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

Shail Khiyara

I bring over two decades of leadership across enterprise software, SaaS, and industrial transformation. 

My journey started in civil and structural engineering, leading global infrastructure projects across Energy, Water, and Industrial sectors. Since then, I’ve led enterprise SaaS companies—both public and private—as CEO and board advisor, focused on driving systemic transformation through AI and automation.

Today, I serve as CEO of Swarm Engineering, where we build agentic AI systems that enable enterprises to automate complex decisions and unlock new levels of efficiency and resilience. AI isn’t a bolt-on. It’s the logic layer shaping how organizations operate in real time.

This isn’t gradual progress—it’s a leap. Technologies like federated learning and constraint-based reasoning are enabling smarter, decentralized decision systems across the supply chain and beyond.

My second book, Agentic Artificial Intelligence, became an Amazon #1 Best Seller at launch, exploring how AI is shifting from passive tools to autonomous collaborators.  It builds on my first book, Intelligent Automation, which remains widely used in both industry and academia.

At my core, I think like a strategic operator—fusing systems thinking with executional clarity. Whether I’m writing, building, or advising, my focus is simple: compress complexity, elevate outcomes, and challenge conventional limits.

I founded VOCAL, a global initiative of 90+ brands collaborating on the future of intelligent automation and AI—because in a world saturated with technology, the real advantage comes from how we think about it.

Founder, Chief Executive Officer

AI for the Industrial World

Plutoshift AI is on a mission to bring data intelligence and AI to the world’s physical infrastructure. Think electronic medical record for industrial systems. Plutoshift AI helps global leaders realize the power of their operational data to increase efficiency, reduce costs, and build more resilient and sustainable businesses.

𝗜𝗳 𝗬𝗼𝘂 𝗖𝗮𝗻’𝘁 𝗡𝗮𝗺𝗲 𝘁𝗵𝗲 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻, 𝗔𝗜 𝗪𝗼𝗻’𝘁 𝗦𝗮𝘃𝗲 𝗬𝗼𝘂

I’ve been in too many rooms where teams debate models, forecasts, and architectures without ever agreeing on what decision they’re actually trying to improve.

We talk a lot about 𝗯𝗲𝘁𝘁𝗲𝗿 𝗔𝗜.
We spend far less time on 𝗯𝗲𝘁𝘁𝗲𝗿 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀.

That gap is where most AI initiatives quietly stall.

𝗔 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗶𝘀 𝗻𝗼𝘁 𝗮 𝗺𝗼𝗱𝗲𝗹 𝗼𝗿 𝗮 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻. It’s something you 𝘤𝘰𝘯𝘵𝘳𝘰𝘭, made under 𝘶𝘯𝘤𝘦𝘳𝘵𝘢𝘪𝘯𝘵𝘺, in service of a 𝘮𝘦𝘵𝘳𝘪𝘤 𝘵𝘩𝘢𝘵 𝘢𝘤𝘵𝘶𝘢𝘭𝘭𝘺 𝘮𝘢𝘵𝘵𝘦𝘳𝘴.

If that isn’t clear, sophistication won’t save you.

The real work happens before code is written:

• What are we optimizing first?
• What tradeoffs are acceptable?
• Which uncertainties actually move outcomes?

This part feels slow. It produces no dashboards. So it gets rushed.

And later, people say, “𝘵𝘩𝘦 𝘮𝘰𝘥𝘦𝘭 𝘥𝘪𝘥𝘯’𝘵 𝘸𝘰𝘳𝘬.”

In real operations, I’ve seen simple approaches outperform elegant ones:

• 𝗖𝗹𝗲𝗮𝗿 𝗿𝘂𝗹𝗲𝘀 𝘄𝗶𝘁𝗵 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 𝗯𝗲𝗮𝘁 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻
• 𝗗𝗲𝘁𝗲𝗿𝗺𝗶𝗻𝗶𝘀𝘁𝗶𝗰 𝗽𝗹𝗮𝗻𝘀 𝘀𝘂𝗿𝘃𝗶𝘃𝗲 𝘂𝗻𝗰𝗲𝗿𝘁𝗮𝗶𝗻𝘁𝘆 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗯𝘂𝗳𝗳𝗲𝗿𝘀 𝗮𝗻𝗱 𝗷𝘂𝗱𝗴𝗺𝗲𝗻𝘁
• 𝗛𝘂𝗺𝗮𝗻𝘀 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝗰𝗼𝗺𝗽𝗲𝗻𝘀𝗮𝘁𝗲 𝗳𝗼𝗿 𝘃𝗼𝗹𝗮𝘁𝗶𝗹𝗶𝘁𝘆, 𝗲𝘃𝗲𝗻 𝘄𝗵𝗲𝗻 𝘁𝗼𝗼𝗹𝘀 𝗽𝗿𝗲𝘁𝗲𝗻𝗱 𝗶𝘁 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗲𝘅𝗶𝘀𝘁
  
