

give it a try and let me know what you think, completely open source and all you have to is `pip install fiftyone` and follow the instructions on the readme

everyone is hype about gtc, but the 3d vision conference is this week and i'm much hype for that

i made a repo and a dataset to explore the papers

checkout the repo here:
 https://lnkd.in/gRFz6Kb7

here's a dataset that you can use to explore the papers:
 https://lnkd.in/g2RA87fD

it's been a long, long while since i've done a live stream on linkedin, but it's happening in t-mius 8 minutes!

if you're interested in learning about how to work with video datasets using open source tools, open data, and open models...this is the session for you!

Join us on Feb 26 for Exploring Video Datasets with FiftyOne and Vision-Language Models. Register for the Zoom: https://lnkd.in/gCk7gGPi

Video is the hardest modality to work with — more data, more complexity, and annotation workflows that don’t scale. This hands-on session by Harpreet Sahota 🥑 shows how to understand what’s inside massive video datasets without manually watching thousands of clips.

You’ll learn how to:
🎬 Navigate and explore video datasets in the FiftyOne App and understand dataset structure
🔎 Compute embeddings with Qwen3-VL to enable semantic search, zero-shot classification, and clustering
📝 Generate video descriptions and localize events using vision-language models like Qwen3-VL and Molmo2
🧭 Visualize patterns and trends through embedding projections in FiftyOne
📏 Evaluate model outputs against Action100M’s hierarchical annotations

Perfect for ML engineers, data scientists, and computer vision teams working with large-scale video data who want practical workflows for exploration, curation, and debugging.

#computervision #machinelearning #ai #datascience #videoanalytics #visionlanguagemodels #mlops #opensource

Derek Van de Streek, Swati Bannore Jain and 11 other attendees

Feb 26 - Exploring Video Datasets with FiftyOne and Vision-Language Models

excited to be back in stuttart! if you're in the area and want to speak at the meetup on april 21st, send me a dm

Chief Community Officer @ Voxel51 | Startup Advisor

Are you based in the Stuttgart area? Consider speaking at the upcoming April 21 - Stuttgart AI, ML and Computer Vision Meetup: https://voxel51.com/speak

#computervision #ai #artificialintelligence #machinevision
#machinelearning #datascience #opensource #stuttgart

i've learned a lot from Eric Ma over the years, from the first time I saw one of his talks on principled data science workflows to talks he's given for my communities over the years, and his latest work on getting the most from coding agents.

check out his next talk, and support the SciPy community as well!

Together with my teammates, we solve biological problems with network science, deep learning and Bayesian methods.

As a data scientist, how much of your week is spent on work a coding agent could do?

I once planned multiple days of work for a machine learning experiment last year. This was an experiment that I had put off for an entire quarter because, as a team lead, I didn't have the time to block out the 3-4 afternoons that I thought I'd need. 

Instead, I described the problem to Claude Opus 4.5 via OpenCode, and it wrote the code, ran the training, found issues, switched strategies, and finished the whole thing in 20 minutes, complete with a written report drafted *with* figures referenced.

The data scientists who figure this out now will have an edge.

I'm teaching a workshop on how to do this flavour of agentic data science to raise funds for SciPy 2026's Financial Aid Program. You'll learn:

- Prescriptive prompting for experiments
- Project structure for agents
- Logging and verification strategies to enable automated control
- Report writing with AI
- Staying in control during EDA
- The minimalist version first

These are the same techniques I use in my personal projects and my teammates to compress data science timelines from days to minutes. I think you'll have a chance to learn something good while doing something good!

Details:

- Date: March 27 & April 3, 2026
- Time: 2:00-4:00 PM EST
- Venue: Google Meet (calendar invite will be provided)
- 40 spots available
- $1,000 minimum donation, paid directly to NumFOCUS (tax-deductible), student pricing: $200!

Video recordings available if you can't attend live.

Sign up here: https://lnkd.in/eFjc36Tb. I'm looking forward to seeing what you'll build with these techniques! 

P.S. If you can't make it but share it with others who have the means and would benefit from the workshop, I would deeply appreciate it!

