The most memorable moment for me at Gartner’s Supply Chain Symposium in Barcelona 2026 wasn’t another AI success story. It was one of the conference’s keynote presentations, which challenged one of AI’s underlying assumptions.

Throughout the conference, organizations shared impressive examples of using AI to automate processes, accelerate decision making, and generate insights. Global companies demonstrated how AI is becoming deeply embedded in procurement and supply chain operations, promising greater efficiency, faster execution, and better visibility.

The conversation largely focused on what AI can do. Then keynote speaker, digital anthropologist, and bestselling author Rahaf Harfoush shifted the conversation from AI’s capabilities to its human consequences.

She introduced a concept I hadn’t encountered before: infobesity.

AI Has Solved Information Scarcity. It Has Created Infobesity.

Harfoush describes infobesity as the tendency for individuals and organizations to consume more information than they can realistically process. 

One of Harfoush’s most thought-provoking observations was that organizations increasingly confuse consuming information with making progress:

• Reading another report isn’t the same as learning.
• Generating another dashboard isn’t the same as gaining insight.
• Receiving another AI summary isn’t the same as making a better decision.

The concept immediately resonated with me because, like many professionals today, I’ve often struggled to synthesize the enormous amount of information now available at my fingertips.

For decades, technology has focused on making information easier to access. AI has made information almost effortless to create—but not necessarily easier to evaluate.

But our ability to consume, prioritize, and act on that information has not evolved at the same pace.

The idea fundamentally changes the question we should be asking about AI. Much of today’s discussion around AI focuses on familiar concerns:

• Hallucinations and data accuracy
• Privacy and intellectual property
• Environmental impact
• Job displacement
• The long-term implications of increasingly autonomous systems

Yet comparatively little attention has been given to a different question: How do we prevent AI from overwhelming us with more information than we can meaningfully process?

According to Harfoush, infobesity has several characteristics that leaders should be thinking about:

• More information does not necessarily create better decisions.
• Infobesity can accelerate burnout.
• AI-Generated “Workslop”
• Intentional information diets matter.
• Discernment is becoming a top leadership skill.
• AI should reduce friction, not increase noise.

Let’s explore each of these.

More Information Does Not Necessarily Create Better Decisions

Organizations often assume that more information leads to better decisions.

But information and insight are not the same thing.

At some point, additional information stops improving decisions and begins delaying them. Instead of increasing confidence, it can create uncertainty, encourage over-analysis, or make it harder to distinguish what is truly important.

Procurement and supply chain professionals are particularly vulnerable to this. Every day we monitor supplier performance, freight markets, commodity pricing, tariffs, geopolitical developments, sustainability regulations, inventory, quality metrics, customer demand, and countless internal KPIs. AI now allows us to generate even more analysis across every one of these areas.

Individually, each source provides value. Collectively, they can make it harder to identify the few insights that actually require action.

The challenge is no longer finding information. It’s knowing which information matters enough to change a decision.

AI-Generated “Workslop”: Another Symptom of Infobesity

One consequence is AI workslop: AI-generated emails, reports, presentations, meeting notes, and other workplace content that appears polished at first glance but often lacks accuracy, context, originality, or sound judgment.

The content often looks polished but proves repetitive, inaccurate, or lacking the context needed to answer the real question.

Anyone who has spent two hours reviewing an AI-generated report or editing an AI-generated email understands the irony. Creating the content may take seconds. Ensuring it is accurate, useful, commercially appropriate, and worth sharing still requires human judgment.

AI often shifts work rather than eliminating it, replacing the effort of creating a first draft with the effort of reviewing, correcting, and refining one.

Infobesity Can Accelerate Burnout

The problem with workslop isn’t simply that it exists. It’s that someone still has to consume it.

Every AI-generated report, email, presentation, and meeting summary competes for human attention. As the volume of AI-generated content grows, so does the pressure to read more, review more, respond faster, and produce even more content.

AI promises greater efficiency. But if implementation focuses primarily on generating more information rather than reducing unnecessary information, organizations risk replacing repetitive manual work with repetitive cognitive work.

Human attention remains finite.

Greater efficiency should create more space for strategic thinking, collaboration, and innovation—not more digital noise. Otherwise, AI risks contributing to cognitive fatigue and burnout rather than alleviating it.

Intentional Information Diets Matter

One of the most practical ideas from the keynote was the concept of an intentional information diet.

Just as healthy eating is about quality rather than quantity, healthy individuals and organizations should become more deliberate about the information we consume.

Harfoush proposed a simple framework for developing a healthier information diet:

• 50% Breadth: Cross-disciplinary learning from a variety of sources.
• 40% Depth: Deep work that challenges your thinking and cognitive abilities.
• 10% Novelty: Unexpected ideas and connections that break existing patterns. (Apparently, Wiki Roulette is a great way to do this!)

Discernment: The Leadership Skill AI Can’t Re place

As AI democratizes information generation, discernment becomes a competitive advantage.

Tomorrow’s most valuable leadership skills won’t be generating more information. It will be recognizing which information deserves attention, challenges existing assumptions, encourages innovation, and carries genuine strategic, operational, or commercial significance.

One point I found particularly compelling was Harfoush’s observation that information without integration is just noise.

Collecting information isn’t enough. Leaders must continually ask:

• What should we do with this information?

• How will it impact our business?

• How do we integrate these learnings into our organization?

This is where AI delivers its greatest value.

Used intentionally, AI sh ould organize research, identify patterns, synthesize insights, and eliminate repetitive information-management tasks.

Its purpose shouldn’t be to generate more content. It should help people exercise better judgment.

Why This Matters for Supply Chain Leaders

This concept felt particularly relevant for procurement and supply chain professionals because our industry already operates in an environment saturated with information.

Every day we evaluate suppliers, monitor global events, interpret regulations, negotiate contracts, assess quality, manage logistics, and respond to changing customer requirements.

AI can help us do many of those things faster. But more information doesn’t automatically produce better decisions. The most successful companies will increasingly ask: How can AI help our people think more clearly and focus on what matters most?”

Ultimately, business is about people.

Technology, data, and AI are powerful tools, but they should strengthen human judgment, not replace it.

The strongest supply chains are still built on trusted relationships, thoughtful decision making, and experienced professionals who understand context, nuance, and commercial realities. AI can accelerate many aspects of that work, but it cannot replace the conversations that build trust, the judgment that comes from experience, or the relationships that ultimately drive successful business partnerships.

Perhaps the future of AI won’t be measured by how much information it creates.

It will be measured by how effectively it helps people think more clearly, make better decisions, and focus on what truly matters.