The question isn’t “𝘐𝘴 𝘵𝘩𝘪𝘴 𝘰𝘱𝘵𝘪𝘮𝘢𝘭?”
It’s “𝗗𝗼𝗲𝘀 𝘁𝗵𝗶𝘀 𝗵𝗼𝗹𝗱 𝘂𝗽 𝘄𝗵𝗲𝗻 𝗿𝗲𝗮𝗹𝗶𝘁𝘆 𝘀𝗵𝗼𝘄𝘀 𝘂𝗽?”

The same applies to data.

𝗕𝗲𝘁𝘁𝗲𝗿 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗼𝗻𝗹𝘆 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗶𝗳 𝗶𝘁 𝗰𝗵𝗮𝗻𝗴𝗲𝘀 𝘁𝗵𝗲 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗮𝘁 𝘁𝗵𝗲 𝗺𝗼𝗺𝗲𝗻𝘁 𝗶𝘁’𝘀 𝗺𝗮𝗱𝗲. If it doesn’t alter action, it’s just noise with better branding.

And here’s the uncomfortable truth about AI:

𝗠𝗼𝗱𝗲𝗹𝘀 𝗱𝗼𝗻’𝘁 𝗰𝗵𝗼𝗼𝘀𝗲 𝗴𝗼𝗮𝗹𝘀. 𝗣𝗲𝗼𝗽𝗹𝗲 𝗱𝗼.

AI optimizes what we tell it to optimize. It doesn’t decide what 𝘴𝘩𝘰𝘶𝘭𝘥 matter, how to balance tradeoffs, or what “good” really means.

𝗧𝗵𝗮𝘁’𝘀 𝗹𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽. 𝗡𝗼𝘁 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻.

The next wave of advantage won’t come from smarter algorithms alone. It will come from teams who frame decisions clearly, respect uncertainty, and design AI to support human judgment.

Before your next AI initiative, pause and ask:

➤  𝗖𝗮𝗻 𝘄𝗲 𝗰𝗹𝗲𝗮𝗿𝗹𝘆 𝗻𝗮𝗺𝗲 𝘁𝗵𝗲 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻?
➤  𝗗𝗼 𝘄𝗲 𝗮𝗴𝗿𝗲𝗲 𝗼𝗻 𝘄𝗵𝗮𝘁 “𝗯𝗲𝘁𝘁𝗲𝗿” 𝗺𝗲𝗮𝗻𝘀?
➤  𝗪𝗶𝗹𝗹 𝘁𝗵𝗶𝘀 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗰𝗵𝗮𝗻𝗴𝗲 𝘄𝗵𝗮𝘁 𝘀𝗼𝗺𝗲𝗼𝗻𝗲 𝗱𝗼𝗲𝘀 𝗮𝘁 𝘁𝗵𝗲 𝗺𝗼𝗺𝗲𝗻𝘁 𝗼𝗳 𝗰𝗵𝗼𝗶𝗰𝗲?

If the answer is no, AI won’t save you.

𝗕𝗲𝘁𝘁𝗲𝗿 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 𝗰𝗼𝗺𝗲 𝗳𝗶𝗿𝘀𝘁.
Everything else is downstream. 

SWARM

Founder & CEO | Author | Board Member Building bridges between AI, operations, and real-world decisions

I’ve noticed something interesting in the conversations I’ve had this week.

Whether it’s AI, operations, or supply chains, the hardest part is almost never the technology.

It’s the moment before the decision. Here’s what that looks like in practice.

A team builds a forecasting model.
Accuracy improves. Dashboards look great.

But when demand shifts, no one acts. Why?
Because no one ever answered the real question:

Are we deciding how much to produce, where to allocate inventory, or how much risk we’re willing to accept?