Open article: Agentic Data Science Workshop | SciPy 2026 Fundraiser by agent-assisted-data-science.vercel.app

Agentic Data Science Workshop | SciPy 2026 Fundraiser

We just released a new AWS workshop that I’m really excited to finally share 👇
https://lnkd.in/eiNprTd7

This came from something I keep seeing across autonomy, robotics, and computer vision teams lately.

Most teams are not blocked by models anymore.
They are blocked by data and iteration speed.

So we wanted to show what a practical workflow actually looks like:
🚗 generate synthetic driving data
 🧠 auto label using foundation models
 🔧 fine tune a small vision language model
 ☁️ deploy and iterate using AWS SageMaker
 👀 inspect and improve everything inside FiftyOne

The goal was simple.

Build something real that teams could follow end to end.

Huge credit to Ryan Patrick Sweeney, Mark Vinciguerra, and Derick Thompson for driving this forward, along with great collaboration between Amazon Web Services (AWS), NVIDIA Omniverse, and Voxel51 🙌

Also excited that Voxel51 is now live on AWS Marketplace, which makes getting started a lot easier for teams working on computer vision and robotics workflows!

Personally, I think this is how a lot of Physical AI systems will get built going forward.

Faster loops between data, models, and deployment instead of long waiting cycles.

If you’re working on robotics, AV, or multimodal systems, I’d genuinely love to hear what you’re building.

More coming soon 🚀

#PhysicalAI #ComputerVision #Robotics #MultimodalAI #SyntheticData #AWS #MachineLearning #AutonomousSystems

Open article: GitHub - aws-samples/sample-finetuning-small-vlms-synthetic-data by github.com

Contribute to aws-samples/sample-finetuning-small-vlms-synthetic-data development by creating an account on GitHub.

GitHub - aws-samples/sample-finetuning-small-vlms-synthetic-data

I’m so happy to have my boi Wiz present at one of our meets!

AI @ NVIDIA - 🏗️ Build | 🚢 Ship | 🚀 Share

View Chris "The Wiz 🪄" Alexiuk’s profile

skills.md - you've seen it, you've probably used it (I assume if you're following this LinkedIn account, you're someone who uses tools like OpenCode/etc.

I'm excited to be yappin' about skills at an upcoming Voxel51 / Hugging Face virtual event with a line up that boggles the mind: 

Ben Burtenshaw, Daniel Ávila Arias, and AdonAI Vera.

My presentation will focus on something near and dear to my heart: Skills as documentation. 

The days of documentation aren't over - humans, and agents, still need to understand how things work - but they're changing quickly. Not everyone wants to read a thorough getting started guide that may be built for a specific system (and if it's not, it'll be ~2K words long) Sometimes, you just want to clone a repository - and get cooking. 

Skills help bridge that gap - context for LLMs, but tailored for a human experience. 

Can't wait for the event, come on out and ask any skill questions you have!

looking forward to hosting this workshop tomorrow, join me!

Join Harpreet Sahota 🥑 on Feb 26 for a virtual workshop to learn how to use Facebook's Action100M dataset and FiftyOne to build an end-to-end workflow - https://lnkd.in/gFvwbQni

What you'll learn:

* Navigate and explore video data in the FiftyOne App, filter samples, and understand dataset structure

* Compute embeddings with Qwen3-VL to enable semantic search, zero-shot classification, and clustering

* Generate descriptions and localize events using vision-language models like Qwen3-VL and Molmo2

* Visualize patterns in your data through embedding projections and the FiftyOne App

* Evaluate model outputs against Action100M's hierarchical annotations to validate what the models actually capture

By the end of the session, you'll have a reusable toolkit for understanding any video dataset at scale, whether you're curating training data, debugging model performance, or exploring a new domain.

***********

Want to build better computer vision models? FiftyOne is an open source toolkit from Voxel51 (our Meetup sponsor) that helps you curate datasets, evaluate model performance, visualize embeddings, catch annotation errors, and eliminate duplicate images—all in one place.