So when results disappoint, the conclusion is easy: “The model didn’t work.”

What actually failed was clarity about the decision. Once the decision is explicit, the rest gets easier. When it isn’t, no amount of sophistication saves you.

That pause is where leadership actually lives.

#Leadership #DecisionMaking #EnterpriseAI #DecisionIntelligence

𝗔𝘀 𝘁𝗵𝗲 𝘆𝗲𝗮𝗿 𝘁𝘂𝗿𝗻𝘀, 𝗶𝘁’𝘀 𝘄𝗼𝗿𝘁𝗵 𝗿𝗲𝗺𝗲𝗺𝗯𝗲𝗿𝗶𝗻𝗴 𝗵𝗼𝘄 𝗿𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝘁 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘀𝘂𝗿𝘃𝗶𝘃𝗲.

Most people think the Amazon survives because it’s lush.
It doesn’t.

𝗧𝗵𝗲 𝗔𝗺𝗮𝘇𝗼𝗻 𝘀𝘂𝗿𝘃𝗶𝘃𝗲𝘀 𝗯𝗲𝗰𝗮𝘂𝘀𝗲 𝗮 𝗱𝗲𝘀𝗲𝗿𝘁 𝗼𝗻 𝗮𝗻𝗼𝘁𝗵𝗲𝗿 𝗰𝗼𝗻𝘁𝗶𝗻𝗲𝗻𝘁 𝗳𝗲𝗲𝗱𝘀 𝗶𝘁.

Each year, wind carries phosphorus-rich dust from the Sahara across the Atlantic.

Roughly 20 to 30 million tons make it all the way across. 𝗧𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗲𝗾𝘂𝗶𝘃𝗮𝗹𝗲𝗻𝘁 𝗼𝗳 𝗮𝗯𝗼𝘂𝘁 𝗼𝗻𝗲 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝘁𝗿𝘂𝗰𝗸𝗹𝗼𝗮𝗱𝘀 𝗼𝗳 𝗻𝘂𝘁𝗿𝗶𝗲𝗻𝘁𝘀, 𝗲𝗻𝗼𝘂𝗴𝗵 𝘁𝗼 𝘄𝗿𝗮𝗽 𝗮𝗿𝗼𝘂𝗻𝗱 𝘁𝗵𝗲 𝗘𝗮𝗿𝘁𝗵 𝗮𝘁 𝘁𝗵𝗲 𝗲𝗾𝘂𝗮𝘁𝗼𝗿 𝗶𝗳 𝗹𝗶𝗻𝗲𝗱 𝘂𝗽 𝗲𝗻𝗱 𝘁𝗼 𝗲𝗻𝗱.

That dust replaces nutrients the rainforest loses to rain and flooding.

𝗡𝗼 𝗱𝘂𝘀𝘁. 𝗡𝗼 𝗿𝗲𝗽𝗹𝗲𝗻𝗶𝘀𝗵𝗺𝗲𝗻𝘁. 𝗡𝗼 𝗿𝗮𝗶𝗻𝗳𝗼𝗿𝗲𝘀𝘁.

We design systems as if value is created locally. 𝗜𝗻 𝗿𝗲𝗮𝗹𝗶𝘁𝘆, 𝗿𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝗰𝗲 𝗰𝗼𝗺𝗲𝘀 𝗳𝗿𝗼𝗺 𝗲𝘅𝘁𝗲𝗿𝗻𝗮𝗹 𝗶𝗻𝗽𝘂𝘁𝘀 𝘁𝗵𝗮𝘁 𝗿𝗲𝗽𝗹𝗮𝗰𝗲 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲 𝘀𝘆𝘀𝘁𝗲𝗺 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀𝗹𝘆 𝗹𝗼𝘀𝗲𝘀.

By external inputs, I mean the nutrients, capacity, information, and talent that normal operation constantly drains.

That’s true in agriculture, in supply chains, and inside organizations.

The 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗿𝗶𝘀𝗸𝘀 aren’t inside your operation.
𝗧𝗵𝗲𝘆’𝗿𝗲 𝘁𝗵𝗲 𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝗰𝗶𝗲𝘀 𝘆𝗼𝘂 𝗱𝗼𝗻’𝘁 𝗺𝗼𝗱𝗲𝗹, 𝗱𝗼𝗻’𝘁 𝗺𝗲𝗮𝘀𝘂𝗿𝗲, 𝗮𝗻𝗱 𝗱𝗼𝗻’𝘁 𝗱𝗲𝗳𝗲𝗻𝗱.

Nature figured this out first.

𝗪𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 “𝗦𝗮𝗵𝗮𝗿𝗮 𝗱𝘂𝘀𝘁” 𝗶𝗻 𝘆𝗼𝘂𝗿 𝘀𝘆𝘀𝘁𝗲𝗺 𝘁𝗵𝗮𝘁 𝘆𝗼𝘂’𝗿𝗲 𝘁𝗮𝗸𝗶𝗻𝗴 𝗳𝗼𝗿 𝗴𝗿𝗮𝗻𝘁𝗲𝗱?

#SystemsThinking #Resilience #Agrifood #SupplyChain #DecisionMaking

Most conversations about #AI in food systems still start with dashboards and pilots.

The real question is different:
𝗖𝗮𝗻 𝘄𝗲 𝗺𝗼𝘃𝗲 𝗳𝗿𝗼𝗺 𝗶𝗻𝘀𝗶𝗴𝗵𝘁 𝘁𝗼 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗮𝘁 𝘁𝗵𝗲 𝘀𝗽𝗲𝗲𝗱 𝘃𝗼𝗹𝗮𝘁𝗶𝗹𝗶𝘁𝘆 𝗻𝗼𝘄 𝗱𝗲𝗺𝗮𝗻𝗱𝘀?

I’m looking forward to speaking at the Gulfood World Economy Summit in #Dubai to talk about how AI & automation becomes a strategic capability not a tech upgrade.

When supply chains are fragile, labor is constrained, and margins are tight, execution is the strategy.

https://lnkd.in/gHuvUM3Z

Gulfood - The World's Biggest F&B Event 
SWARM

View company: Gulfood - The World's Biggest F&B Event

Digital transformation and the implementation of intelligent automation are redefining the operational standards of the global food system.

Shail Khiyara , CEO at Swarm joins the Gulfood World Economy Summit to discuss how breakthrough technologies and AI powered automations serve as strategic value creators. As the CEO of Swarm he will examine the role of AI in reshaping agriculture and manufacturing while addressing the need for global upskilling. We look forward to his insights on leveraging digital tools to overcome supply chain disruptions and enhance long term competitiveness.

📅 26 - 29 January 2026
📍 Dubai Exhibition Centre, Expo City

Register now : https://lnkd.in/dfkhjBvj

#Gulfood #Gulfood2026

𝗕𝗿𝗮𝘇𝗶𝗹 𝗷𝘂𝘀𝘁 𝗯𝗲𝗰𝗮𝗺𝗲 𝘁𝗵𝗲 𝘄𝗼𝗿𝗹𝗱’𝘀 𝗹𝗮𝗿𝗴𝗲𝘀𝘁 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗹𝗮𝗯.

Most headlines about Brazil’s agribusiness in 2026 focus on scale.

Record harvests. Export dominance. Global relevance.

But the AgTechNavigator piece quietly reveals something more important: #Brazil is now operating inside one of the most volatile, constrained, and financially fragile ag systems on earth. <link in the comments>

➤ High interest rates.
➤ Farmer bankruptcies.
➤ Trade quotas from China.
➤ EU sustainability rules.
➤ Currency swings.
➤ Political uncertainty heading into a national election.

This is not a growth story. This is a 𝗰𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 story.

That complexity is already showing up in hard flows, not theories.
Analysts expect Brazil’s soybean export boom to resume sharply in Q2 2026, resetting global grain movements and amplifying price, logistics, and timing volatility across the entire system.

When capital costs are 15%, you do not survive by being “right eventually.” You survive by being able to change direction before the damage compounds.

In a system like this, 𝗳𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝘀 𝗱𝗲𝗰𝗮𝘆 𝗳𝗮𝘀𝘁𝗲𝗿 𝘁𝗵𝗮𝗻 𝗺𝗶𝗹𝗸. A plan that made sense 30 days ago can be lethal today.

That is why Brazil is quietly becoming the most advanced decision environment in global agriculture.

Not because it has more data. But because it has less tolerance for being wrong.