“pip install fiftyone” is all it takes to get started - https://docs.voxel51.com/

#computervision #ai #artificialintelligence #machinevision #machinelearning #datascience #opensource

Andreas Welsch

Andreas Welsch is an internationally recognized top 10 Agentic AI leader and one of today’s most sought-after thought leaders and keynote speakers for business and technology audiences. With over two decades of global leadership experience, previously as Vice President at SAP, Andreas has helped Fortune 500 companies cut through AI hype to deliver measurable business outcomes.

He is the Founder and Chief Human Agentic AI Officer of AI consulting firm Intelligence Briefing, the best-selling author of the AI Leadership Handbook and The HUMAN Agentic AI Edge, and a leading voice on AI strategy, adoption, and transformation. 

At the heart of Andreas’s work lies a clear value proposition: he helps business leaders understand how to apply AI responsibly, effectively, and profitably by addressing the questions that decision-makers face:

• How do we turn AI into business value, not just experimentation?
• How can we prepare our workforce for AI-driven transformation?
• How can we empower our teams to use AI without creating AI workslop?
• What practical steps can we take to avoid ethical, operational, or financial pitfalls?

Andreas’s keynotes and workshops are known for their clarity, strategic relevance, and deep insight. Drawing from more than two decades in the software industry, he offers real-world frameworks and practical steps tailored to leadership audiences. He introduces leaders to AI agents, leading hybrid teams of humans and AI, and AI-driven business models, explaining not only what’s next, but what matters most and why.

During his tenure at SAP, Andreas accelerated the integration of AI across enterprise applications and positioned SAP as an AI leader. He brings first-hand experience and a global perspective to every business and has been named a LinkedIn Top Voice, Thinkers360's Top 10 Thought Leader in AI, Generative AI, and Agentic AI, The Futurum Group's Top 14 AI Influencer, PEX Network’s Top 30 AI Leader, and SwissCognitive’s Top 50 Global AI Ambassador.

His work has appeared in CIO.com, VentureBeat, InformationWeek, and the American Management Association. He serves on the Editorial Board of the Journal of AI, Robotics and Workplace Automation and as an adjunct professor at West Chester University of Pennsylvania.

For leaders looking for clarity, action, and strategy, Andreas delivers a transformative experience beyond the hype. Follow his “What’s the BUZZ?” podcast and newsletter, “The AI MEMO”, and work with Andreas to turn hype into outcome for your business.

Vice President & Head of Marketing & Solution Management — Artificial Intelligence

Defined GTM and product marketing for Artificial Intelligence (AI) across SAP’s product portfolio, incl. AI Business Services on SAP Business Technology Platform in the context of embedded AI capabilities and intelligent process automation via Robotic Process Automation (RPA) and low-code/ no-code offering. Led global team of product marketers and solution managers

“Is your hand getting tired?” attendees asked.
“You should have a stamp,” others joked. 
But that would circumvent the HUMAN aspect and authenticity. 

For two hours straight, attendees waited in line to receive their signed copy of The HUMAN Agentic AI Edge on launch day yesterday.

I signed each one of the 300 books with:
Stay HUMAN. 
Get AI-Ready.

Sounds great, doesn’t it? But it was the little chats here and there, the feedback on my closing keynote, and talking about the good old days with former colleagues, that added the HUMAN touch.


If you haven’t gotten your copy yet, you can get it on Amazon for a 90% launch discount!


A special shout-out to Paul Kurchina, the mastermind behind the annual “Next Generation SAP Enterprise Architect Community Learning Forum,” master connector, and extraordinary supporter!

#ArtificialIntelligence #AgenticAI #IntelligenceBriefing

I signed 300 books at the big launch this week, but this interaction made an impression on me:

Jade was running the bar and serving customers. When the book line was short, she came over, and I signed a copy for her. She asked about my self-publishing process and mentioned that she has published three books on Amazon. As I was breaking down the banners and stowed them away at the end of the event, Jade came over again. 

“Can I say something?” she asked. 

I was curious, but wasn’t quite sure what was on her mind. 

“Successful people need to hear this, too: I am proud of you!”

I didn’t expect to hear these words.