➤ When China tightens beef quotas.
➤ When the Brazilian real moves five percent.
➤ When fertilizer costs jump.
➤ When weather shifts planting windows.

The winners will not be the farms, processors, or exporters with the best dashboards.

They will be the ones who can 𝗿𝗲-𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝘁𝗵𝗲 𝘄𝗵𝗼𝗹𝗲 𝘀𝘆𝘀𝘁𝗲𝗺 𝗶𝗻 𝗵𝗼𝘂𝗿𝘀, 𝗻𝗼𝘁 𝗾𝘂𝗮𝗿𝘁𝗲𝗿𝘀.

This is where AI stops being a reporting tool and becomes an operating system.

Not “what happened.”
But “𝘄𝗵𝗮𝘁 𝘀𝗵𝗼𝘂𝗹𝗱 𝘄𝗲 𝗱𝗼 𝗻𝗼𝘄.”

We built SWARM around this reality long before most of the world caught up to it: 𝘃𝗼𝗹𝗮𝘁𝗶𝗹𝗲 𝗽𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝗻𝗲𝗲𝗱 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗲𝗻𝗴𝗶𝗻𝗲𝘀, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗮𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀.

Brazil in 2026 is not an emerging market.

It is a stress test for whether #AI can actually run a complex, high-stakes economy in motion.

And the rest of the world is about to learn from it.

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Proud to be speaking at the 𝗶𝗻𝗮𝘂𝗴𝘂𝗿𝗮𝗹 𝗚𝘂𝗹𝗳𝗼𝗼𝗱 𝗪𝗼𝗿𝗹𝗱 𝗘𝗰𝗼𝗻𝗼𝗺𝘆 𝗦𝘂𝗺𝗺𝗶𝘁 this month.

From 26–29 January 2026, ministers, policymakers, and CEOs will come together in #Dubai to confront the hardest question in food and trade:

𝗛𝗼𝘄 𝗱𝗼 𝘄𝗲 𝗯𝘂𝗶𝗹𝗱 𝗳𝗼𝗼𝗱 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝘀𝘂𝗿𝘃𝗶𝘃𝗲 𝘃𝗼𝗹𝗮𝘁𝗶𝗹𝗶𝘁𝘆 𝗶𝗻𝘀𝘁𝗲𝗮𝗱 𝗼𝗳 𝗰𝗼𝗹𝗹𝗮𝗽𝘀𝗶𝗻𝗴 𝘂𝗻𝗱𝗲𝗿 𝗶𝘁?

This is not about trends. It is about 𝗰𝗹𝗶𝗺𝗮𝘁𝗲 𝗿𝗶𝘀𝗸, 𝗴𝗲𝗼𝗽𝗼𝗹𝗶𝘁𝗶𝗰𝗮𝗹 𝘀𝗵𝗼𝗰𝗸, 𝗳𝗿𝗮𝗴𝗶𝗹𝗲 𝘀𝘂𝗽𝗽𝗹𝘆 𝗰𝗵𝗮𝗶𝗻𝘀, 𝗮𝗻𝗱 𝗿𝗲𝗮𝗹 𝗲𝗰𝗼𝗻𝗼𝗺𝗶𝗰 𝗿𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝗰𝗲.

Food security in 2026 will not be decided by who has the most data.
It will be decided by who has 𝗔𝗜 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻 𝘁𝘂𝗿𝗻 𝘂𝗻𝗰𝗲𝗿𝘁𝗮𝗶𝗻𝘁𝘆 𝗶𝗻𝘁𝗼 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀, 𝗳𝗮𝘀𝘁 𝗲𝗻𝗼𝘂𝗴𝗵 𝘁𝗼 𝗺𝗮𝘁𝘁𝗲𝗿.

In a world of climate shocks and broken trade lanes, 𝗔𝗜 𝗶𝘀 𝗻𝗼 𝗹𝗼𝗻𝗴𝗲𝗿 𝗮 𝘁𝗼𝗼𝗹. 𝗜𝘁 𝗶𝘀 𝗮 𝘀𝘂𝗿𝘃𝗶𝘃𝗮𝗹 𝗹𝗮𝘆𝗲𝗿.

I will be sharing what it takes to build 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗱𝗿𝗶𝘃𝗲𝗻, 𝘁𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝘁, 𝗮𝗻𝗱 𝗰𝗹𝗶𝗺𝗮𝘁𝗲-𝘀𝗺𝗮𝗿𝘁 𝗳𝗼𝗼𝗱 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 when stability is gone and every choice carries consequence. If you care about the future of food, trade, and global security, this is where the real conversations are happening.

https://lnkd.in/g5CNeeQ6 

#WorldEconomySummit #Gulfood2026 #FoodSecurity #ClimateRisk #SupplyChains #AI SWARM

𝗪𝗵𝘆 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗔𝗜 𝗶𝘀 𝗳𝗮𝗶𝗹𝗶𝗻𝗴 𝘁𝗵𝗲 𝗥𝗢𝗜 𝘁𝗲𝘀𝘁.

Most companies are paying a hidden "Ontology Tax." 🛑

They spend 18 months trying to map their entire world before the AI makes a single decision.

It’s too slow.
It’s too expensive.
It’s usually wrong by the time it's finished.

At SWARM, we do it differently. We use Decision Traces. Instead of modeling the world upfront, we capture it in motion:

What rules were actually used? Who approved the exception? What outcome followed?

This creates a Context Graph that grows with your business. It doesn’t break when the world changes - it adapts.

𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗯𝗿𝗲𝗮𝗸𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗶𝘀𝗻’𝘁 𝘀𝗺𝗮𝗿𝘁𝗲𝗿 𝗺𝗼𝗱𝗲𝗹𝘀. 𝗜𝘁’𝘀 𝗯𝗲𝘁𝘁𝗲𝗿 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀.

#SupplyChain #EnterpriseAI #DecisionIntelligence

After becoming an 𝗔𝗺𝗮𝘇𝗼𝗻 𝗯𝗲𝘀𝘁𝘀𝗲𝗹𝗹𝗲𝗿 at launch, I am honored to share that  𝘈𝘨𝘦𝘯𝘵𝘪𝘤 𝘈𝘳𝘵𝘪𝘧𝘪𝘤𝘪𝘢𝘭 𝘐𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘤𝘦 made it into Forbes and gets mentioned as the 𝗧𝗼𝗽 𝟭𝟬 𝗠𝘂𝘀𝘁-𝗥𝗲𝗮𝗱 𝗧𝗲𝗰𝗵 𝗕𝗼𝗼𝗸𝘀 𝗼𝗳 𝟮𝟬𝟮𝟱 just two weeks ago.

This book wasn't born in a vacuum. It came out of a lot of long conversations with various authors about what we were all seeing in the field across the AI economy - from research and consulting to enterprise operations, product, and startups. 

But we were all noticing the same thing. #AI was quietly moving from tools and dashboards into systems that act.

This was not a "theory" book. It was a field report. When multiple people with very different incentives and vantage points start describing the same shift, it usually means something real is happening.

We wrote it because that change felt bigger than most people realized at the time. The list is nice. What matters more is that the world has now caught up. 

Enterprises are actually deploying agents that schedule, allocate, optimize, and make decisions in live environments. The questions we wrestled with on paper are now showing up in boardrooms and operating rooms.

Grateful to everyone who has read it, challenged it, or built on it.

The next phase of AI is not about smarter chatbots. It is about systems that act in the real world. And we are just getting started. 

Forbes Link - https://lnkd.in/g4Gq3mMZ

Pascal BORNET, David De Cremer, Tom Davenport, Brian Evergreen, Phil Fersht, Rakesh Gohel, Shail Khiyara
 
https://lnkd.in/grGWSqcg

Big news to share: the book we 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗱 𝘁𝗵𝗶𝘀 𝘄𝗲𝗲𝗸 𝗷𝘂𝘀𝘁 𝗵𝗶𝘁 𝘁𝗵𝗲 𝗔𝗺𝗮𝘇𝗼𝗻 𝗕𝗲𝘀𝘁 𝗦𝗲𝗹𝗹𝗲𝗿𝘀 𝗹𝗶𝘀𝘁.

My intention was to spark new thinking, challenge assumptions, and contribute to the evolving conversation around #AgenticAI, the transformation (again) of #IntelligentAutomation and what's next in the future. 