A dozen thoughts rushed through my head: 
How nice of her to come over to say that. Successful? Proud of ME?

All I could think to say was: “Thank you so much.”

But I’ve been thinking about that interaction and her words for the rest of the week.


Let’s all be a little more like Jade, and be a little more HUMAN. 


PS: Read or listen to the best-selling The HUMAN Agentic AI Edge on Amazon or Spotify.

#ArtificialIntelligence #AgenticAI #IntelligenceBriefing

📘 NOW AVAILABLE: The HUMAN Agentic AI Edge! 
When AI becomes the next “easy button,” leaders need to set expectations with their teams early. 

Otherwise, low-quality, sloppy results creep in, and performance, skills, and reputation degrade.

Between the triad of standards, guardrails, and readiness lies the real work that leaders need to do now, beyond “giving everyone Copilot etc.”

Let’s face it: team members are not off the hook doing their best work. They never were.

Like a senior manager recently shared with me: “Now, I’m getting all these meeting summaries and action items from my team members. I don’t have time to go through all of them.”

Creating is easy. Filtering and prioritizing are the new bottleneck for most leaders.

In the book, you will find the frameworks, anecdotes, and examples that help you empower and encourage your team to use AI responsibly while remaining accountable and high-performing.


Today is the official book launch together with 500 IT leaders at the Next Generation SAP Enterprise Architect Community Learning Forum—keynote and book signing included.


In case you are not on-site, you can get your copy on Amazon for the special launch offer!


Stay HUMAN. Become AI-ready.

And celebrate the big launch with me!

#ArtificialIntelligence #AgenticAI #Leadership

How do you measure the success of a launch?
Whatever your answer, launch day is intense. 
Whatever your product or service, you prep and prep, and prep…and hope for the best. 

Once the launch is on, market reception and feedback are largely out of your hands.

What applies to software and category launches applies to book launches, too. 

On Wednesday, I was checking the category rankings to see how The HUMAN Agentic AI Edge was moving up in the three categories I selected for the launch. 

But it wasn’t. 

It sat at rank #76 all morning and afternoon.
I was getting nervous. Had I missed to activate even more parts of my network? Was everyone just too busy during the day (or had forgotten about buying the book)?

Was the number of sales not enough to make even a slight dent?

Then, one of my friends texted me. 
“Your book is #3 in the charts!”

I was relieved. At least a little. Viewing the category instead of the book showed the correct ranking. But the question of how many more sales I’d need to make it to #1 was nagging. You just don’t know. 

At dinner, we celebrated the launch together with the other speakers of the Next Generation SAP Enterprise Architect Community Learning Forum. 

By then, the book had moved to #2. Soooo close. So close. 

4 minutes past midnight, it hit the top spot in the “Hot Releases” list on Amazon in Germany—just not in a category. 

I decided to go to sleep and check whenever I’d wake up. #2 wasn’t so bad for launch day. But would other books overtake it tomorrow?

I briefly woke up just before 4am and grabbed my phone. Had anything changed in the past 4 hours??

Yes, it had! #1 in Management Skills…a best-seller!! Satisfaction. Screenshot. Sleep. In that order.

Since then, it has hit #1 in all three categories!
A super successful launch. 


But it’s one of these things that you can’t do alone. Thank you so much for your support and readership! I’m deeply grateful!


(Don’t miss to get the launch promo of $0.99 for the ebook for the next 24 hours: https://lnkd.in/dcKY6biC)


Next up: Keynotes, workshops, and podcasts!

#ArtificialIntelligence #AgenticAI #Leadership

During the launch of The HUMAN Agentic AI Edge, 300 attendees waited in line to get their signed copy. Here’s how quickly 3 hours went by…

In each book, I wrote:

Stay HUMAN. 
Get AI-Ready.

Because in order to become an AI-first business, your team needs to get AI-ready…first.


Since then, many attendees have reached out, and I even met a few IRL this week!

Thank you for the awesome feedback and reviews. If you’ve received or bought a copy, please consider leaving your feedback on Amazon. 

Empowering and encouraging team members to use AI without creating slop is the task of the hour. 