𝗚𝗿𝗮𝘁𝗲𝗳𝘂𝗹 𝗳𝗼𝗿 𝘁𝗵𝗲 𝘀𝘂𝗽𝗽𝗼𝗿𝘁, 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸, 𝗮𝗻𝗱 𝗰𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆 𝗳𝗿𝗼𝗺 𝘀𝗼 𝗺𝗮𝗻𝘆 𝗼𝗳 𝘆𝗼𝘂. Honored that it’s landing with readers. Equally honored and grateful that I could work with this most accomplished and distinguished group of coauthors: Pascal BORNET, Tom Davenport, David De Cremer, Jochen Wirtz, Brian Evergreen, Phil Fersht, Rakesh Gohel ! 

#AmazonBestSeller #ThankYou #AI #Leadership #Automation #BookLaunch #Gratitude

Agentic Artificial Intelligence

AI didn’t fail to transform operations.

The decision structures underneath never changed. Real transformation starts there.

#decisionintelligence SWARM  
Deloitte Insights

𝗪𝗵𝗮𝘁 𝗶𝗳 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝗔𝗜 𝗯𝗿𝗲𝗮𝗸𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗶𝘀𝗻’𝘁 𝘀𝗺𝗮𝗿𝘁𝗲𝗿 𝗺𝗼𝗱𝗲𝗹𝘀, 𝗯𝘂𝘁 𝗯𝗲𝘁𝘁𝗲𝗿 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀?

For years, enterprise software optimized for data throughput.
Load tables. Run queries. Ship dashboards.

𝗕𝘂𝘁 𝗟𝗟𝗠𝘀 𝗮𝗻𝗱 𝗮𝗴𝗲𝗻𝘁𝘀 𝗱𝗼𝗻’𝘁 𝘄𝗮𝗻𝘁 𝗿𝗮𝘄 𝗿𝗼𝘄𝘀. 𝗧𝗵𝗲𝘆 𝘄𝗮𝗻𝘁 𝗰𝗼𝗻𝘁𝗲𝘅𝘁. 𝗠𝗲𝗮𝗻𝗶𝗻𝗴. 𝗖𝗮𝘂𝘀𝗮𝗹𝗶𝘁𝘆.

They want the world represented the way humans reason about it.

That’s why #ontology-first platforms suddenly make sense in the LLM era. They give models a structured world to reason over. But they also come with a heavy tax: long implementations, deep modeling, cross-team alignment, and ROI that can take years.

𝗧𝗵𝗲𝗿𝗲’𝘀 𝗮𝗻𝗼𝘁𝗵𝗲𝗿 𝗽𝗮𝘁𝗵.
𝗜𝗻𝘀𝘁𝗲𝗮𝗱 𝗼𝗳 𝗺𝗼𝗱𝗲𝗹𝗶𝗻𝗴 𝘁𝗵𝗲 𝘄𝗼𝗿𝗹𝗱 𝘂𝗽𝗳𝗿𝗼𝗻𝘁, 𝘀𝘁𝗮𝗿𝘁 𝗯𝘆 𝗰𝗮𝗽𝘁𝘂𝗿𝗶𝗻𝗴 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀.

➤ What data was referenced.
➤ What rules or policies applied.
➤ What exceptions occurred.
➤ Who approved what.
➤ What action was taken.
➤ What outcome followed.

Those decision traces preserve the why, not just the state. Over time, they form context graphs that naturally reveal the entities, relationships, and constraints that actually matter. Not because an engineer prescribed them, but because the business demonstrated them.

This doesn’t eliminate the need for governance. Authority still matters. Semantics still matter. But instead of guessing upfront, you standardize what proves stable and keep the rest adaptable.

At SWARM, this is how we think about decision intelligence. Every recommendation carries its lineage. The logic, the constraints, the tradeoffs. Not just an answer, but an explanation you can trust.

𝗔𝗜 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻’𝘁 𝗲𝘅𝗽𝗹𝗮𝗶𝗻 𝗶𝘁𝘀𝗲𝗹𝗳 𝗶𝘀𝗻’𝘁 𝗿𝗲𝗮𝗱𝘆 𝗳𝗼𝗿 𝗿𝗲𝗮𝗹 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀.
Decision traces are how we get there.

#AgenticAI #EnterpriseAI #SupplyChain #Operations

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Andreas Welsch

Shail Khiyara

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The Battle

Andreas Welsch

Shail Khiyara

Followers

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Engagements

Likes

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);}Shail Khiyara's LinkedIn Performance

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