I’m curious: How much AI slop do you receive per day? And what would it take to stop it?

#ArtificialIntelligence #AgenticAI #IntelligenceBriefing

Earlier this week, we had a special pre-launch book signing for members of the Chief Architect Network (CAN) that Grant Ecker leads.

Grant and the CAN community connect Chief Architects and senior IT executives to discuss and learn about new topics (such as Agentic AI) and how IT organizations can both prepare themselves and implement these technologies. Since 2021, the community has grown to over 620 members globally.

I’ve been following Grant on LinkedIn for a few years now. So, I was super excited when we first hosted our first event together in December, and when we finally got to meet in person this week.

When AI-generated news and the AI hype make it harder to discern what's real and what's actually working, being part of a community of trusted, human leaders and experts is the way to go.

So here’s a special Friday shout-out Grant and the network!
Give him a follow and maybe we'll see each other at a future event, too.


Love the red tumbler, btw. It goes so well with The HUMAN Agentic AI Edge and the launch-week promo of a symbolic Dollar (or Euro) over on Amazon.


Happy Friday, everyone!


#ArtificialIntelligence #Leadership #Community

“I hadn’t thought about agents as digital employees, yet,” shared a leader with me after attending yesterday workshop, “but it makes sense!”

Let’s get this out of the way for context:
- Approaching agents as digital employees is a helpful metaphor as you define guidelines, guardrails, add processes, but…
- They are still “just software” when it comes to the accountability for their decisions incl legal or ethical aspects (accountability stays with you)

I call it the “Dual-Lens Principle.”

Another attendee rightfully asked who creates the majority of agents in a business today?—IT. 

HR is not at the table. Yet, it’s a major workforce shift and HR can contribute wit that experience. Job descriptions, codes of conduct, rewards, org charts included. IT and HR need to collaborate.

That’s a central point in The HUMAN Agentic AI Edge which participants learned about. Tomorrow is the official book launch, which means you can learn about it, too!


How do you view AI agents?—As digital employees or just another piece of software?


#ArtificialIntelligence #AgenticAI #IntelligenceBriefing

The HUMAN Agentic AI Edge was just covered on Forbes!! Coverage includes the 6 dimensions of the Operating Model you will find in the book.  

When work is no longer a matter of effort, purpose moves into focus.

When AI generates outcomes on par with human results, quality and delivery speed become the differentiating factors.

Ultimately, the question is how you define your value at work when AI can eventually do more tasks that humans do.

The key lies in elevating what makes us unique.
And that’s a core role any leader needs to play. 

How do you define your value at work?


Thank you, Joe McKendrick, for covering a key message of the book in this article!

Don’t miss to get your copy of the best-selling ebook, paperback, or audiobook wherever you get your books!

#ArtificialIntelligence #AgenticAi #IntelligenceBriefing

You've heard me say it time and again:
Your AI agents need high-quality data to deliver high-quality results.

But what does Agentic-Ready Data look like?
And where does that high-quality data even come from when data is rarely current, correct, enriched, or governed.

I can't wait to learn about it from the Precisely team at the Gartner Data & Analytics Summit in Orlando next week at booth # 727. Learn more here: https://lnkd.in/dXhPcGiS

If you're on site, don't forget to join this session:

How a Global Gaming Leader Is Closing the Agentic AI Data Integrity Gap
Monday, March 09, 2026 / 03:30 PM - 04:00 PM EDT (Osceola D)
Paul Bell, Global Head Of Data Trust & Integrity, Entain
Cam Ogden, SVP of Product Management, Precisely

One thing is clear, the highest quality data that is integrated, governed, and enriched is needed for successful AI, automation, and analytics initiatives across the enterprise.

It better be. It has to be.


See you in Orlando!


#ArtificialIntelligence #AgenticAI #Sponsored

If you haven’t gotten your copy, yet, there’s still time to snag the launch price of $0.99 on Amazon today! The HUMAN Agentic AI Edge

graphical user interface, text, application

“What’s new, and what’s real with Agentic AI?” is the big question I’m getting answers to next week in Orlando.

I’ll cover the latest news on site, interview top executives, and talk to customers to get information straight from the source.

One thing is clear:
Large organizations are innovating with Agentic AI. They just don’t talk about it publicly (out of fear to get bad press or backlash). But we need more transparency (not less!), so everyone can avoid the costly mistakes. 

Join me in Orlando for the Gartner Data & Analytics Summit! Leave a comment if you’re going, too.


Still need to register? Use code ‘JOINMEINORLANDO’ to save $450 off registration: https://lnkd.in/duUD-re3
 

PS: Looking forward to catching up with Kate Strachnyi, SCOTT TAYLOR, George Firican, and Ravit Jain.

#GartnerDA #DataCommunity #DataSummit #ArtificialIntelligence #AgenticAI

Agentic AI value does not come from models alone. Instead, quality, trust, and governance of the data behind it are more critical than ever.

To learn more, I spoke with Felix Van de Maele, CEO of Collibra, to discuss why turning AI ambition into real business value starts with one thing: Data Confidence.

Here’s what stood out:

1. AI success is mostly a data challenge
Felix makes the case that enterprise AI is largely driven by the data organizations feed into their models, agents, and use cases. When companies have confidence in their data, they can move faster, generate higher-quality outputs, and drive stronger adoption across the business.

2. Unstructured data is the next big frontier
Most enterprise data is still unstructured, and that creates a major challenge for AI teams. Felix explains why discovering the right documents, identifying sensitive information, and evaluating data quality are essential if organizations want to get better ROI from AI initiatives.

3. More context does not always mean better results
Simply loading every available document into an AI system is not a winning strategy. Better outcomes come from intentional governance of the data and context that agents rely on.

4. Agentic AI raises the stakes for governance
As AI agents begin to take more autonomous actions, accountability becomes even more important. Felix breaks down why organizations need to govern inputs, monitor outputs, and establish the right controls to move AI from experimentation into production responsibly.

If you're tasked with scaling AI in your enterprise, this conversation is a strong reminder that trusted data is the foundation for trusted AI outcomes.


#ArtificialIntelligence #AgenticAI #DataGovernance

Anthropic calls it: Theoretical capability.
You might also call it: Market potential. 

Keep in mind that these are the key industries and occupations that Anthropic is selling to!

So, it’s not surprising for a vendor to picture their product as covering close to 100%(!) of tasks in management, finance, programming, legal, life sciences, and office admin.

The bigger questions are about how to turn theoretical into actual capability:
1) Why is there so much untapped potential?
2) How can organizations close that gap?

Yet, the cause is all around you in your business:
Leaders are asking “We’ve given everyone access to Copilot, Claude & Co., now what?”

Tools have theoretical capabilities.
Humans need actual capabilities. 


Since the summer, I’ve been running cohorts of my “Certified AI Leader” upskilling program.

The four levels of the learning journey cover the basics of using AI assistants, applying advanced prompting techniques, building your first AI agents, and leading your teams through AI-driven change: https://lnkd.in/dq4ayVWX


Prepare your teams expand their actual capabilities. DM me for the details. 


PS: In the meantime, learn how to shape the next generation of AI-ready teams with my new book, The HUMAN Agentic AI Edge.

#ArtificialIntelligence #Upskilling #IntelligenceBriefing

AI agents are only as good as the data behind them.

That’s why I talked to Cam Ogden, SVP of Product Management at Precisely, to learn more about the challenge many organizations are underestimating: whether their data is actually Agentic-Ready Data.

As more companies move from AI experimentation to enterprise agents making decisions on their behalf, the bar for data trust rises dramatically. Cam shares why “AI-ready” and “agentic-ready” are not the same thing, and what leaders need to do now to close that gap.
Here’s what you’ll learn:

1. Why data trust matters more in the age of AI agents
When dashboards fail, teams lose confidence. When agents act on flawed data, the business takes on real operational risk. Agentic AI requires a much higher standard of trust, completeness, and confidence in enterprise data.

2. Where the AI readiness disconnect really comes from
According to the 2026 State of Data Integrity and AI Readiness report (https://lnkd.in/dMm72RbM), co-developed with the Drexel LeBow Center for Applied AI and Business Analytics, many leaders say their organizations are AI ready because they have roadmaps, cloud investments, and executive support in place. But at the operational level, the picture often looks very different, creating a gap between strategy and execution. That’s also why so many organizations are still struggling with data quality, context, and integration.

3. The hidden measurement problem in AI adoption
A major issue is not just whether companies are investing in AI, but whether they are measuring success in a meaningful way. Too few organizations have clear metrics tied to AI outcomes, which makes it harder to prove impact and scale what works.

4. How to close the agentic AI data integrity gap
Leaders need to address six core challenges, spanning siloed data, missing context, stale data, incomplete records, weak governance, and rising cost from untangling these issues. Start with one use case, strengthen the data foundation, prove value, and then scale across the business.

If you’re exploring AI agents in the enterprise, this conversation will help you understand why trusted, well-governed data is becoming a competitive requirement.

Watch and listen how leaders can build the Agentic-Ready Data foundation needed for real AI scale.

#ArtificialIntelligence #DataStrategy #AgenticAI #AgenticReadyData #Precisely

Everyone wants AI agents. But most organizations are still skipping an important step: 

Matching the type of Agentic AI they want to the level of readiness they actually have.

A practical way to think about Agentic AI is in 3 categories:

1. Personal productivity: AI helps an individual draft, summarize, research, or analyze. Accountability is still clear.

2. Operational efficiency: Teams hand recurring work to agents, such as reporting, data checks, or coordination. Review processes start to matter much more.

3. Strategic differentiation: Agents support core processes like procurement, customer support, or financial analysis. This is where scale rises fast, but so does risk.


The mistake many companies make is treating all three the same. It’s a core aspect in my new best-selling book, The HUMAN Agentic AI Edge.

As agent autonomy increases, so must clarity around ownership, permissions, quality standards, and review.

That is why leaders need to look at agents through two lenses at the same time:
- as digital employees that need guardrails
- as just another piece of software that must be governed

Most importantly, human are still responsible. AI can accelerate work, but it does not remove judgment. If standards do not keep pace with adoption, “productivity gains” quickly turn into review overhead, rework, and hidden clean-up.

The better approach:
- Start where accountability is clear.
- Design deliberately as complexity increases.
- Keep human judgment ahead of AI capability.

Wanting AI agents is easy. Using them well is the real work. Read the full guest article on Technical-ly

#ArtificialIntelligence #AgenticAI #IntelligenceBriefing

For the weekend ahead, get some reading or listening in and learn with The HUMAN Agentic AI Edge audiobook how to empower your team to become AI-ready.

You’ll learn about:
- Why professionals need to do a Labor-Shift Check before passing on AI-generated results
- Whether (or when) to view AI agents as digital employees
- How to encourage your team to balance AI-driven efficiency with human judgment 

Why it matters:
At the end of the day, your stakeholders are indifferent about whether your team or its AI created the results. But you’ll hear about it when quality degrades.

Get started today and shape the next generation of AI-ready teams!


#ArtificialIntelligence #Leadership #IntelligenceBriefing

Your biggest AI advantage is a repeatable way for people to use it.

Start a tiered champion program: basic membership and sandbox access, short role-based courses, hands-on prototyping, and named local contacts who connect teams to deployment support. 

Curate short learning paths, keep playgrounds safe, and push pilots that show clear deployment paths so adoption comes from informed users, not guesses.  

Stop confusing speed with scale. Quick experiments teach a lot, but without structure they create waste. Require a simple pilot template (goal, expected benefit, data needs, security checklist, deployment path), run short cycles, and measure outcomes you can act on. Keep governance light but consistent so teams don’t reinvent the same work.  


This is just an excerpt of my weekly newsletter—subscribe to read the latest issue via the link under my name.

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Performance ScoreAndreas Welsch's LinkedIn Performance

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Harpreet Sahota 🥑

Andreas Welsch

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Harpreet Sahota 🥑's LinkedIn Performance

Performance ScoreAndreas Welsch's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreHarpreet Sahota 🥑's LinkedIn Performance